The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types . We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. Statistical analysis of shape is a fundamental problem that is frequently encountered in biology. In paleontology, the bulk of information about the prehistoric world is deduced from the shape of fossils, whereas in developmental genetics the phenotypic significance of genes and pathways is often inferred from shape abnormalities. Automatic detection of phenotypic features is hindered by the facts that 3D morphology is difficult to measure and that the theory behind the analysis of complex structures such as 3D surfaces or density maps is more or less in its infancy Unlike morphological data, other types of 3D data have been deposited in databases for some time, with examples ranging from 3D statue scans We selected mammalian teeth as the morphological system to focus on because these structures have several attractive properties: in any given species tooth shape is generally very consistent and tightly regulated by genes, tooth shape is adaptive and correlates with the physical properties of key dietary sources Statistical analysis of dental shape carried out until now can be coarsely grouped into three different approaches with the main difference being the type of model used to represent the shape of analyzed samples. In the most traditional approach, samples are compared by taking sets of linear measurements of defined local structures present on the surface of a tooth crown , sizes of feature sets found and searching times across the classification models . The seatooth-diet, toothrow-diet, tooth-morph and toothrow-morph training sets respectively. As expected, a best-first search initiated from an empty subset found on average the smallest subsets. Subsets found by repeatedly initiating a best-first search from random starting points were about two to three times larger and those found by rank search from two to four times larger.Repeating the best-first search from 50 random subsets improved performance only slightly: by 4%, 7%, 1% and 3% for the tooth-diet, toothrow-diet, mixed-diet, tooth-morph and toothrow-morph training sets respectively. Best-first search was at most twice as slow, with corresponding times being 23, 18, 72, 29 and 16 sec. Repeated best-first search was from 700 to 2500 times slower with average searching times ranging from two to six hours.The linear rank search was the fastest, with average searching times 14, 10, 34, 18 and 9 sec for the tooth-diet, toothrow-diet, mixed-diet, tooth-morph and toothrow-morph training sets respectively.1-NN (1-nearest neighbor) was consistently the best classifier for all five problems indicating the mosaic-like partition of the underlying feature space. Performances of other NN models varied across different problems from as good as 1-NN to several times less accurate. Differences between the best generative (naive Bays with multivariate kernel (NB-N) and normal (NB-K)) and the best non generative (C4.5 decision tree and NN) models were 5%, 8%, 12%, 5% and 4% for toothrow-morph training set was 97% accurate, for tooth-morph training set 94% accurate and for tooth-diet, toothrow-diet and mixed-diet training sets 93%, 91% and 85% accurate respectively. Performance on samples outside the training sets can be evaluated using the ToothKit software that is supplied with the best generative and non generative classifiers that are asterisked in Accuracy (accuracy = 1–CVER) of the best classifiers was at least 85% for all five training sets. Best classifier for We were also interested in which features were used by different classification tasks. We assumed that this is best revealed by the probability distribution of features in the selected subsets averaged across all subsets selected for a given classification task. The probability distribution of a feature in a set is its frequency in that set (0 or 1) normalized by the length of the set. The top ten features ranked by their mean probability are given in tooth-diet and toothrow-diet top tens, but, quite expectedly, 4 and 3 common features between top tens of these sets and the mixed set respectively. This appears to be good evidence of the repeatability of feature selection. Top ten features for dietary prediction and dental type prediction had several matches. This is particularly the case for the mixed-diet problem .Here, we have demonstrated how the analysis of 3D phenotypes can be automated: the researcher selects phenotypes for the training set, converts them to DEMs, labels samples by the categorical variable of interest, extracts features, runs feature selection and applies the obtained classifiers to new samples. Notably, most of these steps are automated, where only the selection and labeling of the training set need to be carried out by the investigator. The selection of samples can be further facilitated by gathering 3D phenotypes into databases, which has already started to happen A couple of the features show distinctly higher occurrences in the training sets. D2dist mean  and that, in spite of partial overlaps, different problems favored different features.Comparisons of feature selection schemes, classification models and features revealed several important aspects. Compared to feature ranking, direct evaluation of feature subsets produced clearly better classifiers at a moderate cost of approximately doubling the searching time. Repeating the best-first search, on the other hand, does not appear beneficial as a thousand-fold increase in computation time is traded for only a moderate improvement in accuracy. NN models were consistently the best for all five problems, and were on average two times better than the generative NB models. However, in terms of absolute accuracies both NB and Tree/NN models performed well for all but the mixed set, with CVER ranging from 7% to 15% and from 3% to 9% respectively. Presumably due to its large size, There are at least two straight-forward applications for the classifiers we obtained. First, the classification model can be used to extrapolate relationships between shape and the variable of interest from the training set to new instances. This has immediate applications in paleontology where classifiers built on extant species can be used to reconstruct diet and other variables for extinct species. Moreover, such reconstructions will be objective as they will not include subjective assessments beyond the selection of the training sets. Another application is developmental biology where one central aim is to link abnormal shapes to underlying developmental mechanisms, and our approach can be used together with forward genetics to screen new phenotypes for which the underlying development is not yet known.k morphologies in the database that are most similar to either a specific query or specific query morphology dm is the database morphology, qm the query morphology, and dist the posterior distribution assigned by the employed classifier. To illustrate this idea, ToothKit implements a search function that allows the user to search a disk using any of the classifiers supplied with the program and the similarity measure as defined in the above equation. Preliminary tests using tooth-morph and toothrow-morph classifiers suggest that these searching schemes return morphologies that are considered relevant in terms of general shape similarity. In future studies, performance can be assessed more formally by precision-recall and other measurements.Second, using these classifiers we can implement retrieval by content for unannotated databases of 3D phenotypes, i.e. finding the Whereas our study brings automated approaches into the domain of biological shape analysis, it obviously does not provide a foolproof technique for all morphologies or classification tasks. Biological 3D objects, which vary greatly among species and from individual to individual, are especially challenging for statistical comparison and major advances in theory of this field are needed before any two 3D surfaces or solids can be compared within a universal framework. However, this study does demonstrate that for a limited domain of 3D shapes it is possible, and actually quite straightforward, to define a set of features that will provide a basis for automated statistical analysis. In addition to teeth, GIS-like feature extraction is applicable to many other objects that approximate 2.5D surfaces, both biological  and non-biological (land forms). Whereas many of the features used on teeth to build classifiers may be applicable to other shapes, it remains to be seen how successful these features would be at classifying diverse biological shapes. Interestingly the D2 shape function (the mean distance between two random surface points), which was successfully incorporated into several classifiers, was adapted from a general purpose comparison approach designed to discriminate between 3D objects that have nothing to do with teeth (such as CAD models for cars). This suggests that features do not have to be system-specific. On the other hand, the frequently used features in classifications may be helpful in identifying functionally significant aspect of morphology. For example, the OPC was previously suspected to be informative in distinguishing diet Yet another consideration is the efficiency of automated 3D analysis in comparison to trained persons. Our informal tests suggest that expert opinion (with over 20 years' experience) is at least as accurate as our automated routines. However, expert opinions do not provide implicit probabilities and are limited to a small set of  classification problems. Additionally, with an increasing number of teeth, the automated routines becomes more efficient, especially if we consider that each new classification problem would require manual reinspection of each specimen by a person. Therefore, we envision that these new types of morphological analyses promise not only informative ways for classifying morphologies, but may also be useful in exploring classic questions of morphospace occupation, and tempo and mode in morphological evolution e.g. .When implemented in conjunction with a 3D morphological database, this approach has the potential to boost the application of 3D shape analysis, since even non-experts will gain the ability to build “on the fly” descriptive/predictive models from arbitrary sets of 3D scans. Advances along these lines will push the development of 3D morphology analysis towards the ease of the current sequence analysis.tooth-diet and toothrow-diet sets, morphologies were labeled according to the dietary preferences of the corresponding species , selenodont tooth row (SelTr), lophodont tooth row (LophTr), and bunodont tooth row (BunTr). The test sets were comprised of teeth from members of the Orders Artiodactyla, Carnivora, Chiroptera, Perissodactyla, Primates and Rodentia . Before scanning, teeth were oriented manually to maximize crown-base projection in the xy-plane. Scanning produced unordered point cloud files that were further processed to digital elevation models (DEMs). A 2D outline of the single tooth/tooth row was selected to separate the analyzed surface from the background of the maxilla bone and the fixative material. This was done by picking a sequence of boundary points using Surfer Version 8 software. Boundary points were then used to delete the background part of the point cloud in Matlab Version 7. The remaining surface points were interpolated to DEM using triangle-based cubic interpolation implemented in Matlab griddata function. Artifacts in concave regions of the surface boundary produced during surface interpolations based on convex hulls were deleted using boundary points. The total resolution of DEMs (number of rows×number of columns) was set to be approximately 10 000 points for single teeth and 50 000 points for tooth rows by setting digital grid resolution as a function of the dimensions of the point cloud's bounding box:delta x and delta y are the point cloud's bounding box dimensions in the xy-plane, N is 10 000 or 50 000 depending on the sample, and res is the resolution of the digital grid.Samples were scanned using Nextec Hawk 3D laser scanner and Roland Dr Picza needle scanner at between 10 and 50 µm resolution, depending on the size of the sample. Scans were added for interactive viewing in our online database MorphoBrowser (see Pilot studies using various resolutions were undertaken to find a middle resolution that was not so low as few of the major features were not present (such as cusps and crests), but not so high as to either give greater emphasis to very small features or to slow down scan processing. For other data types (e.g. skin wrinkling or joint surface shape), other resolutions may be more applicable.To extract features we implemented five Matlab procedures with each procedure designated to a particular feature type. The exact definition of a feature could be modified by varying values of input parameters. Using these, we extracted 100 features , the number of subsections (p2) and the index of the section examined (p3).These features are referred using “noc) based on the angle between the xy-component of the corresponding normal and the reference vector. Third, vertices belonging to the same orientation class were clustered into patches according to 4-cell connectivity. Finally, patches smaller then a threshold value of minps*projA were discarded, where minps is the minimum patch size, and the number of the remaining patches was returned as the OPC.OPC is a measure of surface discontinuity that is quantified as the number of surface patches with different orientations in the xy-plane C. This da parameter) counterclockwise until it was shifted to the next orientation class as defined by the reference vector's initial direction. Examinations of the variance for mixed-diet showed that the maximum value from this rotation series is less affected by rotation (data not shown), hence we used the Maximum of Rotated Orientation Patch Count (MROPC).To improve invariance against rotation in the xy-plane several OPC values were calculated by iteratively shifting the reference vector counterclockwise. The reference vector, which initially points along the x-axis, was iteratively shifted by 9 degrees .These features are referred using “To perform data mining we used algorithms for probabilistic classification, model validation and feature selection, implemented in an open source WEKA library weka.classifiers.bayes.NaiveBayes, with both normal and kernel density functions. Decision trees were built using C4.5 algorithm weka.classifiers.trees.J48. To construct k-nearest neighbor models we used weka.classifiers.lazy.Ibk. Number of neighbors was set to 1, 3, 5 and 7, with neighborhood defined by Euclidean distance.We used three types of probabilistic classification models: naive Bayes weka.attributeSelection.WrapperSubsetEval, with the seven classification models described above.Cross validation is a measure of model accuracy and its robustness against random changes in the relative composition of the training data and the data for which an inference is made In machine learning it is well recognized that the exact feature combination used for a particular classification task is generally the single most influential factor affecting classification accuracy weka.attributeSelection.RankSearch coupled to information gain measure weak.attribureSelection.InfoGainAttributeEval and the best-first search weka.attributeSelection.BestFirst.For the evaluation of feature subsets all searches used 10-fold cross validation combined with one of the seven classifiers. We used rank search http://www.biocenter.helsinki.fi/bi/evodevo/toothkit/index.html.In this freeware Java program we implemented some of the major functionalities discussed above: converting *.stl, *.obj, *.dxf and *.wrl polygon meshes into DEMs, feature extraction, classification and retrieval by content. ToothKit is supplied with trained classifiers asterisked in Table S1Composition of the training sets.(0.24 MB DOC)Click here for additional data file.Table S2Comparing feature selection schemes and classification models.(0.11 MB DOC)Click here for additional data file.Table S3Feature names and IDs.(0.09 MB DOC)Click here for additional data file.


Guthrie cards from 54 patients with ALL and 47 healthy controls matched for age and birth place were tested negative for both HHV-6 and EBV DNA. All samples contained amplifiable DNA when tested by HLA-DQ PCR. Our negative findings suggest that childhood ALL is unlikely to be associated with an  Acute lymphoblastic leukaemia (ALL) is the most frequent childhood malignancy in Western countries. The different subtypes of leukaemia differ in their patterns of genetic change, natural history, prognosis and possibly aetiology . One modin utero) transmission. Since they persist and establish latency in their natural host after primary infection, they may be reactivated during immunosuppression (Epstein–Barr virus (EBV) and human herpes virus 6 (HHV-6) are two potentially oncogenic viruses, widely distributed in the human population, which can be spread by vertical or horizontal  and four children were diagnosed as T-ALLs (CD3+ or CD8+). A total of 24 children were diagnosed before the age of 4, 16 children were between 5 and 9 years, 12 children were between 10 and 14 years of age and two children were older than 14 years. The median age at diagnosis was 5 years . These children had been admitted for treatment at four different Paediatric Oncology Swedish Centres from 1980 through 2001. As a control group, we obtained 47 healthy controls that were matched for age and birthplace, and data from the controls were collected from the Swedish Medical Birth Register, which is a standardised set of medical records introduced in Sweden in 1973 (Two bone marrow-transplanted patients were positive for HHV-6 and EBV-DNA, respectively. These two patients were included as positive controls. Guthrie cards ‘spiked’ with blood from these patients were tested for the presence of HHV-6 or EBV DNA. Blood samples were taken from these two patients and added to a new Guthrie card.At the time of analysis, the filter paper samples were stored at room temperature before extraction. The extraction method utilised was MEM extraction, previously described, with minor modifications (Presence of HHV-6 DNA was analysed by a nested PCR, with the primers corresponding to the conserved region of HHV-6 of both variants A and B amplifying a 173 bp segment (Presence of EBV DNA was analysed by a nested PCR with the primers corresponding to the fragment of EBV EBNA gene 1 amplifying a 208 bp segment (As a control for the presence of DNA extracted from Guthrie cards and for DNA amplifiability, a PCR with a set of HLA DQ primers was performed (Written informed consent was obtained from patients, controls and parents. The local ethics committee of the Karolinska Institutet at Karolinska University Hospital approved the study protocol.The Guthrie cards of all 54 patients with ALL, as well as all 47 healthy controls, were tested negative by PCR for both HHV-6 DNA and EBV DNA. All samples contained amplifiable DNA when tested by HLA-DQ PCR. HHV-6 or EBV DNA could be detected in the blood as well as in the ‘spiked’ Guthrie cards from the two BMT patients with HHV-6 and EBV infection, respectively.The use of stored Guthrie cards as a source of DNA has been shown to have several uses. DNA is relatively stable and blood collected from newborns contains 2–3 times higher levels of nucleic acid when compared to adults. In several studies, it has been shown that viral DNA could be successfully amplified from Guthrie cards in case of congenital CMV, HSV and HIV infection (in utero with a virus that has the oncogenic potential could be involved in the initiation of ALL, by inducing genomic instability and allowing specific effects on B lymphocytes. Twin studies suggest that an additional molecular event or exposure is then required postnatally for the preleukaemic clone to expand. The second event, leading to leukaemia, can occur at a time of maximum stress on lymphocyte precursor proliferation and may be promoted by exposure to a common infectious agent (The difficulty to divide childhood leukaemia into homogenous subgroups may explain the complexity when investigating different aetiological factors. In our material, the majority of children had pre-B-ALL. It has been suggested that infection in utero. But there are also opportunities for leukaemogenic infection to occur after birth and before the children in space–time clustering studies have moved away from birth addresses.Space–time clustering of ALL has raised the possibility of an infectious agent in ALL. Kinlen and others proposed that the mixing of previously separate groups of people, as in the creation of new towns in rural construction projects or military camps, may raise the incidence of leukaemia by facilitating transmission of infective agents (Another model for virus transmission during pregnancy is suggested by observations that leukaemia in cats can result from maternal transmission (Intrauterine infection is a result of either primary maternal infection or reactivation of the latent infection. Primary infection with HHV-6 during pregnancy is a rare event, since more than 90% are seropositive at the age of 3, infection being most frequent during the first year of life . In a reThe fact that neither HHV-6 DNA nor EBV were detected in dried blood spots obtained from newborns at birth indicates that congenital infections with these viruses are uncommon. The possibility of false-negative results due to infection early in pregnancy and being latent at birth must be considered. However, for congenital CMV infection, it has been shown that Guthrie cards were positive for CMV DNA even when the maternal infection took place during the first or second trimester, indicating that viremia persisted to birth . Similarin utero infection with these viruses although a latent infection cannot be ruled out by this method, nor infection after birth. In view of the epidemiological evidence for a relation between childhood ALL and infection, the search for a virus aetiology must continue.HHV-6 DNA and EBV-DNA were neither detected by PCR in blood from Guthrie cards in children who had developed ALL nor from healthy controls. Hence, it is unlikely that childhood ALL is associated with an


Stabilization for recurrent anterior shoulder dislocation can be achieved through either an open or arthroscopic approach. The former tends to have a lower recurrence rate but longer rehabilitation.The technique of mini-Bankart repair has been used at this establishment since 1996. We retrospectively reviewed the patients that had undergone this procedure. We describe our experience of the mini-Bankart procedure and the results in 24 patients with a mean follow-up of 56 months .The technique is a direct mini-approach to the shoulder joint, preserving the inferior portion of subscapularis. Where present, a Bankart lesion is repaired with two GII Mitek anchors (Ethicon) and the capsule reefed. There were no incidences of repeat anterior dislocation, and the average time period taken to return to work was 8.8 weeks. We recommend this technique due to its low recurrence rate and satisfactory return to normal function. Young adults that sustain a traumatic dislocation of the shoulder have a high risk of further dislocations. The reason for over 85% of these recurrent dislocations is the Bankart lesion , although5Surgeons favoring arthroscopic repair describe benefits relating to smaller incisions, an improved range of postoperative movement, an earlier return to work and sport and a lower risk of subscapularis failure. It has been demonstrated that patients treated arthroscopically do have higher functional scores postoperatively, but there is a significantly increased risk of subsequent instability and re-dislocation when compared to the open technique (12-16%).Consequently, the senior author (ACC) has developed a mini-open Bankart procedure, with the aim of combining the stability of the open approach with the improved functional outcomes of the arthroscopic technique. We describe the procedure here and the postoperative outcome in 24 patients with a mean follow-up of 56 months .The patient is placed in the deck chair position. A 5-cm vertical incision is made 2 cm lateral to the coracoid process, extending towards the axillary fold . The conWhere present, a Bankart lesion is freshened with a burr drill and repaired with two GII Mitek anchors . The anchors are placed at 3- and 5-o'clock positions for right shoulder ; and 7- Postoperatively, patients are placed in a polysling for 6 weeks; ensuring external rotation is avoided for the initial 3 weeks. Patients are under immediate supervision of physiotherapists.Twenty-four procedures have been performed in 24 patients  with a mean age of 28 years  and a mean follow-up of 56 months . There were 10 right-sided and 14 left-sided procedures. Twenty-one primary stabilizations were performed; with 3 revision procedures, all of whom had undergone their primary surgery in other institutions. All 24 patients had recurrent dislocations with unidirectional instability, and all had a Bankart lesion evident at surgical repair.There were no incidences of repeat anterior dislocation, although there was 1 posterior dislocation 2 years postoperatively following subsequent traumatic event, which was managed conservatively. Twenty-two patients have returned to work after a mean duration of 8.8 weeks . Those in desk jobs returned after 5.6 weeks, while manual workers recommenced work after 11.2 weeks . Of the 2 patients not returning to work, one patient had been unemployed prior to developing shoulder instability and the other is awaiting stabilization of the contralateral shoulder. All patients have also returned to sport, after a mean time period of 22 weeks  postoperatively. One patient complained of perceived limitation of movement; there was 1 incident of superficial wound dehiscence and 3 incidents of dysesthesia at the scar. There were no episodes of subscapularis tendon rupture.Recurrent shoulder instability is a relatively common condition usually affecting young adults. Detachment of the antero-inferior labrum (the Bankart lesion) facilitates recurrent anterior instability and can be repaired via an open or arthroscopic approach.vs. 18%) and lower re-dislocation rates (5% vs. 12%) when compared to arthroscopic approach. The meta-analysis by Lenters et al. comparing open and arthroscopic repairs also demonstrated that the open repair is more successful in enabling patients to return to their previous work and/or sport.[Based upon the current literature, open stabilization remains the gold standard, with a statistically significant lower risk of subsequent instability  or arthroscopic repair (12%-16%).7Return to work and sport in our patient group was also comparable with both open and arthroscopic stabilization.8‐10 All Our patient group reported no serious complications. Three have some scar dysaesthesia, although this has previously been recognized in both open and arthroscopic Bankart repairs. One of tHowever, as the study is retrospective, it was not possible to formally compare functional scores preoperatively and postoperatively. Nevertheless, subjectively, all patients felt that their quality of life had improved and were satisfied with their outcome.We recommend mini-Bankart repair technique due to its low recurrence rate and satisfactory return to function.


Presence of lobular intraepithelial neoplasia (LIN) is not routinely reported as part of margin assessment in breast conservation therapy (BCT) as in ductal carcinoma in situ (DCIS). With new emerging evidence of LIN as possible precursor lesion, the hypothesis is that LIN at the margin may increase the risk of local recurrence with BCT. The aim is to determine whether there is an increase incidence of recurrence when LIN is found at surgical margins on BCT.We retrospectively reviewed a total of 1,334 BCT at a single institution in a 10 year period. Inclusion criteria are positive margin with LIN from primary BCT containing invasive and/or in situ carcinoma with comparison to the negative control group who had similar diseases with negative margin for LIN.We identified 38 cases (2.8%) with LIN either lobular carcinoma in situ/atypical lobular hyperplasia (LCIS/ALH) at a margin on initial BCT with 36% recurrence rate. Of the 38 cases: 5 (13%) were lost to follow-up, 12 (32%) had no further procedures performed and 21 (55%) had re-excision. Out of 21 patients who had re-excisions, 12 (57%) had residual invasive carcinoma or DCIS, three (14%) had pleomorphic LCIS and 4 (19%) showed residual classic type LCIS. 71% had significant residual disease  and 29% had no residual disease. A negative control group consisted of 38 cases. We found two patients with bone or brain metastasis and one local recurrence. Clinical follow up periods range from 1 to 109 months.LIN found at a margin on BCT showed a significant recurrent ipsilateral disease. Our study supports the view that LIN seen at the margin may play a role in recurrence. Foote and Stewart  initiallPleomorphic lobular carcinoma in situ (PLCIS) is known as a variant of LCIS which is negative for E-cadherin, supporting lobular differentiation. PLCIS may show central comedo necrosis and a higher nuclear grade resembling DCIS. PLCIS found at a margin has an increased recurrence rate when compared to classic LCIS. Hence it is recommended for re-excision when the surgical margins are involved with PLCIS on BCT. A study on PLCIS at a margin and radiation therapy has yet to be performed and further investigation needs to be done.Moreover, recent studies show that LCIS and invasive lobular carcinoma (ILC) share a similar genetic molecular biology. New research suggests that there is a genetic progression of LCIS to an invasive carcinoma and that the biologic significance of LCIS may be a "field effect" of this lesion for the development of invasive carcinoma -5. With We retrospectively reviewed a total of 1,334 breast surgical excision specimens at a single institution in a 10 year period with a keyword search of "breast, lumpectomy, excision, lobular carcinoma in situ (LCIS) and atypical lobular hyperplasia (ALH)" via our Tamtron Powerpath computer system, after obtaining institutional review board (IRB) approval. We routinely did not use LIN terminology and WHO grading of LIN 1, 2 and 3 in our institution. Our terminology composed of ALH, and LCIS which were the classic type, LCIS with distension and comedo necrosis with nuclear grade 2 and pleomorphic LCIS with nuclear grade 3. Our terminology can be extracted, however, to WHO classifications: LIN grade 1 being ALH and LCIS classic type, LIN grade 2 being LCIS with distension and with or without comedo necrosis with nuclear grade 2 and LIN grade 3 being pleomorphic LCIS with nuclear grade 3.  fitting our inclusion criteria for the positive group. Of the 38 cases: 5 (13%) were lost to follow-up, 12 (32%) had no further procedures performed and 21 (55%) had subsequent pathology specimens which consisted of 10 mastectomies, 10 re-lumpectomies, and 1 re-lumpectomy followed by mastectomy. Of 21 patients with re-excision, 12 (57%) had residual invasive carcinoma or DCIS, three (14%) had pleomorphic LCIS, 4 (19%) showed residual classic type LCIS, one (5%) had contralateral DCIS, and one (5%) had no residual tumor. Out of 21 patients who had re-excisions, 71% had significant residual disease , and 29% had no residual disease on re-excision. The clinical reasons that prompted re-excision in 21 patients with LCIS at the margin from the initial breast conservation surgery were not clearly documented in the medical record. Per surgeons, most of these patients decided to undergo additional surgeries mainly due to two factors; LCIS being a risk factor to developing into cancer in the future and any lesion being "positive" at the margin in the pathology report are enough to cause anxiety. Also, some of the patients who had invasive lobular carcinoma were not detected in a routine mammogram but additional imaging modality such as ultrasound and MRI were done to detect the presence of tumor. And hence, the annual clinical follow-up studies after BCT would be a financial burden to some patients. Thirteen (34%) cases had negative residual diseases or no recurrence in their clinical follow up. The median follow up from 12 patients who had no re-excision was 36 months [mean follow up of 40.1 months], ranging from 1 to 109 months with mammogram follow-up. Hormonal receptor studies were performed on invasive carcinoma or DCIS cases only. We did not perform hormonal receptors on classic LIN or pleomorphic LIN cases. However, most of the pleomorphic LIN with grade 3 cases had E-cadherin stain. See Additional file A negative control group consisted of matched 38 cases with BCT of invasive carcinoma and/or in-situ carcinoma that also had LIN in the specimen, but with clear margins. No patients had re-excision from this group. Both groups were matched to tumor type, stage and grade, lymph node status and patient age with clinical follow up in the patient's medical records. See Additional File From the negative control group, we found two (5.2%) patients with bone or brain metastasis and one (2.6%) with local recurrence. Follow up months ranged from 4 to 93 months, with a median of 47.5 months [mean of 45.6 months].There is controversy in the management of the lobular intraepithelial neoplasia (LIN), namely atypical lobular hyperplasia (ALH)/lobular carcinoma in situ (LCIS) diagnosed by core needle biopsy without other proliferative lesions such as atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), or invasive carcinomas. Some recommend excisional biopsy and others support no excision. There is consensus amongst pathologists, however, regarding the margin assessment of LIN on excisional biopsy; it is not mandatory to report LIN at the margin as in DCIS or invasive carcinoma and most pathologists do not report LIN at the margin. Obtaining a margin clear of LIN is not a surgical goal. Generally, the presence of LIN at the lumpectomy margin is regarded as irrelevant by most clinicians. The lack of consensus on this topic is illustrated by the results of a recent online survey by the American Society of Breast Disease. The survey posed the question of appropriate management of a patient with LCIS at the margin of a lumpectomy for invasive cancer. 40% of those who replied stated that they would consider re-excision in this circumstance and 8% stated that they would always perform a re-excision. .Also, unlike DCIS, patients with LIN alone on excision are not treated with radiation after breast conservation therapy unless there is a concomitant DCIS or invasive carcinoma. With emerging new evidence that LIN is not just a risk factor but a precursor lesion to invasive carcinoma, margin status may play an important role in the treatment of patients with LIN. If LIN is indeed a precursor lesion, then its presence at the surgical margin in a lumpectomy specimen should increase local recurrence in patients treated with breast-conserving therapy. In an attempt to test this hypothesis, we compared local residual/recurrence rates in patients with and without LIN at the margin who underwent breast conservation surgery for the treatment of invasive carcinoma or DCIS. Ideally, the positive and negative control groups should have a similar disease process except for margin status. The positive group included some cases that had no cancer/DCIS, i.e. only LCIS, with LCIS/ALH at the margin but the negative group did not have any cases that had only LCIS/ALH in the specimen. This was done so that our study would underestimate rather than possibly overestimate the risk of having LIN at the margin, especially given the fact that it is clinically a short-term follow-up.As it is often difficult to differentiate between a local recurrence and a new primary in the treated breast, all tumor found in the ipsilateral breast during follow-up were classified as local recurrences in our study. Technically it shouldn't be considered as recurrences, but considered as residual tumor because the cancer was probably there at the time of initial resection, and not progressed from the margin LIN.Our study showed 39% had significant recurrent diseases when LIN was seen at the surgical margin of initial breast conservation therapy, compared to 7.9% from negative control group. This 7.9% includes patients with metastasis in the negative group, but the 39% from positive group counts only local recurrence.There are limited numbers of LIN recurrence data after only breast conservation therapy. The reported frequencies of recurrence of invasive carcinoma after LCIS diagnosis is approximately 10% and 20% of patients at 10 years and 20 years, respectively. The survival rate at 15 years was 100% in a cohort of 32 patients -8.The NSABP B-17 study analyzed a subset of 182 patients with LCIS in addition to DCIS and treated with breast conservation therapy alone was compared to DCIS alone in the incidence of recurrence. The ipsilateral recurrence of LCIS and DCIS was significantly lower than DCIS alone; 2.2% in LCIS and DCIS and 12% in the DCIS alone respectively. Also, the contralateral breast recurrence incidence was 1.1% compared to 9% respectively. Their conclusion was that the presence of LCIS should not lead to more surgery such as mastectomy [A similar conclusion was drawn from Carolin K et al.  study whJobsen et al.  looked aRobin M. Ciocca et al.  studied Jolly et al.,  on the cStolier A et al.  reportedLiterature supports that with the incidences of ipsilateral and contralateral recurrence rates, mortality rates are low with LIN, and even with invasive lobular carcinoma. This may be due to the fact that the development of invasive carcinoma after LIN takes a long time. Most of the studies have a short median follow-up and cannot exclude the possibility that, with a longer follow-up duration, an impact of LIN on local recurrence will be significantly increased. In fact, the study of Rosen et al. reported the average interval to the development of cancer was 20.4 years after biopsy . AnotherLong term follow-up of LIN treated with BCT alone has demonstrated a 1% per year cumulative long-term risk of breast carcinoma persisting even 10-20 years after diagnosis. Like most retrospective studies, the inability to prospectively evaluate the conclusions and hypotheses is a limiting factor, as well as a short term follow up in LIN. Clinical follow-up of more than 5 years is needed to verify the significance of LIN in the ipsilateral recurrence. Prospective randomized trials related to therapy of patients with LIN at the margin are needed to clearly understand the risk of local recurrence. However, a low mortality rate supports the view that mastectomy is not indicated to clear LIN at the margin if LIN is classic type and grade 1. If there is an overlapping feature of LCIS with DCIS, then re-excision is not unreasonable.There is no doubt that LIN is a risk factor for subsequent carcinoma, and morphologic, immunohistochemical and epidemiologic observations support the statement that LIN is also a direct precursor to invasive carcinoma. Although our data is limited due to the fact that it is a retrospective study and small in sample size, such data would only add to the limited number of LIN recurrence rate after breast conservation therapy. The limitation of our study is that there may be follow-up bias. In our negative control group, there are not any additional surgeries so we cannot be sure that there are no cancerous lesions in the control group.In order to better understand the local recurrence rate to ipsilateral, contralateral, and systemic metastatic rate, it would be important to include the description of margin status by LIN. Our data suggests that the adequacy of the excision with LIN at the margin should be considered, and re-excision is recommended to decrease recurrence rate .The authors declare that they have no competing interests.SKA has made contributions to conception, design, interpretation of data, drafting the manuscript, and approval of the final version of the paper. MM carried out the acquisition of data and contributed important intellectual content. EPO carried out participation in the design of the study and performed analysis of data. NAM carried out drafting and revising the paper critically. All authors read and approved the final manuscript.Diagnostic pathology. LCIS Table S1.Click here for fileTable S2: Diag pathol.Click here for file


Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes.It was found that a SNP set derived from the MLST database on the basis of maximisation of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates.A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required. Streptococcus agalactiae  is a significant human pathogen, particularly of newborn infants. The population structure of this species has been examined using restriction digestions of the genome ) is the probability that an isolate belonging to the CC of interest will be genotyped as such.Specificity (TN/[TN +FP]) is the probability that an isolate that does not belong to the CC of interest will be genotyped as such.PPV (TP/[TP + FP]) represents the proportion of isolates that type as a CC member that are correctly identified.eBURST ,23 is a Isolates were subcultured onto brain heart infusion agar  and incubated at 37°C for 24 hrs. Genomic DNA was obtained by a new mutanolysin-based extraction method. Two loopfuls of cells were resuspended in 500 μL of water containing 50 U of mutanolysin (Sigma Aldrich) incubated at 56°C for one hour, boiled for ten minutes at 100°C, and placed on ice to cool. Tubes were centrifuged at full speed in a microfuge for three minutes, and the supernatant collected and stored at 4°C.Real-time PCR was carried out on the ABI7300 device (Applied Biosystems). Each reaction contained 5 pmol of each primer, 1 μL of genomic DNA, 10 μL of Applied Biosystems SYBR Green MasterMix, and molecular grade water to a final volume of 20 μL. For the glnA429 reactions, double the amount of primer was used (10 pmol each primer) to obtain reliable amplification.The PCR protocol was as follows: 50°C for two minutes, followed by a stage at 95°C for 10 minutes; 95°C for 15 seconds, and 60°C for one minute for 40 cycles.The dissociation stage was 60°C–95°C.The primer sequences for the kinetic PCR reactions are shown in Table This experimental work has been approved by the Sydney West Area Health Service Human Research Ethics Committee .D-maximisation SNP selection method that, in the case of S. aureus, yielded a SNP set with good resolving power and good correlation between SNP profile and clonal complex structure. However, for GBS the rate of increase of D per SNP added to the set was lower than any other bacterial species tested so far  . Eleven SNPs were required to reach D = 0.95, while the previous worst performer in the accumulation of D per SNP was S. aureus, which required seven SNPs to reach D = 0.95 [The aim of this study was to identify a small SNP set that can resolve the major GBS clonal complexes as defined by eBURST analysis of the GBS MLST database. Firstly we assessed the utility of the D maximised SNP set was investigated. GBS displays very little diversity among MLST allele sequences; Jones et al (2003) reported that sequence variation ranges from 1.2% to 2.5% at different MLST loci. Moreover, examination of the MLST database reveals that approximately 45% of eBURST-defined single locus variants are generated through the acquisition of a pre-existing allele, rather than by the generation of a new allele through presumed mutation (data not shown). This indicates that the species' horizontal gene transfer rate is at least comparable to point mutation. Minimum SNPs-based derivation of D-maximised SNP sets from non-clonal microbial species usually provides an almost exponential increase in D as SNPs are added to the SNP set [D-maximised set. Thus our current understanding of D-maximised SNP sets derived from GBS MLST data is that significant horizontal gene transfer disrupts that relationship between SNP profile and population structure, and a paucity of SNPs to choose from means that the resolving power of D-maximised SNP sets is poor with respect to comparably sized SNP sets derived from the MLST databases of other non-clonal bacterial species.The reason for the poor performance of the  SNP set . This isD maximisation is not the optimum approach for identifying a useful SNP set for GBS, and that a new approach was needed. It was also concluded that while sets of 7–8 SNPs provide a very good compromise between number of SNPs and resolving power for other bacterial species [D-maximisation experiments suggest that the optimum size of a generally applicable GBS-genotyping SNP set will be smaller than 7–8, irrespective of the SNP identification method used.Accordingly it was concluded that  species , the lacglnA36, glnA429, glcK180, and adhP111. The positions of these in the concatenated MLST database are 1536, 1929, 2697 and 111 respectively.The alternative strategy that was developed involved the use of the Minimum SNPs Not-N algorithm  to find A complete description of the relationship between the SNP profiles and the GBS MLST-defined population structure was determined, using the MLST database as downloaded on April 4, 2007. This was accomplished using the "working backwards" mode of Minimum SNPs. An overview of the results is shown in Table The correspondence between the generally applicable SNP profiles, and the GBS population structure as revealed by eBURST analysis is good, but imperfect. A significant contributor to this is the inability of eBURST analysis to generate a reliable population structure from a high frequency recombination species. This is a limitation determined by differences in evolutionary history between different parts of the genome, rather than of the eBURST algorithm itself. This phenomenon is particularly evident with the large highly interlinked eBURST group that contains CC1, CC19 and CC10, and a number of smaller/derived CCs. eBURST analysis cannot reliably define precise evolutionary pathways with this population structure because there are so many essentially equivalent topologies. A consequence of this is that any given topology will inevitably result in very closely related STs sometimes being separated by many steps in the eBURST diagram. Therefore, assigning isolates to particular clones, with a high level of confidence, is not possible within such a highly interlinked population.Nevertheless, if CC membership is clinically relevant, false negatives may be a serious problem. Accordingly we developed a strategy to minimise false negatives for defined groups of STs. During the course of this study we observed that if the "defined variant" algorithm in Minimum SNPs is used to identify SNPs diagnostic for a specific CC founder, the first one or two SNPs in the series will differentiate the CC from the rest of the population, and the later SNPs in the series will distinguish the CC founder from its double and single locus variants. This approach alone produces similar false positive and negative rates to those produced with the four generally applicable SNPs described above and so is therefore less efficient, because different SNP sets are required for each CC. However, given that a generally applicable SNP set has been already been developed using other means, we postulated that for any given CC, the false negatives would be different for a "CC founder specific SNP", and the four generally applicable SNPs. Therefore, a strategy in which a single CC-specific SNP was interrogated in isolates that are negative for that CC on the basis of the generally applicable SNPs would ensure that no single locus variants were missed. We have termed such a SNP a "safety net SNP". It was also postulated that the safety net SNP would be effective in reducing false positives from the generally applicable SNP set. As with the "false negative" problem, we hypothesised that the false positives from the safety net SNP, and the generally applicable SNPs would not overlap.This strategy was tested using CC17 as a model system, because this CC is generally regarded as causing a high proportion of paediatric infections, and is potentially a valuable diagnostic target.If CC17 is defined as consisting of ST-17 plus its single locus variants, the generally applicable SNPs provide very good sensitivity and specificity Table . The ST-atr351 (position 1350 in the concatenated database), with ST-17 possessing the "A" allele. This allele eliminates the four false negatives, so we term atr351 the "safety-net" SNP. Eighty-five (27.1%) of known GBS STs possess the A allele, so at first analysis, this SNP appears to generate a large number of false positives for CC17. However, the great majority of these STs are members of CC17, or the closely related CCs, CC67 and CC22. Remarkably, only five STs that are "A" at the safety net SNP are not members of the eBURST group that contains CC17, CC67 and CC22.Minimum SNPs "Defined variant" analysis for ST-17 revealed that the single most discriminatory SNP (i.e SNP1 in the program's output) is An unanticipated benefit of interrogating the safety net SNP is that it is very effective at resolving CC22 and CC23, which are not resolved by the generally applicable SNPs. The only CC22 members which do not type as CC17 on the basis of the safety net SNP are ST-168 and ST-169  In summary, the safety net SNP may be qualitatively regarded as being very effective at discriminating CC17, together with the closely related CC67 and CC22, from other CCs within the species.Quantifying the performance of the safety net SNP is not straightforward, because it is designed to provide an alternative or back-up to the generally applicable SNP set, as opposed to simply adding another allele to the SNP profile of the diagnostic target. The most informative approach is to calculate its performance separately against groups of STs that return particular profiles when interrogated at the generally applicable SNPs. This is because the different generally applicable SNPs-defined groups of STs differ greatly with respect to the proportion that possess the CC17 "A" allele at the safety net SNP. A corollary of this is that the profile obtained from the generally applicable SNPs may potentially indicate whether it is worthwhile interrogating the safety-net SNP at all.As stated above, the three CC17 false negatives as defined by the generally applicable SNPs return two different profiles – those associated with CC67, and CC23. The specificity of the safety-net SNP differs greatly as a function of which generally applicable SNP profile has been obtained , ST-86 (CC-19), ST-226 (not part of a major CC), ST-271 (CC67) and ST305 (ST23). None of these possess an A allele at the safety net SNP apart from ST-271 which, is arguably part of CC-17 anyway. Therefore, the safety net SNP is very effective eliminating CC17 false positives.The power of the safety net SNP on its own to serve as a CC17 diagnostic is also of interest. As stated above, the general property of this SNP is that it discriminates the closely related CCs CC17, CC22 and CC67 from the rest of the species. eBURST analysis puts these CCs into a single group. The specificity, sensitivity and PPV provided by this SNP in diagnosing either ST17 plus single locus variants (narrow definition of CC17), or the CC17–CC22–CC67 eBURST group (wide definition of CC17) were calculated. As expected, this SNP provides high sensitivity against both targets, and high specificity and PPV against the CC-17–CC22–CC67 eBURST group  which is a current employer of FH and a previous employer of PMG. QUT, and authors PMG and FH would potentially benefit from any commercial arrangement regarding this patent application.EH optimised and validated the SNP interrogation procedures and carried out the majority of the SNP-based genotyping and associated data analysis. TF identified the generally applicable SNP set and developed the prototype SNP interrogation assays. AJS developed the safety net SNP interrogation assay and carried out a significant proportion of the genotyping and associated data analysis. DK, FK and GLG participated in the study design, selected and assembled the isolates and participated in data analysis. FH participated in the study design and the optimisation of the SNP interrogation assays. PMG conceived of and coordinated the study, carried out the bioinformatics analyses apart from the initial SNP selection, and wrote the majority of the manuscript. All authors approved the final manuscript.Complete isolate information.Click here for fileGBS st all match profiles.Click here for fileGBS SNPs Vs CCsrev.Click here for fileatr351.STs that possess the "A" allele at the CC17 safety net SNP, Click here for file


Our objectives were (a) to see if we would find QTLs not originally discovered in a previous investigation that assessed these traits over the entire 21-day period and (b) to see if some of these QTLs discovered might affect the activity traits only in the early or in the late time intervals.In recent years it has become increasingly apparent that physical inactivity can predispose individuals to a host of health problems. While many studies have analyzed the effect of various environmental factors on activity, we know much less about the genetic control of physical activity. Some studies in mice have discovered quantitative trait loci (QTL) influencing various physical activity traits, but mostly have analyzed inter-individual variation rather than variation in activity within individuals over time. We conducted a genome scan to identify QTLs controlling the distance, duration, and time run by mice over seven consecutive three-day intervals in an FThis analysis uncovered 39 different QTLs, over half of which were new. Some QTLs affected the activity traits only in the early time intervals and typically exhibited significant dominance effects whereas others affected activity only in the later age intervals and exhibited less dominance. We also analyzed the regression slopes of the activity traits over the intervals, and found several QTLs affecting these traits that generally mapped to unique genomic locations.It was concluded that the genetic architecture of physical activity in mice is much more complicated than has previously been recognized, and may change considerably depending on the age at which various activity measures are assessed. Physical activity is an important behavior exhibited by most humans on a daily basis. Activity levels vary considerably among populations, sexes, and/or age cohorts ,2, althoAlthough there is a wealth of knowledge about the environmental factors that predispose individuals to physical inactivity, it is somewhat surprising that we still know comparatively little about the genetic control of voluntary exercise. It is clear that the heritability of various activity traits in humans is moderate to high in magnitude ,10, althet al. [Nearly all of these studies have analyzed inter-individual variability, but it has been apparent for some time that physical activity levels vary within individuals over time as well ,21. A reet al.  who searet al. . This reet al. , becauseWe previously conducted an interval mapping analysis of the average distance, duration, and speed run by mice during a three week (21 day) period, and were successful in discovering 4 significant QTLs (on chromosomes 9 and 13) and 14 suggestive QTLs that affected these traits, with many colocalizing to similar positions in the genome . Since tWe had two basic aims in our investigation: (1) We wanted to discover how many QTLs influence these traits over the different time intervals and identify which ones would correspond to those QTLs previously found for activity over the entire 21-day period. We expected to find novel QTLs for activity that we did not uncover in our original study. (2) We were particularly interested to see if we might find some QTLs affecting the traits only in the early, or only in the late, intervals, and if so, what pattern of effects they might exhibit.2 population of mice produced from an original cross of two inbred strains, C57L/J and C3H/HeJ, because these strains exhibited a great deal of divergence in wheel-running activity levels [et al. [2 mice were measured for three activity traits: total daily distance in kilometers and total daily exercise time in minutes (each was recorded every 24 hours), and average daily running speed in meters/minute obtained by dividing distance by duration. For all mice, this was accomplished with a solid surface running wheel mounted in their cages that interfaced with a computer that counted the total wheel revolutions and recorded the time each mouse spent exercising [et al. [We used an Fy levels . Thus Li [et al.  previousercising . In all  [et al. ,23 for d2 mice were measured daily during a 21 day period for each of these three physical activity traits.All mice were exposed to the running wheels when they were from 35 to 62 days of age and measured for distance, duration, and speed each day for several weeks. For the purposes of this study, however, we age-matched the available activity data to a 63-day-old start age to the extent possible. This resulted in a final sample of 297 mice that were 63 days of age and 13 mice that were 60 days of age at the start of testing. Prior to this start age, all 310 mice had previously been exposed to running wheels for an average of 13 days (range 1 to 28 days). Once testing started, the FP > 0.05) and less variation than single-day values. This averaging therefore resulted in values that were relatively more precise, thereby increasing the statistical power to detect QTLs influencing the activity traits. We also considered that seven timepoints were sufficient to ensure an adequate assessment of these traits over the 21-day period, and the phenotypic values of these traits in each of the seven intervals were used to provide snapshots in time as the mice aged throughout the 9- to 12-week period. Thus our basic intent was to assess the genetic changes that occurred during this 21-day time period. Distance, duration, and speed values over each of the 7 intervals are designated DT1-DT7, DR1-DR7, and SP1-SP7 throughout the analysis.To analyze within-individual variation, we calculated the mean of the activity trait values for each successive three day interval. We found that single-day values were subject to considerable variation , and theAll mice were genotyped with the use of 129 single-nucleotide polymorphisms (SNPs) that differed between the C57L/J and C3H/HeJ progenitor strains. These SNPs provided coverage of all 20 chromosomes in the genome  with an average intermarker interval of about 14 cM. A few SNPs were not resolved, so for the QTL analyses described below, sample sizes occasionally were reduced slightly from 310.P < 0.01). All activity trait values therefore were adjusted for these effects by calculating residuals from the model and adding them to the appropriate means in the overall population.Prior to the QTL analysis, we first tested the seven distance, duration, and speed traits for potential effects due to sex, litter size, rearing block, and age . This waet al. [We also tested for any potential effects of the number of days of exposure to the running wheel prior to the start of testing. This factor was not statistically significant for any of the activity traits throughout the age intervals, so did not require any further adjustments to the activity data. Because all mice had previously exercised and showed no effect due to the number of prior days of exposure, it should be borne in mind that any QTLs found for the activity traits in the first several intervals would not be expected to be those strictly for anxiety or other fear-related behavioral differences as was postulated for the mice in the study by Kelly et al. . On the et al.  have shoet al. [We used the regression approach of interval mapping  to searcet al. . The anaet al.  and if tet al. , with tha) and dominance (d) genotypic values and the contribution  for the QTLs.We also tested each chromosome for two-QTL and sex-specific QTL effects on the activity traits following procedures previously described . Once thWe expected some of the QTLs to be commonly affecting the various activity traits throughout the time intervals. We therefore first inspected the positions of all QTLs found for the values of each of the activity traits throughout the time intervals to see if they colocalized. Where this occurred, we conducted pleiotropy tests using the procedure outlined by Knott and Haley . This prAs an alternate to the analysis of each of the activity traits over the seven intervals, for each mouse we used linear regression to calculate the slope of each of the three traits over all intervals. These slopes for distance, duration, and speed were composite traits that represented the changes in activity throughout the intervals, and we conducted QTL analyses on these traits in the same manner as already described. Any QTLs found for these slopes were assumed to indicate genomic regions influencing the trajectory of wheel-running activities across the entire 21-day period.th and 5th interval, and then increase considerably in the last two intervals. Thus unlike distance or duration, the highest mean value for speed is reached in the last (7th) time interval. One-way analyses of variance showed that there were statistically significant (P < 0.01) overall differences among the 7 intervals for each of the three activity traits, and Tukey's post-hoc tests suggested that the individual pairwise differences were mostly between traits in intervals 1 and 2 versus those in later intervals. Standard deviations for each trait are comparable across the intervals.Basic statistics (means and standard deviations) for distance, duration, and speed throughout the seven time intervals are given in Additional file For each of the three traits, Additional file DIST, DUR, and SPD followed by their appropriate chromosome number and an extension to indicate whether they were the first or second QTL on each chromosome. Chromosomewise threshold LPR values generated from the permutation procedure varied from 1.82 to 2.47, averaging 2.08. Genomewise threshold LPR values varied in a narrow range from 3.33 to 3.58.The results of the genome scan for QTLs affecting the activity traits in each of the seven intervals are given in Additional files DIST9.1, affected all 7 distance traits, the LPR scores for 5 of which reached significance at the genomewise level. Three other QTLs, DIST5.1, DIST8.1 and DIST13.1, affected several different traits; so overall, 4 of the 13 QTLs exhibited pleiotropy.For distance  of the dominance genotypic values reach significance, but the average of their absolute values is 0.24 and many exhibit overdominance (d greater than a) or underdominance (d less than a), so dominance appears to be important for these QTLs. The trends of the additive and dominance genotypic values across the intervals for the four pleiotropic QTLs are generally consistent. DIST5.1 and DIST13.1, for example, exhibit primarily additive effects on the distance traits since all a values are positive and significant whereas none of the d values reach significance. DIST9.1 exhibits an interesting alternate pattern in which all additive effects are significant, but dominance genotypic values are significant only for early distance , declining to non-significance for late distance . The contribution of each QTL to the total phenotypic variability in the distance traits ranged from 3.2% to 11.1%, averaging 5.1%.The distance QTLs primarily exhibit significant additive genotypic effects, their absolute values averaging 0.26 standard deviations. Most (23 of 30) of the DUR4.1F, DUR9.1, and DUR14.1F affect only early duration whereas DUR5.1, DUR6.1, and DUR13.1 affect late duration. The duration QTLs exhibit nearly the same frequency of significant additive (14/23) and dominance genotypic effects (12/23). Dominance effects appear to be more important since the mean of the absolute d values (0.32) well exceeds that for the a values (0.22). This disparity partly has been generated because of the particularly high d values exhibited by all three female-specific QTLs. Negative d values outnumber positive d values, and a number of QTLs exhibit significant underdominance. One noteworthy trend is that all three pleiotropic QTLs previously identified as affecting early duration traits show nonsignificant additive but significant dominance effects whereas the reverse is true for the late duration traits . The contribution of each QTL to the total phenotypic variability in the duration traits averaged 5.5%.For duration  allele tended to increase speed more so than the C3H/HeJ allele (slow strain). All but four of these a values also reached statistical significance whereas about half (15) of the d values were significant. However, means of the absolute a (0.28) and d values (0.27) were nearly identical, suggesting an important role for dominance. As was true for DIST9.1, SPD9.1 also exhibits significant dominance effects for early (SP1-SP3) but not late (SP4-SP7) speed. However, this trend does not always hold for the other pleiotropic QTLs; for example, SPD8.1 shows dominance for both early and late speed, and SPD5.1 effects on early speed are additive only. The contribution of each QTL to the total phenotypic variability in the speed traits averaged 5.5%.For speed  only for duration. The average of the absolute dominance genotypic values tends to decrease throughout the age groups for distance  and duration , although not for speed . For distance and duration especially, therefore, dominance is more important in the early ages and tends to decrease in the later age intervals.Additional file DIST9.1, DIST9.2, DUR9.1, DUR9.2) previously found for the interval traits , however, suggests it probably is the same as a female-specific QTL for duration previously found (DUR4.1F). All 7 QTLs exhibit a great deal of dominance. In fact, all of the dominance genotypic values exceed the additive genotypic values, and 5 of the 7 individual d values reach significance.In the genetic analysis of regression slopes, we discovered only 3 QTLs for distance, 3 for duration, and 1 for speed  in one or more intervals. We assume that most of these are true QTLs because as previously explained, only about one false positive result is expected using the chromosomewise levels of significance.The basic objective of this study was to better understand the genetics of voluntary physical activity within individuals. For this purpose, we averaged the distance, duration, and speed run each day by the FThe number of activity QTLs we discovered is more than double the number of total QTLs (18) originally found affecting the three activity traits obtained by averaging daily values over the entire three-week period in mice from this same population . These ret al. [et al. [Among the 39 time-specific QTLs we discovered, 15 appear to be the same as those previously shown by Lightfoot et al.  to signi [et al. , includi2 population we generated from crossing the C57L/J and C3H/HeJ strains, and as QTL studies are performed with other progenitor strains, we should expect additional QTLs to be found, including on the four chromosomes where we found none.We also discovered a number of other QTLs that affected the activity traits in just one age interval. Most of these QTLs generally were not detected in the previous study  that useDUR15.1 exhibiting pleiotropic effects on duration in both early (DR3) and late intervals (DR7). It is possible that this result may simply be a consequence of limited statistical power to detect QTLs influencing duration throughout both the early and late intervals. To the extent that this is true, it would suggest caution in postulating the existence of separate sets of QTLs that affect duration only at certain ages. However, inspection of the highest LPR scores among all seven intervals for the six chromosomes on which the QTLs affecting only early or late duration are located reveals a rather clear and consistent trend. As one example, DUR5.1 significantly affected duration during the late (4-7) intervals only  and speed (SPD9.1) throughout all 7 time intervals, but the comparable QTL for duration at this location (DUR9.1) was significant only for two early age intervals  to middle (weeks 4-6) periods while another set affected middle to late growth (weeks 7-10), with very few QTLs affecting the entire postnatal growth period [et al. [et al. [Although it is not yet clear whether we should generally expect to find separate QTLs affecting physical activity at early or at late ages, such a trend has been seen for other complex traits. For example, Cheverud et al.  measuredh period . Rocha e [et al.  and Alla [et al.  discoverThis pattern of effects of the pleiotropic QTLs is consistent with the major trend seen in the correlations among the activity traits in which they tended to decrease in magnitude between increasingly distant time intervals  or even higher than the additive genotypic values (duration). This was as expected because in our previous analysis of 21-day activity traits, we found considerable dominance for the QTLs we discovered . In addie traits , and hete traits . Nehrenb [et al.  also obsy et al.  who noted/a ratio declined with age. This was particularly noticeable for duration, where the mean d/a ratio for the first three age intervals of 6.65 was much higher than that of 0.88 for the last three age intervals. Cheverud et al. [d/a trend exhibited by QTLs for body weight over a 10-week interval in their mouse population, and suggested that this strong dominance and/or overdominance for early growth may have arisen as a response to selection for an increased early growth rate.The most interesting aspect about the dominance we observed was its prevalence especially in the QTLs for early compared with later activity. This pattern was most apparent for distance and duration rather than speed, and was sufficient to reach statistical significance in the regression analyses of the absolute dominance genotypic values for these two traits over the seven age intervals. Especially with the additive genotypic values generally increasing throughout the ages, this also means that the d et al.  found a 2 generation such as ours where the support intervals for the QTLs tend to be rather large. In addition, at present there are few studies that have searched for QTLs affecting activity traits in mice, so we have little data to use for comparison. And even where other studies may be available, they typically involve other inbred strain progenitors which are expected to yield QTLs uniquely polymorphic between those strains. A case in point is the mouse study by Kelly et al. [et al. [At present we have little information about the genes underlying these QTLs for the activity traits. Partly this is because of the imprecision of the mapping process in an Fy et al.  who disc [et al. .et al. [2 mice that is different from that for activity in individual, early, or late time intervals. Should the genes underlying these QTLs eventually be identified, it is possible that they play an important role in the maintenance of physical activity over long periods of time.It might be particularly useful to know the identity of the genes underlying the QTLs we discovered for the slopes of the activity traits. These QTLs were most interesting because, as was also found by Kelly et al. , their l2 population over each of seven three-day intervals. Although some of these QTLs are apparently the same as found in our original study using the average of these physical activity traits measured daily over the entire 21-day period [We have located a number of QTLs that influence the direction, duration, and speed run by mice in our Fy period , a numbeLJL performed the data analysis, wrote and prepared the manuscript for submission. JTL was the principal supervisor of the study and assisted with preparation of the manuscript. DP designed the genome scan including SNP selection, and reviewed the manuscript. All authors read and approved the final manuscript.Basic statistics for the activity traits. Shown are the means and standard deviations (Std) of distance (km/day), duration (min/day) and speed (meters/min) during each of the seven time intervals (1-7). The sample size = 310 in all cases.Click here for fileCorrelations and principal components analyses for the activity traits. Correlations are given for distance, duration, and speed traits for each of the 7 time intervals as well as loadings on the first two principal components, I and II, derived from a component analysis of the correlation matrix for each of the three traits.Click here for fileQTLs for distance. Shown are the locations, confidence intervals (CI), LPR scores (log10Prob-1), percentage of the total phenotypic variation explained (%), and standardized additive (a) and dominance genotypic values (d) for QTLs on all chromosomes affecting distance in any of the 7 time intervals (DT1 through DT7). Each QTL for distance is designated DIST followed by its chromosome number and an extension to indicate whether it is the first or second QTL on that chromosome. Subscripts are given for QTLs if they affect only males (M) or only females (F). Locations are given as map distances from the nearest proximal marker (Marker Dist) and from the centromere (Cent. Dist) and confidence intervals are expressed as distances from the centromere. Single locations and confidence intervals are indicated for multiple traits when tests suggested pleiotropy of common QTLs. All LPR values are significant at the 5% chromosomewise level or at the genomewise level (†). * = P < 0.05; ** = P < 0.01.Click here for fileQTLs for duration. Shown are the locations, confidence intervals (CI), LPR scores (log10Prob-1), percentage of the total phenotypic variation explained (%), and standardized additive (a) and dominance genotypic values (d) for QTLs on all chromosomes affecting duration in any of the 7 time intervals (DR1 through DR7). Each QTL is designated DUR followed by its chromosome number and an extension to indicate whether it is the first or second QTL on that chromosome. Subscripts are given for QTLs if they affect only males (M) or only females (F). Locations are given as map distances from the nearest proximal marker (Marker Dist) and from the centromere (Cent. Dist) and confidence intervals are expressed as distances from the centromere. Single locations and confidence intervals are indicated for multiple traits when tests suggested pleiotropy of common QTLs. All LPR values are significant at the 5% chromosomewise level or at the genomewise level (†). * = P < 0.05; ** = P < 0.01.Click here for fileQTLs for speed. Shown are the locations, confidence intervals (CI), LPR scores (log10Prob-1), percentage of the total phenotypic variation explained (%), and standardized additive (a) and dominance genotypic values (d) for QTLs on all chromosomes affecting speed in any of the 7 time intervals (SP1 through SP7). Each QTL is designated SPD followed by its chromosome number and an extension to indicate whether it is the first or second QTL on that chromosome. Subscripts are given for QTLs if they affect only males (M) or only females (F). Locations are given as map distances from the nearest proximal marker (Marker Dist) and from the centromere (Cent. Dist) and confidence intervals are expressed as distances from the centromere. Single locations and confidence intervals are indicated for multiple traits when tests suggested pleiotropy of common QTLs. All LPR values are significant at the 5% chromosomewise level or at the genomewise level (†). * = P < 0.05; ** = P < 0.01.Click here for fileQTL summary statistics for the activity traits over the seven time intervals. Shown are the number of QTLs affecting the activity traits over each of the seven time intervals, the percentage of the total phenotypic variation they contribute , and the means of their absolute additive (a) and dominance genotypic values (d).Click here for fileQTLs for the slopes of the activity traits over all seven intervals. Shown are the locations, confidence intervals (CI), LPR scores (log10Prob-1), percentage of the total phenotypic variation explained (%), and standardized additive (a) and dominance genotypic values (d) for QTLs on all chromosomes affecting the regression (slope) of distance, duration, and speed over all intervals. Each QTL for distance is designated DISTB, DURB, or SPDB  followed by its chromosome number and an extension to indicate whether it is the first or second QTL on that chromosome. Subscripts are given for QTLs if they affect only males (M) or only females (F). Locations are given as map distances from the nearest proximal marker (Marker Dist) and from the centromere (Cent. Dist) and confidence intervals are expressed as distances from the centromere. Single locations and confidence intervals are indicated for multiple traits when tests suggested pleiotropy of common QTLs. All LPR values are significant at the 5% chromosomewise level or at the genomewise level (†). * = P < 0.05; ** = P < 0.01.Click here for file


Fragile X syndrome is the most common inherited form of mental impairment characterized by cognitive impairment, attention deficit and autistic behaviours. The mouse model of Fragile X is used to study the underlying neurobiology associated with behavioral deficiencies. The effect of Fragile X glial cells on the development of neurons has not been studied. We used a co-culture technique in combination with morphometrics on immunostained neurons to investigate the role of astrocytes in the development delays associated with hippocampal neuron development.We found that hippocampal neurons grown on Fragile X astrocytes exhibited a significant difference from the neurons grown with normal astrocytes after 7 days in vitro for many parameters including increases in dendritic branching and in area of the cell body. However, after 21 days in culture, the neurons grown on Fragile X astrocytes exhibited morphological characteristics that did not differ significantly from the neurons grown on normal astrocytes. With antibodies to the pre-synaptic protein, synapsin, and to the excitatory post-synaptic protein, PSD-95, we quantified the number of developing excitatory synapses on the dendrites. In addition to the delays in dendritic patterning, the development of excitatory synapses was also delayed in the hippocampal neurons.These experiments are the first to establish a role for astrocytes in the delayed growth characteristics and abnormal morphological features in dendrites and synapses that characterize the Fragile X syndrome. As the central nervous system (CNS) develops numerous events must occur in a highly regulated manner to create the intricate organization of neural networks that control the mature brain. One of the key players recognized in the guidance of neuron development is the astrocyte -5. As suFMR1) gene causing gene silencing and a lack of the protein product, Fragile X Mental Retardation Protein (FMRP) [FXS is the most common inherited form of mental retardation, affecting approximately 1/2500 children . Children (FMRP) .Fmr1 knockout (-/-) mouse model of FXS is well accepted as an appropriate model in which to study the neurobiology of FXS [Fmr1-/- mouse has been shown to demonstrate behavioural qualities similar to those seen in individuals with FXS, including: susceptibility to seizures, hyperactivity and learning impairments [Fmr1-/- show similarly abnormal dendritic spine morphology and altered synaptic function [The y of FXS . The Fmrairments -17. Addifunction ,19, as dfunction .Fmr1-/- mouse [Fmr1-/- mouse model to investigate the role of astrocytes in the development of the abnormal neuronal characteristics seen in FXS [Contrary to the current belief that FMRP is only expressed in neurons, recent work in our lab revealed that FMRP is also expressed in cells of the glial lineage in the /- mouse . Based on in FXS . In shortm1Cgr Fmr1[The FMRP knock-out FVB.129P2(B6)-r1tm1Cgr  and wildFmr1-/- mice, in culture for 7, 14 or 21 days. These cultures were grown in culture for 7, 14 or 21 days. A total of three independent cultures per condition (genotype+days in vitro (DIV)) were completed.Primary hippocampal neurons with astrocytes were grown in co-culture conditions as detailed previously by our lab . BrieflyFollowing removal of the media, the cells were fixed with 4% PFA in PBS or ice cold (-20°C) acetone for 15 or 20 minutes, respectively. After three washes with PBS, and the application of 0.1% Triton X-100 where necessary, non-specific binding was blocked with 1% bovine serum albumin (BSA) for 30 minutes. Primary antibodies were applied to the coverslips and incubated overnight at 4°C. The second day, following washes with PBS, secondary antibodies were incubated with the cells for 3 hours at room temperature. Following a final set of washes with PBS and distilled water, the coverslips were mounted onto slides with Vectashield fluorescent mounting medium  containing DAPI to stain the nuclei.The following antibodies, diluted in 1% BSA, were used: chicken anti-Map2 , guinea pig anti-synapsin , mouse monoclonal anti-PSD-95 , anti-mouse AlexaFluor 594 , anti-guinea pig FITC  and anti-chicken FITC .Images were acquired using a Zeiss Axioskop 2 epi-fluorescence microscope and Axiovision (v4.6) image acquisition software.http://www.ibridgenetwork.org/arizona/UA07-56-Neuronmetrics[http://rsbweb.nih.gov/ij/. The following parameters were evaluated: number of dendritic branches, length of the longest primary dendrite, and the area covered by the dendritic arbor. For each independent culture, 50 isolated MAP2(+) neurons were selected and analyzed for morphology. Once each neuron image was converted to a black and white TIFF file, the images were processed through Neuronmetrics™ to generate pixilated skeletons and to obtain the morphological measurements listed above. Examples of representative neurons overlaid with digitized skeletons and area demarcations generated by Neuronmetrics™ are shown in Figure Morphological measurements were conducted using Neuronmetrics™ onmetrics, a plug-For each of the above neurons the area of the cell body was also measured, by tracing around the cell body using Image J.Synapses were identified by the co-localization of the pre- (synapsin) and post-synaptic (PSD-95) puncta, using a custom written plug-in for Image . After sStatistics were performed using SPSS version 17, with an alpha level set to 0.05. All data are presented as mean ± SEM. Where the data had significantly different variances , and deviated significantly from a normal distribution  tests were used.DIV, stained with MAP2 (green) to enable the visualization of the dendritic arbors. In the same image the astrocytes are stained with an antibody directed against Glial Fibrillary Acidic Protein , and the nuclei are stained with DAPI (blue). Upon examination of the cultures, no obvious differences could be seen between clusters of neurons grown on Fmr1-/- compared to those grown on WT astrocytes. To perform the morphometric analysis, isolated neurons were selected at random from the coverslip  increased in the neurons grown on Fmr1-/- astrocytes (12.90 ± 0.62) compared to those grown on WT astrocytes (10.93 ± 0.44). This was also true for the cells measured at 21 DIV .At 7 4)Figure . BranchiDIV. At 7 DIV, neurons grown on Fmr1-/- astrocytes exhibited significantly  lower values (148.93 ± 6.47) of their longest dendrites compared to neurons grown on WT astrocytes (167.40 ± 6.47) or 21 DIV .The length of the longest dendrite was also significantly different at 7 7)Figure . The lenDIV, but not 14 or 21 DIV, the cell body area was significantly  increased in neurons grown on Fmr1-/- astrocytes (197.10 ± 5.87) compared to those grown on WT astrocytes (179.85 ± 3.95) or 21 DIV .At 7 5)Figure . The celFmr1-/- astrocytes compared to those grown on WT astrocytes at both 7 DIV  and 14 DIV   in culture .The area of the dendritic arbor was significantly decreased in neurons grown on ) Figure . The areDIV) is altered when grown on Fmr1-/- astrocytes, but these abnormal characteristics disappear with time. By 14 DIV, three out of four of the morphological characteristics we studied were no longer significantly altered in neurons grown on Fmr1-/- astrocytes. The last parameter, the area of the dendritic arbor, had also reached levels comparable to values seen in neurons grown with WT astrocytes by 21 DIV.Therefore, by the morphological parameters evaluated in these experiments, it appears that the growth of the neurons early in development . The number of synapses per 50 μm increased over time in neurons grown on WT astrocytes; whereas in neurons grown on Fmr1-/- astrocytes, there was a slight decrease in the number of synapses over time Figure . This sie Figure .DIV and 14 DIV on neurons grown with Fmr1-/- astrocytes is brought to levels comparable to normal by 21 DIV.Therefore, similar to the morphological characteristics we evaluated, it appears that the abnormal number of synapses found at 7 Fmr1-/- astrocytes for up to 21 days in vitro in order to investigate the possibility of an astrocyte-mediated delay in hippocampal neuron development. We evaluated the changes in neuron dendritic arbor morphology and excitatory synapse expression at 7, 14 and 21 DIV. We found that both the morphological parameters and the synaptic protein expression approached normal levels by 21 DIV, with three of four morphological parameters approaching normal at 14 DIV. Our results suggest that Fmr1-/- astrocytes do not completely prevent normal hippocampal neuron growth, but delay it.In this study we used a co-culture procedure in which normal primary hippocampal neurons were co-cultured with normal or Fmr1 -/- astrocytes on normal primary hippocampal neurons at 7 DIV [Drosophila dfmr1 gene [DIV, is different from the synaptic protein analysis at 7 DIV of that same series of experiments. This difference could be due to the modifications of the experimental design in the present studies. First, in this study we used synapsin as our pre-synaptic protein antigen. While we would not expect that there would be a difference in the number of pre-synaptic puncta identified by the synapsin antibody versus the previously used synaptophysin antibody, this difference should be noted. Second, in the previous report we evaluated the pre- and post synaptic proteins independently whereas in the present experiments we report the co-localization of the pre-and post-synaptic proteins. It is in fact possible that the number of pre- or post- synaptic protein puncta does not correlate in a positive direction with the number of synapses. If that were the case there could be a decrease in the numbers of pre- and post-synaptic puncta independently, but there could be an increase in the number of co-localized puncta. Third, and most importantly, here we report the synaptic protein expression in segments of dendrites taken from neuron networks, whereas in the previous paper we focused on the absolute numbers of pre- and post-synaptic puncta per isolated neuron. It could be expected that synapse number will vary when comparing neural networks with isolated neurons.The morphological results presented herein are consistent with our previously reported results for the effects of at 7 DIV . This fimr1 gene . HoweverFmr1-/- astrocytes reach normal maturity, but are delayed in the process. At 7 DIV the neurons grown on Fmr1-/- astrocytes had significantly different cell measurements from the neurons grown on WT astrocytes for all of the parameters we measured. However, by 21 DIV those neurons had morphological measurements that closely resembled those of neurons grown on normal astrocytes.The results presented here support the idea that hippocampal neurons grown with During development the growth of dendritic arbors is a highly choreographed dynamic balance between phases of extension and retraction. Cues that regulate the initiation and promote dendritic arbor development are equally as important as those that stop its elaboration . There iFmr1-/- astrocytes appear to be in a branching mode of growth, rather than a mode dominated by arbor extension. This suggests that the dendritic arborization is altered in a manner that would interfere with the normal appropriate wiring of the hippocampal circuits. In 2001, Cline suggested that mechanisms that enhance dendritic arbor complexity have the potential to affect the integrative properties and firing characteristics of a neuron [in vitro. Thus, there is the possibility that astrocytes induce an increase in branching in the early development of hippocampal neurons in FXS, resulting in the alteration of the signaling properties of the neurons. In turn, this may affect key developmental stages when initial neural networks are being established. These alterations could contribute to the underlying abnormal neurobiology, and therefore the clinical deficiencies observed in FXS.In the early stages of development the neurons grown on a neuron . Neuronsa neuron . Astrocya neuron ,30. HereFmr1-/- animal may be unable to appropriately regulate the establishment of the receptive field margins. Under normal conditions there are "stop" signals that inhibit the expansion of dendrites beyond the normal receptive field of the arbor [In addition, it is possible that astrocytes from an he arbor . Althoughe arbor ). AstrocFmr1-/- astrocytes impedes the appropriate timing of excitatory synaptic development. At 7 DIV, neurons grown on Fmr1-/- astrocytes had significantly more excitatory synapses than the neurons grown on WT astrocytes. However, by 21 DIV the numbers of excitatory synapses in neurons grown on Fmr1-/- astrocytes were equal to the quantity seen in neurons under normal conditions.The findings of this study suggest that the growth of hippocampal neurons with DIV neurons grown on Fmr1-/- astrocytes have a significantly greater number of synapses than neurons grown on WT astrocytes. Perhaps at 7 DIV, growth with Fmr1-/- astrocytes promotes an increase in the production of synapses or a decrease the degree of pruning. A number of studies have suggested that many developmental disorders are caused by a lack of pruning early in development. Our findings therefore support a lack of appropriate synaptic pruning early in development as a potential contributor to the neurological abnormalities seen in FXS.The formation of mature synapses is a dynamic process with a continuous fluctuation between synapses being formed and unwanted synapses being eliminated . TherefoFmr1-/- astrocytes at 7 DIV, when compared to neurons grown on WT astrocytes. With time, the difference between the net number maintained in the neurons grown on Fmr1-/- astrocytes and those grown on WT astrocytes decreased, until 21 DIV at which point there is no longer a significant difference. The neurons grown on Fmr1-/- astrocytes have reached a stage of maturity at which their net production of excitatory synapses equals that of neurons grown under normal conditions. Still, there is a possibility that the abnormal early stages of development could play a major role in the ability of neurons to later integrate and transmit information effectively. Abnormal synapses may have been formed alongside atypical local neural networks, and these early alterations may negatively affect the neural circuitry of the region in the long run.We found an abnormally high net number of excitatory synapses being maintained in neurons grown on Fmr1-/- astrocytes reflects an increased number of immature synapses. Given that the dendritic spine is the site for the majority of excitatory synapses, this finding would be in agreement with numerous studies that identified neurons in Fragile X with an abnormally high number of immature dendritic spines. The methods used in the current study did not permit the assessment of alterations in dendritic spine morphology.However, from the findings of this study we cannot make conclusions about synapse maturity. It is possible that the increase in synapses observed in the neurons grown on The development of the CNS is a highly organized process requiring the establishment of correct connectivity with specific target cells. The creation of appropriate neural networks requires an intimate coupling of dendritic arborization and synaptogenesis, perfectly timed to promote the normal circuitry underlying normal neurological function. Individuals with FXS syndrome suffer a diverse range of cognitive impairments. Most research has focused on the effects of a lack of FMRP in neurons, and its implications for the underlying neurobiology of FXS. Knowing that astrocytes contribute to the abnormal neurobiology of this disorder, the current results should promote new therapeutic avenues in the treatment of FXS and related autistic disorders.Using a co-culture system of neurons seeded on astrocytes, we demonstrated that hippocampal neurons showed delays in dendritic growth patterns and also in the expression of excitatory synapses when interfaced with astrocytes that do not express FMRP. This study reinforces the importance of astrocytes in the regulation of normal neuronal development and in the prevention of an altered dendrite phenotype that characterizes Fragile X and autism. Future experiments will focus on differential expression of astrocyte secreted factors and the role of direct neuronal-astrocyte cell contact in the altered developmental sequences we observed in our tissue culture paradigm.SJ designed and performed the tissue culture experiments, immunocytochemistry, morphometric analysis and drafted the manuscript. MN assisted with the tissue culture experiments, immunocytochemistry and morphometric analysis. LD conceived the study, participated in its design and helped to draft the manuscript. All authors read and approved the final manuscript.