Polyethylene glycol  has been shown to mechanically repair damaged cellular membranes and reduce secondary axotomy after traumatic brain and spinal cord injury (TBI and SCI respectively). This repair is achieved following spontaneous reassembly of cell membranes made possible by the action of targeted hydrophilic polymers which first seal the compromised portion of the plasmalemma, and secondarily, allow the lipidic core of the compromised membranes to resolve into each other. Here we compared PEG-treated to untreated rats using a computer-managed open-field behavioral test subsequent to a standardized brain injury. Animals were evaluated after a 2-, 4-, and 6-hour delay in treatment after TBI. Treated animals receive a single subcutaneous injection of PEG. When treated within 2 hours of the injury, injured PEG-treated rats showed statistically significant improvement in their exploratory behavior recorded in the activity box when compared to untreated but brain-injured controls. A delay of 4 hours reduced this level of achievement, but a statistically significant improvement due to PEG injection was still clearly evident in most outcome measures compared at the various evaluation times. A further delay of 2 more hours, however, eradicated the beneficial effects of PEG injection as revealed using this behavioral assessment. Thus, there appears to be a critical window of time in which PEG administration after TBI can provide neuroprotection resulting in an enhanced functional recovery. As is often seen in clinically applied acute treatments for trauma, the earlier the intervention can be applied, the better the outcome. Traumatic brain injury (TBI) is a pernicious event that destroys many lives. Currently, there are no effective pharmacological treatments for TBI . TreatmePEG has been used subsequent to a standardized TBI in the rat to reduce cellular damage in brain in various regions, particularly the white matter of the corpus callosum . AdditioPEG's membrane sealing and reassembly properties were originally utilized for vesicle fusion and hybridoma formation ,9,11. PEThe studies describing the neuroprotective properties of PEG after brain injury persuaded us to test the effect of PEG injection on rat behavior after TBI. In the rat, the same Impact Acceleration injury model as used in the present investigations produced significant behavioral impairment ,1. BrainAll rats studied were 400–450 gram, adult, Sprague-Dawley rats . They were fed (Purina Rat Chow #5001) and allowed water ad libidum. The animals were housed in a climate-controlled facility with a 12:12 hour light:dark cycle. All animal procedures were submitted and approved by the Purdue University Animal Care and Use Committee, with strict attention to university, state, and federal guidelines for the use of animals in research.Rats were anesthetized with 4% isoflurane in 99% oxygen  in a laboratory-fabricated gas chamber. They were intubated endotracheally  and ventilated with 1.5–2.5% isoflurane in 99% oxygen on a Harvard Apparatus small animal ventilator . Body temperature was maintained with a Harvard Apparatus homeothermic blanket control unit. A midline scalp incision was performed, and the periosteum removed to expose the skull. A metal disk, 10 mm in diameter, 3 mm thick, was firmly attached with Loctite super glue gel and dental acrylic  to the skull between the lambda and bregma sutures. A 450-gram brass weight was dropped from a height of two meters onto the disc to induce a severe impact/acceleration injury using this injury model . All aneAfter laboratory induced TBI using the Marmarou model ,5,17 a dNineteen animals of the total of 47 animals used in studies of the 2–6 hour delay were eliminated from the study due to death, skull fracture, or euthanization due to progressive medical problems, an outcome due to using the most severe form of impact. Of the balance, five rats underwent a "sham injury" procedure. These received the same procedures as the injured groups, however the weight was allowed to drop two to three inches from the subject's head. These will be described in the text as "sham injured" or "uninjured" animals. Six "control" rats received a subcutaneous injection of sterile saline, while the experimental groups all received subcutaneous injections of PEG at three time point post injury: six animals at 2 hours, and 8 animals each after a 4-hour, and 6-hour delay in PEG administration. After behavioral testing, animals were sacrificed with an overdose of sodium pentobarbital.We direct the interested reader to significant details of the "activity chamber" construction, the acquisition, management, and validation of data in Koob et al 2006. A 30-minute period of behavioral evaluation in the activity box was used in these investigations. After experimental TBI, a subcutaneous injection of PEG was given at 2, 4, and 6 hours later. Behavioral evaluations were made at 24 hours, 4 days, and 7 days post-injury.X and Y-axis provided data as to the subject's location at any given point . Inserted at equidistant points around the perimeter of the box, 4.5 cm off the base, four infrared beams in the Software designed especially for use with the activity box interpreted the generated series of data points to determine the animal's location in space and time over the course of the experiment (for details and to obtain software see ).Coordinates of the rat's position in space over time can be converted using a spreadsheet  for statistical measurements and the generation of 2- and 3-dimensional graphs 2 + (Y1-Y2)2] determines distance traveled at each 200 msec interval of time. Knowing that the distance between each beam is 20 cm, the resulting sum of distance traveled for all time points over the course of the session is multiplied by 0.2 to give a distance in meters.The distance each subject traveled over the course of data collection was determined by placing the raw data coordinates of the rat's position into a spreadsheet where each beam on each axis is assigned an integer, 1–4;Average speed was calculated by aforementioned distance measurement in meters over the time of the session in seconds.In-house developed computer software collected the rat's coordinates at 200–250 msec intervals, computed the total number of coordinate pairs recorded and number of changes in coordinates throughout the exploration session. Positional coordinate changes indicate movement, thus the number of coordinate changes divided by the total data points recorded equaled the percentage of time spent exploring. As used here, "Percent Time Exploring" reflects not simply exploratory behavior but how quickly and actively the rat moves through the activity box.X or Y-axis, the rat's position could be determined. If beams were not broken, the subject's position could be determined based on the last beam broken and next beam broken. Therefore, the position of the rat in space and time was either determined to be in front of a beam or between two beams, therefore lending a clear nine point by nine point grid of potentially explored location points. Percent area explored was calculated from this 81 point-location grid.To determine the amount of area explored, the coordinates of the rat's position were placed into a spreadsheet file and graphed. If at any given point in time a beam was broken in the An "immediate" intravenous injection of PEG . A trend towards improvement, but statistically insignificant, was noted at the end of the first day post-injury following the 4-hour delayed injection. By 4 days post-injury however, this trend in improvement had become statistically significant  after a 2-hour injection of PEG relative to uninjured animals. The absence of an error bar indicates an SEM that cannot be distinguished from the mean in the bar graph.There was a modest trend for improvement in the average speed attained after PEG injection compared to injured yet untreated animals. This increase only reached significance, however, for PEG-injected animals when administered at 2 hours (day 1 and 7), and for the 4-hour delayed injection at day 4 Figure . SimilarDelaying PEG administration by 2 hours produced a statistically significant increase in the percent time spent exploring compared to injured yet untreated animals on day 1 (for the 2-hour group); day 4 (for the 4 hour group) and at day 7 for both the 2- and 4-hour delayed injection  plays a very substantial role in the resultant catastrophic behavioral loss, both motor/sensory, as well as cognitive. Therefore, there is relatively little time post-injury to affect a rescue of cerebral neurons of the brain when compared to the rescue of comparatively resilient white matter subsequent to SCI. Slowly degenerating white matter within the spinal cord is thus available for longer times after injury to respond to membrane – sealing agents like PEG or Poloxamer – 188. There may be other relevant factors such as changes in the vasculature with time and the sealing of the blood brain barrier at ~5 to 8 hours post-injury in the brain that may also be associated with the loss of PEG effectiveness after cerebral injury. We believe that the extended window in time for the effective use of PEG in SCI is related to these facts.These data suggest that PEG may be clinically useful to victims of TBI if delivered as rapidly as possible after injury. Presently we are beginning a veterinary clinical study of the effect of acute PEG administration in naturally injured canines suffering head injury . It is pPEG solution into animals. Importantly, the lower the molecular weight of PEG, the more toxic might be the byproducts of degradation in the body . Higher molecular weights of PEG  pose no safety risk whatsoever and have been safely used in medicine for over 30 years [Since 1999, we have explored various concentrations and MWs of PEG in pursuing its use as a neuroprotective-sealing agent. Our choices in MW began with the older literature of PEG-mediated cell fusion dating to the 1970s ,7,10 and30 years ,10. Thus30 years ,20. WhenIn our view, it is more likely that a combination treatment may offer the best hope of a significant clinical therapy. For example, acute administration of aldehyde scavengers  may prolPEG: Polytheylene Gycol; TBI: Traumatic Brain Injury; SCI: Spinal Cord Injury; CNS: Central Nervous System.Purdue University has licensed this technology to Medtronics/Sofamor Danek Corporation human clinical testing and commercialization. There is presently no financial support of this research from this corporation in support of the CPR.This work was in partial fulfillment of the requirements for AOK's Doctoral Degree from Purdue University. JMC worked independently on some experiments after his relocation to Dartmouth Medical School, while RBB is the Principle Investigator and Director of the TBI initiative within then CPR, and responsible for all elements of the research. All authors have read and approved the final manuscript.


The pharmacological management of osteoarthritis normally begins with the administration of acetaminophen or a nonselective nonsteroidal anti-inflammatory drug. However, acetaminophen may not be efficacious in all patients, and nonsteroidal anti-inflammatory drugs may be associated with gastrointestinal and cardiovascular adverse effects.A 79-year-old Caucasian man with bilateral hip pain was diagnosed with osteoarthritis of the hip. His past medical history included three prior myocardial infarctions, the most recent one occurring 2 years ago. He is taking aspirin 81 mg once daily. Despite no history of ulcer disease or bleeding, he has been reluctant to take nonsteroidal anti-inflammatory drugs, and because of his cardiac history there is a contraindication to cyclooxygenase-2-specific inhibitors. He was started on naproxen 220 mg twice daily, with the proton pump inhibitor omeprazole 20 mg once daily. Upon follow-up at 4 weeks, his hip pain had decreased from a rating of 7  to 5 on his left side and from 5 to 2 on his right side. The patient began a course of physical therapy in conjunction with a regimen of naproxen 440 mg in the morning and 220 mg at night, plus the omeprazole and acetaminophen 650 mg twice daily. He reported no gastrointestinal effects.The addition of a proton pump inhibitor to nonsteroidal anti-inflammatory drug therapy can reduce the risk of peptic ulcer bleeding by ≥80%, making the incidence of gastropathy the same as with cyclooxygenase-2-specific inhibitors. The fact that naproxen is not associated with an increased risk of acute myocardial infarction made it an appropriate choice for this patient. Osteoarthritis (OA) is the most common joint disorder in the United States and one of the leading causes of disability in the elderly. Approximately 5% of the population over the age of 65 years has radiographic evidence of OA of the hip, and nearly 200,000 total hip replacements are performed annually . There iA 79-year-old Caucasian retired physician presented to the office with a chief complaint of bilateral hip pain that had been present for approximately 2 years but had become increasingly bothersome over the previous 3 months. He described the pain as dull and achy and located anteriorly in both hips with occasional radiation to the groin. At its most severe the pain was rated as a 7 on a ten-point scale in the left hip and as a 5 in the right hip. The pain was most severe in the morning, when the patient first got out of bed, and in the evening, after he had been active all day. There was no history of trauma, and the patient denied other joint symptoms. He reported that acetaminophen 650 mg two or three times daily had been effective for managing his pain but no longer was. He tried ibuprofen 400 mg three times daily, and while it provided adequate pain relief, he was reluctant to begin nonsteroidal anti-inflammatory drug (NSAID) therapy for fear of gastrointestinal (GI) side effects. The patient had taken tramadol, hydrocodone, and oxycodone in the past but experienced troublesome lightheadedness.The patient’s past medical history was significant for coronary artery disease and three prior myocardial infarctions (MIs), the most recent having been 2 years earlier. He was told to take aspirin 81 mg once daily to relieve his current pain. He denied any history of peptic ulcer disease, upper GI bleeding or other bleeding disorders, liver or kidney disease, chronic steroid use, and excessive alcohol intake.On physical examination, the patient was able to walk without an assistive device but demonstrated a slightly antalgic gait. Hip internal rotation was painful and limited to 15° bilaterally. External rotation was 50° on the right side and 40° on the left side. Hip flexion and extension were within normal limits. Flexion-abduction-external rotation (FABER) provocative testing produced hip pain bilaterally. Results of a lower-extremity strength examination are indicated in or hip pain plus hip internal rotation of <15° and erythrocyte sedimentation rate (ESR) of ≤45 mm/hr or hip flexion of <115° if the ESR is not known.This patient met the American College of Rheumatology clinical criteria for OA of the hip , which wThe patient was concerned about long-term NSAID therapy because of potential GI side effects and was reluctant to retry opioid therapy since he had previously experienced lightheadedness. With the patient’s prior history of MIs, cyclooxygenase (COX)-2-specific inhibitors were ruled out as a potential therapy. After reviewing the benefits and relative risk reduction of GI adverse events provided when a proton pump inhibitor (PPI) is used in combination with a nonselective NSAID, his physician decided to start the patient on over-the-counter (OTC) naproxen 220 mg every 12 hours in conjunction with the PPI omeprazole 20 mg once daily. The patient was advised of the black box warnings regarding naproxen that are related to cardiovascular (CV) and GI adverse events , as wellWhen the patient returned to the office 4 weeks later, the patient had been in a physical therapy program for 3 weeks and was taking naproxen 440 mg in the morning and 220 mg at night, omeprazole 20 mg once daily, and acetaminophen 650 mg twice daily. He rated his pain on this regimen as a 5 on a ten-point scale in the left hip and a 2 in the right hip. He was given a straight cane by a physical therapist, which he found to be very helpful in alleviating some of his pain during walking. He reported no adverse GI effects and was pleased with his treatment and progress. He was able to tolerate physical therapy and was learning a home exercise program. A follow-up visit was scheduled for 2 months, during which time the patient will have completed his course of physical therapy; however, he will continue his home exercise program and adhere to his medication regimen.While initial treatment for OA should include nonpharmacologic intervention, when such therapy provides insufficient pain relief, medications should be added while the non-pharmacologic therapy is continued. After careful assessment of risk factors and medical co-morbidities, initial pharmacologic management should begin with acetaminophen or a nonselective NSAID, such as naproxen or ibuprofen. While the nonselective NSAIDs should be used with caution because of their potential for GI side effects, results from a recent observational study showed that the addition of a PPI to NSAID therapy reduced the risk of peptic ulcer bleeding by 82% . The stuPost hoc analysis of the TARGET  study showed that among patients at high CV risk already taking aspirin, the incidence of CV events was significantly higher in the subgroup taking ibuprofen but not in the subgroup taking naproxen when each was compared with lumiracoxib [Another important issue that arises when initiating treatment for patients with OA who are already taking aspirin for cardioprotection is that certain NSAIDs may interfere with the antithrombotic benefits of aspirin through a competitive interaction with platelet COX-1. The co administration of ibuprofen and aspirin has been shown to antagonize aspirin’s irreversible platelet inhibition, indicating that the use of ibuprofen in patients at increased CV risk could limit the cardioprotective effects of aspirin ,12. Postiracoxib . The coniracoxib ,14, or niracoxib , or nonpiracoxib , has notThe application of clinical data to decision making is critical in determining the optimal treatment regimen for patients with OA. The use of OTC naproxen in association with a PPI and low-dose aspirin was found to be effective in treating OA of the hip in this patient with CV and GI risk factors.


Main scope of the EU and FDA regulations is to establish a classification criterion for advanced therapy medicinal products (ATMP). Regulations require that ATMPs must be prepared under good manufacturing practice (GMP). We have validated a commercial system for the determination of bacterial endotoxins in compliance with EU Pharmacopoeia 2.6.14, the sterility testing in compliance with EU Pharmacopoeia 2.6.1 and a potency assay in an ATMP constituted of mononucleated cells used in cardiac regeneration.For the potency assay, cells were placed in the upper part of a modified Boyden chamber containing Endocult Basal Medium with supplements and transmigrated cells were scored. The invasion index was expressed as the ratio between the numbers of invading cells relative to cell migration through a control insert membrane.For endotoxins, we used a commercially available system based on the kinetic chromogenic LAL-test. Validation of sterility was performed by direct inoculation of TSB and FTM media with the cell product following Eu Ph 2.6.1 guideline.Mycetes and B. subtilis were positive after 5 and 3 days respectively. The detection limit was 1-10 colonies.The calculated MVD and endotoxin limit were 780× and 39 EU/ml respectively. The 1:10 and 1:100 dilutions were selected for the validation. For sterility, all the FTM cultures were positive after 3 days. For TSB cultures, A total of four invasion assay were performed: the calculated invasion index was 28.89 ± 16.82% (mean ± SD).We have validated a strategy for endotoxin, sterility and potency testing in an ATMP used in cardiac regeneration. Unlike pharmaceutical products, many stem-cell-based products may originate in hospitals where personnel are unfamiliar with the applicable regulations. As new ATMPs are developed, the regulatory framework is likely to evolve. Meanwhile, existing regulations provide an appropriate structure for ensuring the safety and efficacy of the next generation of ATMPs. Personnel must be adequately trained on relevant methods and their application to stem-cell-based products. The European Union (EU) regulation on advanced therapy medicinal products  (ATMP) iDuring the production of the BM-MNC as medicinal products, variable amounts of impurities product and process-related, are introduced into the final product: cells enter in contact with buffers, reagents and plastics that could be potentially harmful in humans. A safety assessment of BM-MNC cells prepared using density gradient centrifugation should be done in order to ensure that the finished product do not contain any substance or impurity that can have an adverse effect in the patient.BM-MNC should be free from adventitious microbial that could originate from the starting or raw materials or adventitiously introduced during the manufacturing process. In any case, a thorough testing must be performed at the level of finished product in compliance with the methodologies described in the EU or United States Pharmacopoeia (USP), in particular for endotoxin content, sterility and cell potency.Endotoxins are lipo-polysaccharides from gram-negative bacteria and are the most common cause of toxic reactions resulting from contamination with pyrogens: the absence of bacterial endotoxins in a product implies the absence of pyrogenic components, provided the presence of non-endotoxin substrates can be ruled out. Endotoxins can be detected by using the Limulus amoebocyte lysate (LAL) test; unfortunately, it may be masked by factors interfering with the reaction between the endotoxins and the LAL. As a consequence, the suitability of the regents and materials used and the product itself has to be established. The endotoxin limit that can be accepted in a product is based on the route of administration , the threshold pyrogenic dose and volume of the injected product. Some endotoxin limits have been calculated and can be found in the Pharmacopoeia; for non-compendial items and new drugs, the endotoxin limit should be calculated by the user. The Maximum Valid Dilution (MVD) provides an upper bound for dilution that still provides for endotoxin detection at the endotoxin limit. To determine if any interfering characteristics exist, each LAL assay must have a positive product control (PPC) to ensure that endotoxin would be detected if it were present in the sample.in vitro assays using cell systems and in vivo assays using animal models. As concerning the use of bone marrow mononucleated cells in cardiac repair, the importance of characterizing the functionality of injected cells was recently pointed out [in vitro and in vivo assays. Cells were evaluated for hematopoietic colony-forming unit (CFU), and assessment of mesenchymal stem cells colonies. Furthermore, based on the observation that the migratory capacity of bone marrow mononucleated cells predicts the functional improvement after cell transplantation in a hind limb ischemia model [Potency is the quantitative measure of biological activity based on the attribute of the product, which is linked to the relevant biological properties. The assay demonstrating the biological activity should be based on the intended biological effect which should ideally be related to the clinical response. Basically, two types of potency assays can be envisioned: nted out ,16: to eia model  and in hia model , authorsCell migration and cell invasion assays measure the ability of certain cell types to move through a porous membrane toward a chemoattractant or growth factor. In contrast to cell migration through an open pore, cell invasion through an occluded pore is dependent on active enzymatic degradation of the matrix barrier. The Matrigel Matrix consists of laminin, collagen IV, entactin, and various growth factors to mimic the basement membrane. Endothelial cells express proteases MMP 2 and 9, which actively digest the matrix. At the end-point of the assay, invasive cells appear on the underside of the porous membrane and can be quantified.Guidelines for sterility testing of biologics is addressed in the various worldwide pharmacopeias and in Section 21 of the Code of Federal Regulations (CFR), International Conference on Harmonisation (ICH) and Food and Drug Administration Points to Consider documents. ATMP manufactured under GMP conditions require sterility testing performed under GMP guidelines. There are two common types of sterility test methods: the membrane filtration method that requires the test article to first pass through a size exclusion membrane capable of retaining microorganisms and the direct inoculation method requires the sample to be inoculated directly into test media. For the latter, sample is incubated for 14 days in the test media. It is important to determine if the ATMP under testing contains elements able to interfere with the growth of microorganisms within the growth media used for the assay.Aim of this study is the validation of a commercial system (Charles River Endosafe PTS) for the determination of bacterial endotoxins in compliance with Eu Pharmacopoeia 2.6.14 , the validation of the sterility testing in compliance with eu Pharmacopoeia 2.6.1 (sterility) and the validation of the potency assay in an ATMP that is constituted of bone-marrow mononucleated cells used in cardiac regeneration.Testing were performed in the quality control laboratory of the cell therapy unit of the Cardiocentro Ticino. The Laboratory is authorized and regularly inspected by the Swiss competent authorities.For the endotoxin testing and migration assay cells were collected after informed consent from patients enrolled in the "Swiss multicenter intracoronary stem cells study in acute myocardial infarction" . A total of 50 ml of bone marrow was aspirated into heparin-treated syringes from the posterior iliac crest under local anesthesia. Bone marrow was filtered by using a 100 μm nylon mesh , diluted 1:1 in Phosphate Buffered Saline (PBS), and BM-MNC isolated by density gradient centrifugation on Ficoll-PAQUE PREMIUM . Cells were washed three times in PBS filtered through a 70 μm nylon mesh  and then resuspended in 10 ml of 5% v/v human albumin. One ml was collected for migration and invasion assay and endotoxin testing. For the sterility testing, peripheral blood mononucleated cells were obtained from 50 ml of peripheral blood collected from patients immediately after an acute myocardial infarction (AMI) subjected to standard pharmacological therapy.For the immunophenotype, bone marrow and BM-MNC cells were stained in quadruplicate with anti CD45 FITC , anti CD34 PC7 , anti CD133 PE  and with 7-AAD  for the cell viability test. Death cells were excluded from the analysis. Analyses were performed using a Cytomics FC 500 flow cytometer (Beckman Coulter) acquiring at least 100.000 events. Isotype-matched murine FITC, PC-7, and PE conjugated immunoglobulins were used as controls. Cell phenotype was determined by using an ABX Micros 60 .6 BM-MNC collected from acute myocardial infarction patients subjected to standard pharmacological therapy were resuspended in 500 μl of 5% v/v human albumin. For the migration assay, cells were placed in the upper part of an 8.0 μm untreated polyethylene terephthalate membrane 24-well cell culture insert . For the invasion assay cells were placed in the upper part of a modified Boyden chamber Matrigel Invasion Camber : the chamber consist of a 24-well Cell Culture insert with an 8 μm pore size PET membrane, uniformly coated with Matrigel Matrix. The matrix provides a barrier to non-invasive cells while presenting an appropriate protein structure for invading cells to penetrate before passing through the membrane. Both chambers were then placed in a 24-well culture dish containing 500 μl of Endocult Basal Medium supplemented with Endocult Single Quots  and 20% fetal calf serum  and buffers uniformly embedded in the cartridge. The cartridge is inserted into a dedicated reader and 25 μL of the prepared sample are dispensed into the four reservoirs. The reader draws, mixes and incubates the sample with the various reagents at programmed time intervals before transferring it to the optical chambers. The portable spectrophotometer then monitors the change in the optical density and calculates the endotoxin level based on the resulting kinetic values. Cartridges with 5-0.050 EU/mL sensitivity were used in this study. Results are automatically multiplied by the dilution factor entered into the Endosafe system. With the correct dilution the unit achieves results in approximately 15 min.The calculated MVD and endotoxin limit for the ATMP were 780× and 39 EU/ml respectively. The inhibition/enhancement test was done by using the Charles River R+D Inhibition/Enhancement cartridges (range 5-0.05 EU/ml ) and by testing the cell product undiluted and diluted in pyrogen-free water as follows: 1:10; 1:100; 1:500; 1:700; 1:780.This preliminary assay was performed with the aim to find the dilution where the spiked endotoxin can be detected without inhibiting or enhancing the test. Once prepared, the cartridge was inserted in the Endosafe PTS and loaded with 25 μl of the solution in each well. Results were scored after 20 minutes of incubation at 37°C.The ATMP was diluted in LAL reagent water (Charles River ) to 1:10 and 1:100 in pyrogen-free tubes and then loaded in the system. All the tubes, water and pipette-tips were pyrogen-free certified.Sterility testing was carried out under aseptic conditions regularly monitored by appropriate sampling of the working area and by carrying out appropriated controls as specified in on GMP documents.Bacillus subtilis ATCC 6633; Staphylococcus aureus ATCC 6538; Pseudomonas aeruginosa ATCC 9027; Clostridium sporogenes ATCC 19404 and TSB media with 10-100 UFC of Candida albicans ATCC 10231; Aspergillus niger ATCC 16404 and Bacillus subtilis ATCC 6633 . Media were incubated as described for five and three days respectively. Culture plates were inoculated in parallel in order to check the viability of the micro-organisms. Testing was also performed by using the following bacterial strains isolated from bioburden in clean room: Staphilococcus epdermidis 1, Micrococcus lylae and Sphingobacterium multivorum. All testing were performed in duplicate. Bacterial identifications were performed by Gram-staining and by using the mini API detection system . The ID32 and ATB test strips were used for the strain identification .Sterility of the culture media Fluid thyoglicollate medium (FTM) and soya-bean casein digest medium (TSB) used for the culture of anaerobic and fungi/aerobic bacteria  was performed by incubating two vials of medium for 14 days at 32.5°C and 22.5°C respectively. Growth promotion test was performed by inoculating FTM media with 10-100 colony-forming units (UFC) of Validation was performed by direct inoculation of TSB and FTM media with 1% of the total volume of the product under validation as stated in European Pharmacopoeia (2.6.27). For the latter, 500 μl of whole blood and 100 μl of the BM-MNC were inoculated together with 1-10 UFC and 10-100 Colony-forming units of the bacterial strains used in the growth promotion test and incubated as above described. A growth promotion test was performed as a positive control. If clearly visible growth of micro-organisms is obtained after incubation in presence of blood and the ATMP, the product possesses no antimicrobial activity under the conditions of the test, and the sterility may be then carried out without further modification.For the endotoxin testing, a test result was considered valid when the percentage of spike recovery was between 50% and 200% with a coefficient of variation less than 25%.For the sterility testing, the detection limit represent the lowest bacterial concentration in the inoculums that the system can evidence. The specificity of the system represent its ability to detect the single micro-organism in the inoculums and the detection limit represent the lowest micro-organism number in the sample that the system can detect. The robustness of the system represent its ability to obtain identical results when using different products, medium from different lots in different working days.For the invasion assay, data were expresses as the percent invasion through the Matrigel matrix and membrane relative to the migration through the 8.0 μm untreated Membrane (invasion index). The Assay was considered positive when at least ≥10% of the inoculate cells maintain their invasion capacity.Cell phenotype of whole bone marrow and after density gradient separation are reported in Figure 6/ml; 15.2 × 106/ml and 16.2 × 106/ml respectively (16.5 ± 1.2 × 106 mean ± SD) with a pH of 6.5.Testing was performed on three BM-MNC obtained from different patients in three different days. Patient were subjected to standard pharmacological treatment for acute myocardial infarction. The mononucleated cells concentration in the samples were 18.0 × 10Results of the inhibition/enhancement test are reported in Table 6/ml; 12.2 × 106/ml and 15.2 × 106/ml respectively (13.5 ± 1.6 × 106 mean ± SD) with a pH of 6.5.Testing was performed on three whole peripheral blood and the derived mononucleated fractions from different patients in three different days. Patient were subjected to standard pharmacological treatment for acute myocardial infarction. The white blood cell concentration in the mononucleated fraction were 13.0 × 10For the growth promotion test at the end of the incubation period, clearly visible growth of micro-organisms was observed and identity confirmed for all bacterial strains.S. epidermidis 1 growth in both TSB and FTM media at both concentrations whereas M. lylae and S. multivorum growth at both concentrations in TSB medium only. For the validation test, all the FTM cultures resulted to be positive after 3 days at both the concentration tested. For TSB cultures, Mycetes were positive after 5 days and B. subtilis after three. The detection limit of the system was then established in 1-10 colonies. At the end of the incubation period, subcultures in agar plates were performed for all the microbial growth: all the identifications confirmed the starting inoculum confirming the robustness of the system.As concerning the strains isolated from bioburden, A total of four assays were performed in different days. For all the samples a significant invasion index was observed: 28.89 ± 16.82% (mean ± SD). Complete results are reported in Figure Cellular therapy is an emerging field in medicine; all the stem cell medicinal products must be in compliance with principles and guidelines of good manufacturing practice in respect of medicinal products and investigational medicinal products for human use. When any new preparation or method of preparation is adopted, steps should be taken to demonstrate its suitability for routine processing: the defined process, using the materials and equipment specified, should be validated in order to produce cells of the required quality.For certain ATMP that must be administered immediately and that cannot be cryopreserved without damaging the cell viability and quality, the availability of rapid testing method for endotoxin and sterility testing is fundamental.For the latter, traditional methods, including kinetic chromogenic, kinetic turbidimetric and gel-clot LAL assay systems, have been widely used in the pharmaceutical industry. Unfortunately, all of these methods are time-consuming  and become problematic if time-sensitive ATMPs products must be immediately released. In the present paper, we have demonstrated that the PTS endosafe system can be validated for the endotoxin testing of BM-MNC in compliance with European and United States Pharmacopoeia. The time required by the system was approximately 15 min, making it particularly useful as an immediate release testing, where the aim is to prepare and administer the product within a short time period.Sterility testing is regulated by USP 21CFR610.12 and by Eu Pharmacopoeia 2.6.1. We have successfully validated the sterility testing of a mononucleated cell preparation: the sensitivity of the system for the ATCC and bioburden bacterial strains here considered was 1-10 UFC in the inoculums and cultures were positive after approximately 48 hours of incubation.Recently, a rapid microbiological control strategy for cellular products has been issued in EU and USP Pharmacopoeias based on the use of rapid detection systems as the BacT/Alert 3D  or the Bactec . Those systems are in general non destructive, allowing a faster detection when compared to TSB/FTM testing, and products can be released after 7 days. Unfortunately, the microbial growth of certain bacterial strains in those systems is still controversial; as a consequence, those method should be strictly validated both using the prescribed ATCC strains and by using bioburden isolates.All biological products must meet prescribed requirements of safety, purity and potency and no lot of any licensed product may be released by the manufacturer prior to the completion of tests for conformity with standards applicable to such product, including potency. The current regulations allow for considerable flexibility in determining the appropriate measurements of potency that is necessary for product characterization testing; however, the complexity of an ATMP product can present significant challenges in establishing a potency assays.The migration assay of BM-MNC in response to endothelial growth factors, seems to correlate with the beneficial effects of the cell infusion after myocardial infarction ,16: thisBasic and clinical scientists, as well as scientists working in the biotechnology and pharmaceutical industries, need an increased awareness of the questions that must be answered before a stem-cell-based product can be used clinically. Unlike pharmaceutical products, many stem-cell-based products may originate in academic laboratories where researchers are unfamiliar with the applicable regulations. As new stem-cell-based therapies are developed, the regulatory framework is likely to evolve. Meanwhile, existing regulations pertaining to biologic products and human cells, tissues, and cellular and tissue-based products provide an appropriate structure for ensuring the safety and efficacy of the next generation of stem cell-based medicinal products. As they conduct research on stem cells, scientists should be aware of the relevant regulations and their likely application to this products.The authors declare that they have no competing interests.GA wrote the manuscript, SS and VLC performed the experiments, DS performed the sample collections as co-investigator of the Swiss Ami clinical Trial, MG performed literature search, GS and TM participated in study design and coordination. All the authors read and approved the final manuscript.


Drosophila melanogaster genome were documented, of which 40% show tissue-restricted expression.Embryonic expression patterns for 6,003 (44%) of the 13,659 protein-coding genes identified in the  Cell and tissue specific gene expression is a defining feature of embryonic development in multi-cellular organisms. However, the range of gene expression patterns, the extent of the correlation of expression with function, and the classes of genes whose spatial expression are tightly regulated have been unclear due to the lack of an unbiased, genome-wide survey of gene expression patterns.Drosophila melanogaster genome with over 70,000 images and controlled vocabulary annotations. Individual expression patterns are extraordinarily diverse, but by supplementing qualitative in situ hybridization data with quantitative microarray time-course data using a hybrid clustering strategy, we identify groups of genes with similar expression. Of 4,496 genes with detectable expression in the embryo, 2,549 (57%) fall into 10 clusters representing broad expression patterns. The remaining 1,947 (43%) genes fall into 29 clusters representing restricted expression, 20% patterned as early as blastoderm, with the majority restricted to differentiated cell types, such as epithelia, nervous system, or muscle. We investigate the relationship between expression clusters and known molecular and cellular-physiological functions.We determined and documented embryonic expression patterns for 6,003 (44%) of the 13,659 protein-coding genes identified in the Nearly 60% of the genes with detectable expression exhibit broad patterns reflecting quantitative rather than qualitative differences between tissues. The other 40% show tissue-restricted expression; the expression patterns of over 1,500 of these genes are documented here for the first time. Within each of these categories, we identified clusters of genes associated with particular cellular and developmental functions. A defining feature of multi-cellular organisms is their ability to differentially utilize the information contained in their genomes to generate morphologically and functionally specialized cell types during development. Regulation of gene expression in time and space is a major driving force of this process.in situ hybridization [in situ hybridization has the potential to reveal both spatial and temporal aspects of gene expression during development. However, RNA in situ hybridization is not quantitative [A gene's expression pattern can be defined as a series of differential accumulations of its products in subsets of cells as development progresses. Patterns of mRNA expression are studied by two principal methods - microarray analysis  and in sdization ,3. Microdization . A majordization ,6. RNA ititative . For theDrosophila melanogaster as an organism for the global study of gene expression during embryonic development. Genetic and molecular analyses have led to a deep understanding of many embryonic processes in this animal [in situ hybridization have been developed [Drosophila body plan is now the best understood example of a complex cascade of transcriptional regulation during development [There are several reasons for choosing s animal . Classics animal  and robueveloped -12. In meveloped . Such stelopment ,15.Drosophila embryogenesis. Taking advantage of non-redundant gene collections [in situ hybridization of gene specific probes to fixed Drosophila embryos [Drosophila genes, are largely representative of the genome as a whole, allowing the global analysis of gene expression during the embryonic development of a multicellular organism. We organized the complex gene expression space by a hybrid fuzzy-clustering approach that uses microarray profiles to supplement the CV annotation of in situ patterns. We divided the resulting clusters into two categories, broad and restricted. Broad patterns are characterized by quantitative enrichment in tissues that are related by specific cellular states. Restricted patterns are highly diverse and provide a basis for defining gene sets expressed in related tissues and with related predicted functions.We have assembled an atlas of gene expression patterns during lections ,17, we p embryos  and docu embryos . The CV in situ hybridization and systematically annotated with CVs (Release 2.0). The number of genes in the dataset has more than doubled from Release 1 [Drosophila genome.The starting point for our analyses is a collection of 6,003 genes whose embryonic expression patterns we have assayed by elease 1 , from 2,elease 1 , providielease 1 ) betweenDrosophila Controlled Vocabulary for Anatomy maintained by FlyBase [To annotate gene expression patterns, we used a set of 314 anatomical terms selected from the broad  FlyBase . We grou FlyBase .Of the 6,003 genes annotated, 4,759 (79%) showed detectable expression in the embryo, while the remaining 1,244 (21%) were annotated with only the 'No staining' CV term. By grouping genes with identical annotations, the 4,759 genes with detectable expression in the embryo were subdivided into 205 multi-gene groups and 2,335 'singleton' groups . By relaxing the criteria and grouping genes that had at least 75% of their annotation terms in common, we identified 393 multi-gene groups and 1,804 singletons. If we consider each of the multi-gene groups and each of the singleton groups to represent a distinct expression pattern, this method suggests that there are up to 2,197 distinct patterns within our dataset .in situ annotation profiles was calculated using a custom metric that independently weighted the contribution of each developmental stage range .To further refine the number of expression categories, we developed a clustering strategy that allowed us to incorporate the quantitative temporal expression data obtained from the microarray experiments together with the qualitative, but spatially rich, data on expression patterns from the CV annotations. We implemented this approach within the framework of fuzzy c-means clustering ,23 and dThe fuzzy c-means algorithm is fuzzy in that each gene is assigned to one or more clusters . As multOf 4,759 genes expressed in the embryo, we had microarray expression data for 4,496. The best fuzzy c-means run grouped these genes into 39 clusters, and each cluster was designated as either 'broad' or 'restricted'. Clusters containing a significant fraction of genes annotated as 'ubiquitous' were designated as broad, as were clusters containing primarily genes with unrestricted maternal only expression . We also decided to include as broad those clusters of genes exhibiting maternal expression early and midgut-only expression late. Many genes annotated in this way Figure  encode tThe ten clusters encompassing broadly expressed genes have relatively similar array profiles, but the diversity of annotations makes the boundaries between these clusters somewhat arbitrary Figure . While tIn situ hybridization showed continued ubiquitous staining throughout embryogenesis, with the heaviest staining resolving to the differentiated midgut, muscle, hindgut, foregut, and anal pads. Genes within this cluster exhibit diverse cellular functions, but within its core members are more than half of all genes known to be involved in nucleolar-based ribosome biogenesis .Cluster 1B is one of the several broad clusters characterized by peak microarray expression around hours 4-5 . Genes in 3B often appear restricted to the midgut, but this cluster was classified as 'broad' due to its apparent relationship to cluster 2B, both in its overall expression profile and its enrichment for mitochondrial genes . There is a significant correlation (p = 3.7e-9) between the genes in clusters 2B and 3B with genes shown in an RNA interference (RNAi) screen to be induced by the histone de-acetylase SIN3, suggesting a possible regulatory mechanism [in situ clustering (p = 2.6e-8 correlation with cluster 10B), suggesting that this common expression pattern is often beneath the level of detection by whole mount in situ hybridization.Genes in cluster 2B and many in cluster 3B are characterized by peak expression levels around hour 12 (stage 15) and by t Figure . Clusterechanism . A substp = 6.6e-5) and 5B , and the cell cycle, 4B  and 5B . Consistent with this overrepresentation of cell-cycle regulated genes, there is significant overlap between the genes in these clusters and a set of 65 genes identified in an RNAi screen for dE2F transcriptional targets [p = 2.2e-12) and 20% belonging to 4B .Clusters 4B and 5B are characterized by peak expression levels around hours 4-5 (stage 10) and often resolve to exhibit staining in the differentiated nervous system and midgut Figure . The two targets . We havep = 1.1e-29) and other genes involved in protein metabolism. Additionally, 40% of the 100 genes identified as essential for viability based on a large RNAi screen [p = 2.6e-16).Genes in cluster 6B are almost uniformly annotated as ubiquitous at all stages of embryogenesis and this annotation is supported by relatively high average array expression levels at all time points Figure . ClusterThe genes in clusters 1B-6B exhibit remarkably similar expression patterns during gastrulation and were most frequently annotated as endoderm and mesoderm anlagen  show a spike in expression during the blastoderm stage, correlating with the onset of zygotic transcription, and differ from those in clusters 7B, 8B, and 10B by their annotation as 'ubiquitous' through gastrulation. It is likely that for genes in cluster 7B and 9B, the diminishing maternal expression is augmented by zygotic expression; however, a method that specifically distinguishes between maternal and zygotic transcripts is required to categorize these patterns conclusively.Clusters 7B-10B are composed of genes with maternally deposited transcripts that diminish after stage 7 Figure . Those iin situ screen is that a CV annotation strategy is insufficient to describe these patterns fully.The genes and expression patterns in broad clusters have largely failed to attract the attention of developmental biologists, as indicated by the fact that the embryonic expression of only 4.3% of them have been described in the scientific literature . Yet, thWhile the diversity of expression patterns was considerable, our hybrid clustering approach identified a number of tissue or domain specific expression patterns shared among a significant number of genes. While these clusters are more easily categorized than the broad clusters, there is still considerable ambiguity between clusters Figure .Clusters 1R-4R contain 383 genes expressed in various combinations of the yolk nuclei, fat body and blood related tissues Figure . ClusterClusters 5R-7R contain 1,160 genes expressed late in embryogenesis (stage range 13-16) in a number of epithelial structures Figure , includiClusters 13R-16R contain 525 genes expressed specifically in the central and peripheral nervous system Figure . In contClusters 18R and 19R contain 229 genes expressed in either differentiated somatic muscle Figure  or diffeClusters 23R-29R contain 422 genes expressed in a domain-specific manner beginning in the blastoderm stage embryo and typically continuing in a tissue-specific manner throughout embryogenesis Figure . Many geAn additional eight clusters contain 349 genes with late tissue-specific expression . Some of these contain genes expressed throughout development in a single tissue, like the cluster of genes expressed in pole and germ-cell , while others, like the cluster of midgut-specific genes , are primarily expressed in a particular tissue at a particular time.cis-regulatory modules [cis-regulatory modules that are associated with the individual restricted clusters and to examine whether or how these modules are utilized to achieve the observed diversity in gene expression.Despite the significant number of genes that conform well to the patterns represented by the above clusters, a large fraction is expressed in unique combinations of tissues or organs. Fuzzy clustering assigned these genes to the set of clusters that best described their expression patterns. Of the 1,947 genes expressed in a restricted manner, 795 (41%) are assigned to more than one cluster . On the other hand, these patterns are not unrelated. We consider the 29 restricted clusters the most prominent recurring patterns in the dataset, and we can only speculate where to place the biologically significant number of patterns within these two extremes. It is clear that the clusters are not homogenous since 41% of the genes exhibit composite patterns. If we look at all observed combinations of cluster assignments, we find 454 distinct combinations, and 287 of these cluster combinations consist of a single gene. We favor the idea that many of the composite patterns observed result from simple additive combination of the basic patterns driven by independently acting cis-regulatory modules. Direct examination of the patterns that each of these cis-regulatory modules generates in transgenic reporter assays, rather than the patterns of entire genes, will be more powerful in revealing the underlying mechanisms and logic governing the generation and evolution of each gene's expression pattern.Can we estimate the number of distinct expression patterns in Besides grouping genes according to the similarity of gene expression patterns, we used our annotation dataset to define relatedness among tissues based on the similarity of the set of genes expressed in them. Figure The largest, most interconnected set of structures roughly corresponds to the epithelial pattern defined by clusters 5R, 6R and 7R. Notably, the salivary gland duct is isolated from the salivary gland body, reflecting their functional divergence and differential gene expression. The salivary gland duct and trachea are linked by their shared expression of genes required for cuticle deposition. In terms of gene expression, the anal pads are more similar to the hindgut than to other epidermal structures. The large distance between neural and other ectodermal derivatives suggests that specification of neuronal versus epidermal cell fate leads to profound genome-wide changes in transcription. Patterns within the digestive system are interesting - while hindgut and foregut expression are strongly correlated, midgut expression is markedly different despite its functional and spatial relatedness, reflecting its distinct developmental origin.Determining a gene's pattern of expression is a key step towards understanding its function during development. The functions of many genes have been determined, either by direct experimental analysis or by sequence homology and compiled by the GO consortium . Additiop values. We interpolated these results using a log-linear regression function to fit the empirical distribution . The results of this analysis are shown in Additional data file 8, which lists all GO essential .To examine the enrichment of GO and Uniprot categories in individual gene expression clusters, we performed exhaustive pair-wise comparisons . We used methods ) and Uniin situ photographs but is enriched for genes involved in cuticle metabolism. Since formation of the cuticle effectively prevents RNA in situ hybridization, we propose that the genes in cluster 8B are likely expressed during late embryogenesis in a pattern resembling epithelial expression (similar to cluster 5R and 6R), although this pattern cannot be visualized by the standard in situ protocol. The late spike in the average array profile of cluster 8B genes supports this notion.To summarize the functional associations of gene expression clusters, we created a force-directed layout network, which brings into close proximity clusters and GO/Uniprot categories sharing a significant number of genes Figure . In the Interestingly, cluster 7R, containing genes with early (stage 12) onset epithelial expression, clearly separates from 5R and 6R, which contain genes with late epithelial expression (stages 13-16). Early epithelial expressing genes are associated with GO terms for tissue specific functions, such as membrane trafficking, morphogenesis, cell polarity, motility and adhesion, which makes them similar to genes found in the early blastoderm patterning gene cluster (cluster 26R). In contrast, late epithelial clusters (clusters 5R and 6R) associate clearly with cuticle formation in terminally differentiated tissues. This is the best example in our dataset of separation between regulatory developmental genes and effector genes  of the tGenes in cluster 24R are expressed in yolk, mesoderm, dorsal ectoderm and anterior and posterior endoderm anlagen at the blastoderm stage. Consistent with this early expression, these genes are expressed later in differentiated midgut, yolk, fat body and plasmatocytes. The force directed layout suggests that these genes are functionally related to clusters 1-4R, which contain genes expressed in yolk, fat body and blood and involved in metabolite transport. Cluster 24R clearly separates from other blastoderm stage clusters, suggesting that for these particular tissues, specific effector genes are required early in and throughout embryonic development.GO terms related to membrane trafficking, such as secretory pathway, vesicle transport, Golgi apparatus, and ER, assume a central position in the layout with numerous connections to diverse clusters both broad and restricted. This likely reflects the requirement of these core cellular processes in diverse cell types, but also indicates that there are tissue specific differences in the utilization of these pathways. The modulation of these pathways is mediated by GTPases , which eCNS and muscle clusters associate with the expected GO terms for nerve impulse transmission and muscle contraction, respectively. Interestingly, despite their clear functional specialization, both tissues show a common requirement for components of the extracellular matrix.Another way to uncover relationships between gene expression and gene function is to examine the representation of GO terms in individual tissues using the 'anatograms' Figure . For exaCell adhesion molecules are similar to transcription factors in that they are expressed early in development in a number of anlagen, and are later abundant in the nervous system. In addition, these molecules are moderately enriched in differentiated epidermal derivatives Figure . CytoskeComparison of GO terms and gene expression data often leads to self-evident observations because many functional GO assignments are based on published gene expression patterns. We used the Uniprot catalog to correlate gene expression and protein domains Figure . Figure We have described the most complete set of data on spatial and temporal patterns of gene expression during embryogenesis that has been compiled for any metazoan organism. The extent, quality, and unbiased nature of this dataset allowed us to describe and explore gene expression patterns during embryogenesis on a genome wide basis. Below we discuss three issues: how this data can be used as a resource by biologists; the inherent challenges in analyzing such a complex set of data; and what we learned about global strategies for regulating gene expression during embryonic development of a complex multi-cellular organism.cis-regulatory prediction pipelines to identify significant associations between gene expression specificity and genomic sequence features.The dataset we assembled can be used in several ways. First, it provides a rich source of candidate genes for further in-depth study. Researchers interested in a particular developmental process, for example, morphogenesis of the salivary gland, can search our annotations and retrieve a list of genes that are expressed in that structure. Such a gene set can be further subdivided by manual curation, using our primary image data. Second, the clustering classification allows one to address more abstract questions, such as: which genes are expressed in a regulated manner at cellular blastoderm? And which genes are involved in organogenesis in the late embryo? Finally, the dataset represents a starting point for an analysis of the sequence determinants of gene expression patterns. Clustering provides gene groupings based on spatio-temporal gene expression, ranging from unique patterns, through small tightly co-regulated gene sets, to large gene expression classes. These classes can be tested against Drosophila embryo. To address the difficulty of summarizing the gene expression patterns of a group of genes, we developed a new visual aide - the anatogram. Anatograms show the 'position' of a given gene set in the complex space of spatio-temporal gene expression patterns and represent a convenient way to summarize such data for groups of genes. Anatograms also provide an intuitive comparison of differences among groups of genes, which can supplement more rigorous statistical comparisons. Any list of genes can serve to generate an anatogram; for example, the list of Drosophila genes homologous to a gene group in another organism, or the genes that contain a particular sequence motif. In this way, anatograms can be used to compare results from gene expression studies among different species. The color code is based on organ systems shared by metazoan organisms and can be adapted to spatio-temporal gene expression data from other animals, providing an organism-independent way to present spatial gene expression data.Determining expression patterns is only a first step towards further understanding gene function and, therefore, it is important to intersect our spatial expression data with other genomic datasets. Our tools allow anyone with a list of genes, for example, derived from a targeted microarray analysis, to obtain the spatio-temporal expression patterns of these genes in the in situ hybridization survey of developmental processes. Microarrays provide independent measurements that help control the artifacts of in situ hybridization methods, and also provide a quantitative measure of gene expression that is especially important for the interpretation of broadly expressed genes. The combined analysis of these two datasets is synergistic. In situ hybridization reveals the spatial diversity in tight temporal clusters and microarray clustering reduces the artificial diversity introduced by assigning annotations based on the qualitative in situ assay.Our results suggest that parallel microarray analysis should be an integral part of any Drosophila embryogenesis, it is possible to achieve great precision in expression pattern description. However, making distinctions based on the fine details of patterns, such as different subsets of the CNS, can be problematic when examining genes one by one. We found that it was useful to reduce the granularity of the CV to the level where the annotation assignments are most reliable. This approach necessarily underestimates the true diversity of expression patterns; for example, the expression of GstS1 in a distinct subset of cells in the midgut was annotated simply as midgut. On the other hand, this approach enables description of undefined subsets of cells and their grouping with the correct higher order structures. The fine details of differences among expression patterns on a cellular level can be addressed by comparing images of the individual members of the broader groups defined by CV annotation, or by double labeling in situ experiments [In the context of an anatomically well-described system such as eriments ,37. A coeriments ,39.Many genes are expressed ubiquitously but non-uniformly, giving the appearance of a restricted expression pattern. Identifying and correctly categorizing such ubiquitous patterns is important because their description with the standard vocabulary makes it difficult to separate them from genes with true restricted expression patterns. We identified two major classes of ubiquitous patterns, a midgut CNS pattern and an endoderm mesoderm pattern. Late in embryogenesis these differentially stained structures become apparent, whereas immediately after gastrulation there are no apparent differences among the ubiquitous patterns.in situ assay presumably because deposition of the cuticle prevents entry of the probe. In contrast, genes that are expressed in a very small subset of embryonic cells are more likely to be detected by in situ hybridization than by microarray analysis (data not shown).Embryonic development encompasses the complete spectrum of developmental and cell biological processes and, thus, it is not surprising that we detect the expression of 80% of the 6,003 genes we studied. Even this high number underestimates the number of genes expressed during embryogenesis. Our microarray data indicate that the late embryonic genes escaped detection in our Of genes in our unbiased set, 45% are expressed in broad patterns. Broad genes tend to encode proteins that mediate core cellular processes and their apparent patterns reflect quantitative differences in requirements for basic cellular machineries in different tissues, especially late in embryogenesis.Of the genes in our dataset, 35% show spatially and/or temporally restricted gene expression. Our data reveal a tremendous diversity of gene expression patterns. Sets of genes that exhibit exactly the same tissue specific gene expression are rare and usually limited to mature organs. Genes with identical restricted expression patterns spanning multiple stages of embryogenesis were not found, even at the limited resolution level offered by our imaging technique. Genes that are expressed during mid-embryogenesis in a specific tissue very frequently show unrelated patterns earlier and later in development. Consequently, genes that serve as lineage markers by being expressed in a given organ system from anlagen, through primordia to final differentiated organs are rare and, for the most part, had already been discovered by genetic analysis.In order to classify the complex expression patterns, we used a fuzzy clustering approach that allows a gene to participate in multiple clusters. We found that nearly all genes with restricted patterns fell into one of six clearly distinguishable restricted pattern types: yolk, blood and fat; epithelia; nervous system; muscle; blastoderm; or other, less frequent, organ specific patterns. Within each of these basic types, several subtypes were distinguished by their preferential expression in particular combinations of tissues.cis-regulatory code that is responsible for initiating common patterns of gene expression and the potential for diversity in the control of gene expression. Since the control of gene expression is thought to be modular, it is possible that combinations of significantly smaller numbers of regulatory modules achieve the overall diversity of patterns.Remarkably, 41% of the genes belong to more than one cluster, underscoring the diversity of gene expression. It is perhaps expected that the majority of gene expression patterns will be unique when one considers all developmental stages. The diversity of patterns suggests that many genes are turned on independently multiple times in development. It is less intuitive that, in terminally differentiated tissues, many genes are expressed in multiple organ systems. The existence of expression clusters indicates that the restriction of gene activities within organ systems and developmental lineages frequently occurs, whereas the fuzziness of the clusters suggests that expression in atypical combinations of tissues can be achieved. It will be interesting to investigate the D. melanogaster serves as a starting point for further investigation of genomic regulatory networks in development and their evolution.What is the functional significance of the observed pattern diversity? Are all the minute features of the vast number of unique patterns necessary to carry out development? Or is the complexity of patterns largely a consequence of position effects in the proximity of regulatory modules that have little deleterious effect. Careful comparisons of gene expression patterns across multiple closely related species should reveal the patterns that are under evolutionary constraint. Our genome-wide dataset of patterns in in situ hybridization to Drosophila embryos was performed as described [Drosophila embryos by in situ hybridization and documented the expression patterns by digital microscopy. The histochemical color reaction was stopped in all wells of the 96-well plate at the same time once staining pattern appeared for three included control probes as well as in most wells of the plate (1-1.5 hours at 37°C). Individual embryo images were assigned to one of six stage ranges that coincide with major developmental transitions in embryogenesis, and the development of the pattern across time was confirmed with independently derived Affymetrix microarray time course data covering the first 12.5 hours of embryogenesis [in situ experiments representing 6,580 genes. We assembled data from multiple independent experiments for 1,514 (23%) genes (labeled RNA probes were generated separately for each experiment). The same EST clone was used as the source for the probe in 1,241 of the multiple experiments, while different ESTs were used as the source in the remaining 273. Low-resolution production images were captured for all 6,003 genes. No high resolution images were captured for genes labeled as maternal, ubiquitous or no expression . At least one high-resolution image was captured for the remaining 3,365. Of these, 2,202 have high-resolution images at all six stage ranges, and 1,163 are missing at least one stage range. We captured high-resolution images only at stage ranges when a gene was expressed.Large-scale production of gene expression patterns by RNA escribed . Brieflyogenesis . The imaThe primary curator (AB) assigned anatomical terms from the CV concurrently with image acquisition for each gene, providing a first pass annotation of its expression pattern. When the dataset was finalized, a second curator (VH) reviewed and edited the initial annotation assignments. In this second round of annotation, genes with similar or related patterns of expression were examined side by side; these comparisons allowed us to significantly improve the internal consistency of our annotations.We used two approaches to review annotations . Each approach generated lists of genes with related expression patterns that were then used by the second-round curator to review the annotations of individual genes for consistency. The first approach was purely image-based and did not make use of the first round annotations. For each of the first four stage ranges, we examined images of embryos from all 6,580 genes. We developed a software tool for displaying these images in batches, and a subset of images sharing a particular feature  was manually selected. These gene lists were further subdivided until meaningful subsets could no longer be identified.The second approach used the first round annotations to generate lists of genes ordered by similarity to particular sets of CV terms. We developed a software tool that generated lists for any arbitrary set of CV terms, but we found it most productive to define 12 relatively independent sets, each focused on a single organ system, that together covered the entire annotation hierarchy.en masse to make the resulting annotations as uniform as possible. CV terms were added or deleted as necessary, and genes with satisfactory and complete annotations were deemed finished and removed from all re-annotation lists. As part of this process the curator removed 577 (9%) of the genes from the dataset when the quality of the primary data was judged to be insufficient to support high-quality annotation.The lists generated by the two approaches were used to re-annotate similar genes To describe the spatial and temporal gene expression patterns in embryogenesis, we used only two types of relationships, 'part of' to cover spatial relations and 'develops from' to cover temporal relationships among structures. Importantly, we linked terms to six developmental stage ranges and used 'develops from' relationships exclusively to link terms that belong to consecutive stage-ranges. Our anatomical terms were organized into a hierarchical tree, starting with stage range 1-3, which used only two CV terms , and progressively branching through the six stage ranges until stage-range 13-16 with 126 anatomical terms . Anatomical structures that were contained within a larger structure are linked to the larger structure by the 'part of' relationships . Anatomical structures that develop from one another across time are linked by the 'develops from' relationship ). CV terms can have simultaneously the 'part of' and the 'develops from' relationships . Every term occurs in the hierarchy only once. In a few cases where two terms develop into a single later structure , the strictly hierarchical nature of the tree is broken, and both were linked to the child term ('midgut') by the 'develops from' relationship. This fits the directed acyclic graph (DAG) format that is used to capture many biological ontologies.in situ results. Several such blocks may be defined within a single organ system, for example, 'trunk and head somatic and visceral musculature'  in the muscle system. We also collapsed terms referring to the same organ system across a range of stages: structures from stage range 4-6 were collapsed into early organ systems anlagen; structures from stage ranges 7-8 and 9-10 into mid organ systems ; and structures from stage ranges 11-12 and 13-16 into late organ systems . For example, Endocrine_heart refers to the combined anatomical terms for all components of the circulatory and endocrine related structures at stages 11-16 .Many specific structures representing small subsets of tissues had very few or none of the 6,003 interrogated genes expressed within them (50 structures had 8 genes or fewer). We summarized the data by focusing on a subset of 145 structures that make up the most common and readily distinguishable structures in our dataset. Genes annotated with more specific structures were collapsed into more general parent structures. For example, the terms 'dorsal epidermis', 'dorsal apodeme', 'dorsal histoblast nest abdominal', 'dorsal ridge' and 'leading edge cell' were collapsed into 'dorsal ectoderm'. We distinguished two levels of collapsing. Within a stage range, we collapsed the 'part of' relationships to the parent term. The resulting 'blocks' of terms represent the most relevant units of embryo anatomy for describing the RNA n (the number of genes in the list under study) and p . Under this model, the expected number of genes would be np, so gene counts greater than np received positive enrichment scores and counts less than np received negative enrichment scores. The enrichment score was simply the number of standard deviations above or below np in the distribution binomial , or the standard score (z-score).Enrichment in the linear annotation profiles was displayed as the statistical significance of the over- or under-representation in the number of genes annotated with the given structure. The expected number of genes was modeled as a binomial distribution with parameters in situ hybridization and present on the Affymetrix Drosophila 1.0 gene chip. Microarray data were extracted and normalized as described in [There were 4,496 genes detected in at least one tissue by ribed in . An addiribed in ,41 packag × s binary matrix S of CV annotations  where Si, j is 1 when gene i is annotated with term j, and 0 otherwise; g is the number of genes in the dataset and s is the number of annotation terms. We used the 145 term collapsed version of the annotations for all clustering. An additional input matrix L (for 'levels') was the real-valued g × t matrix containing the normalized microarray values [Input to the fuzzy clustering algorithm was the y values ,41.k clusters was represented by a g × k matrix M and iteratively estimated. This matrix was randomly initialized with:The basic procedure was similar to that outlined in , where [r is sampled from the uniform  distribution. The matrix was then re-normalized so that i. A distance function di, j was calculated at each iteration and used to update membership values:where φ is a 'fuzziness' parameter that determines the level of competition between clusters for the same gene . While fuzzy clustering is generally thought to be most useful at φ values of 2 through 10 [φ was set above 1.5, the dataset would converge to one or two very fuzzy clusters composed of diffuse sets of terms. On the other extreme, if we used completely hard partitions , the majority of clusters were empty. If we used a partitioning close to 1, we found that each resulting cluster was distinct. We tried a range of values between 1 and 1.5 and used a φ of 1.05, which yielded the best results (data not shown).Here, rough 10 , we founM dropped below 5e-5, where:Iterations were stopped when the average difference in the membership matrix, ΔL and a binary valued S. Instead of maintaining a discrete centroid model to obtain distance values d, we instead defined di, j as the average distance of gene i to all other genes k, where each k is given the weight of its membership in cluster j:We tried using classical mean  and medoδik is the distance between gene i and gene k. In this way, distances between all pairs of genes are transformed into distances between genes and clusters.Here, si, k in terms of the spatial similarity ss and the array similarity sl :In order to use annotation similarity to determine the contribution of array similarity (as described in Results and discussion), we defined an asymmetric mixture function where microarray similarity has a significant effect when the annotation similarity was medium to high, but very little effect when the annotation similarity was low . The mixture function defines the combined similarity The spatial similarity ν is the median and the absolute deviation is:where The microarray similarity fficient . As a med metric . This mede novo transcriptional initiation most frequently occurs, cellularization and organogenesis. Stage ranges 7-8 and 9-10 represented in most cases carry-over expression from stage range 4-6, and were difficult to score and, therefore, were less reliable. The weights used for each stage range were: stage range 1-3 (7%), stage range 4-6 (36%), stage range 7-8 (7%), stage range 9-10 (7%), stage range 11-12 (7%) and stage range 13-16 (36%).Some stage ranges have only a single associated annotation term , while others have many more (stage range 13-16 has 37 collapsed terms of which up to 17 are used in a single annotation record). The relative abundance of stage range 13-16 terms dominate any metric where each term is given the same weight, so we calculated a stage range-specific similarity independently for each stage and then produced a weighted sum. Stage ranges 4-6 and 13-16 received higher weights because they coincide with two periods in embryogenesis when The similarity score for each stage range consisted of two components: a positive 'match bonus' score for the extent to which the two genes had terms in common, and a negative 'mismatch penalty' score for the extent to which the two genes had mismatched terms. The match bonus contributed twice as much as the mismatch penalty to the overall score:Where The classification of clusters as broad or restricted was made automatically based on the average annotation terms of the genes assigned to the cluster. We classified a cluster as broad if any of the following criteria were met: over 30% of the genes in the cluster were annotated as ubiquitous at some stage from 7 to 16; if the cluster had 75% maternal genes and no restricted annotation terms in two-thirds of the genes; if the cluster contained genes with only maternal and late midgut staining (see Results and discussion). All other clusters were classified as restricted.M often assigned a gene high membership scores in neighboring, highly related clusters. In order to mitigate this fact and assign multiple memberships in a meaningful way, we performed an exhaustive analysis of cluster similarities to assign each gene to a set of significantly unrelated clusters. First, the raw membership matrix was transformed to a binary matrix M* using a threshold of mmin. Next, a distance score Δi, j between each pair of clusters i and j was determined from M* by dividing the number of genes in common by the number in the smaller of the two clusters:As described in the text, we did not attain a fuzzy c-means clustering result where clusters had sharp boundaries. Therefore, the raw membership matrix g is first assigned to the cluster inew with the highest membership score, that is, j that are within a maximum distance dmax of inew  We averaged the results across all runs, calculating the number of times a particular gene was assigned to a particular cluster. By plotting the distribution of values, we identified a natural cutoff at 400/10,000 - gene/cluster assignments occurring in at least 400 of the 10,000 runs became final.Rather than determining a single set of The 'balls and springs' models presented in Figures na∩b is the number of genes shared by CV term a and CV term b, and na∪b is the number of genes in either a or b. For figure a and GO/Uniprot term b is proportional to the Pearson correlation coefficient obtained when comparing the enrichment z-scores of a to those of b. In this way, type II edges are not an indication of the actual number of genes in common between two GO/Uniprot categories, but rather the extent of similarity of the 'expression patterns' of those genes. Likewise, the type III edge between expression cluster c and expression cluster d is not determined by the number of genes shared between those two clusters, but rather the similarity in function between those two sets of genes.where We used the GO and Uniprot databases from April 2006 for all comparisons. A gene was considered to belong to a particular GO category if it associated with the category itself or any descendant of the category linked via IS_A and/or PART_OF relationships in the GO DAG. For instance, if a gene were annotated as an endopeptidase (GO:0004175), it would also be considered a peptidase (GO:0008233). Because many related GO terms have highly redundant sets of genes assigned to them, we also selected a set 179 of GO terms  and proq, was defined as the fraction of the 6,003 annotated genes assigned to the category. For an expression cluster containing n genes total, the background was modeled as a binomial  distribution. When the expression cluster contained x genes within the particular functional category, the exact probability of observing this many or more genes, Pr(X = x)~binomial , was calculated using Matlab's binocdf function .To evaluate whether a given expression cluster was correlated with a particular functional category, we used a statistical binomial test. The background frequency for the functional category, p value attained (pα) was determined within each of the four functional classes , and the empirical distribution was compiled based on the distribution of pα values obtained.We corrected the statistical significance values for multiple testing by creating an empirical distribution of binomial test scores for a large number of randomized gene lists. To generate the gene lists, genes were randomly sampled (without replacement) from the entire genome of 14,586 genes (Release 4.3). We sampled 100,000 such lists for each list size from five genes to 1,000 genes (in increments of 5 genes). Each sample was then statistically tested against all GO and Uniprot categories using the binomial test as described above. The most significant (lowest) pα value obtained for an actual test, we fit the distribution to a log curve using log-linear regression , fitting the parameters a and b in the function log(p) = alog(pα) + b. This produced a function that was a good fit for all list sizes, whereas fitting a linear function (p = apα + b) generally produced fits that deteriorated at low p values.In order to interpolate this empirical background distribution to any given ss ≤ 1 and an array (level) similarity score 0 ≤ sl ≤ 1, the function sc = sl + (1 - sl)sl ss gives a similarity score where microarray similarity has a significant effect when annotation similarity is medium to high, but very little effect when annotation similarity is low.The following additional data are available with the online version of this paper. Additional data file p value smaller than 0.001. B = broad, R = restricted. ‡Total number of unique genes in cluster. §GO or Uniprot id. ¶GO or Uniprot name. ¥Ratio between observed and expected number of genes in intersection of the two gene lists. #Number of genes in cluster annotated with given GO or Uniprot term. **Number of genes in the genome annotated with given GO or Uniprot term. ttAdjusted p value of binomial z test testing the null hypothesis that the overlap between the two gene lists is random. Additional data file Additional data file The schematic of our image-driven curation strategy is shown on the left. The curator generated lists of genes  and the computer produced all the images associated with those genes. Images were presented in batches that were navigated in a manner similar to Google searches with progress tracking. Pages that were viewed were marked. Gene names were shown in the corner of the first image for that gene. The curator reviewed the annotations of all genes expressed in a tissue, for example CNS, and by clicking on an image showing CNS staining, moved that image and the associated gene name to a child gene list. The images for the selected genes were eliminated from the parent pages. Both the parent and child gene lists were stored in a specialized database called the 'list manager' . Lists bClick here for fileComparison of the distribution of selected GO terms  in the Click here for fileWe collapsed the 16 well-defined embryonic stages  into sixClick here for fileFor each organ system, we listed: the 'total' number of genes annotated with any raw annotation term that belonged to that organ system; the number of genes restricted ('restr.') to that organ system, meaning that at the stage range indicated the gene was annotated ONLY with raw terms of that organ system; the number of genes expressed in the organ system and at the same time not expressed in an equivalent organ system at another stage of development (restr. 4-6 and restr. 7-10); the total number of genes expressed in the equivalent organ systems connected by 'develops from' relationship at stage range 4-6 OR stage range 7-10 (st 4-10 uni. = union); and the number of genes expressed in equivalent organ system connected by 'develops from' relationship at stage range 4-6 AND stage range 7-10 (stages 4-10 intrs. = intersection). For each collapsed annotation term (block) we listed: the total number of genes annotated with any raw annotation term that belongs to that block; and the number of genes restricted ('restr.') to the block, meaning that at the given stage range the gene is annotated ONLY with raw terms from the block and no other terms from another block. The organ systems and blocks are color-coded. Mapping of organ systems to blocks of terms and blocks of terms to raw terms is available as supplementary on-line material .Click here for fileSimilar to Additional data file 4, we listed for each organ system and each block of terms: the total number of genes that were annotated with ANY raw annotation term that belonged to that organ system or block; the number of genes expressed ONLY in the organ system or block at the given stage (restr.); the number of genes expressed in the organ system or block and at the same time not expressed in an equivalent organ system or block at another stage of development (restr. 11-12 and restr. 13-16); the number of genes expressed in equivalent organ systems or blocks at stage range 11-12 OR stage range 13-16 (st 11-16 uni. = union); and the number of genes expressed in equivalent organ systems at stage range 11-12 AND stage range 13-16 (stages 11-16 intrs. = intersection). The organ systems and blocks are color-coded. Mapping of organ systems to blocks of terms and blocks of terms to raw terms is available as supplementary on-line material .Click here for fileGenes that share between 50% and 100% of their annotation terms  were grouped and the resulting number of groups enumerated (y-axis). The solid line in each graph shows the total number of groups thus formed for a given level of uniformity. The dashed line shows the total number of groups with a single gene member (singletons) for a given level of uniformity. For uniformity levels of 100%  and 75% (3 out of 4 terms matched within the group) we highlight the total number of groups, the number of singletons and the difference between the two. (A) Data for all genes expressed in the embryo (B) for genes belonging to broad clusters and (C) for genes in restricted clusters.Click here for filess ≤ 1 and an array (level) similarity score 0 ≤ sl ≤ 1, the function sc = sl + (1 - sl)sl ss gives a similarity score where microarray similarity has a significant effect when annotation similarity is medium to high, but very little effect when annotation similarity is low.Given an annotation  similarity score 0 ≤ Click here for filep value smaller than 0.001. B = broad, R = restricted. ‡Total number of unique genes in cluster. §GO or Uniprot id. ¶GO or Uniprot name. ¥Ratio between observed and expected number of genes in intersection of the two gene lists. #Number of genes in cluster annotated with given GO or Uniprot term. **Number of genes in the genome annotated with given GO or Uniprot term. ttAdjusted p value of binomial z test testing the null hypothesis that the overlap between the two gene lists is random.*Terms with adjusted Click here for fileSimilar to Figure Click here for file