Morphinofobia among the general population (GP) and among health care professionals (HP) is not without danger for the patients: it may lead to the inappropriate management of debilitating pain. The aim of our study was to explore among GP and HP the representation and attitudes concerning the use of morphine in health care.A cross-sectional study was done among 412 HP (physicians and nurses) of the 4 hospitals and 10 community health centers of Beira Interior and among 193 persons of the GP randomly selected in public places. Opinions were collected through a translated self-administered questionnaire.A significant difference of opinion exists among GP and HP about the use of morphine. The word morphine first suggests drug to GP  and analgesia to HP . The reasons for not using morphine most frequently cited are: for GP morphine use means advanced disease (56%), risk of addiction (50%), legal requirements ; for HP it means legal risks  and adverse side effects of morphine such as somnolence - sedation  The socio-demographic situation was correlated with the opinions about the use of morphine.False beliefs about the use of morphine exist among the studied groups. There seems to be a need for developing information campaigns on pain management and the use of morphine targeting. Better training and more information of HP might also be needed. During the last decades, considerable progress has been recorded in the knowledge of the action and the use of opiates in pain management -3. In spWhy has this knowledge not been applied by HP and did not have the expected effects among the GP? Do morphine frighten so much the GP and HP becoming a public health problem?Morphinofobia can be defined as a set of false beliefs concerning the negative effects of morphine in the management of pain , an inapMorphinofobia seems widespread and caused by ignorance, prejudices, false beliefs, economic marketing strategies and limitations in the availability of morphine ,10-16.et al. [et al. [et al. [In 1960, the studies of Robins et al.  and Abel [et al.  reported [et al. ,14,20-25et al. [Musi et al.  studied Our study aims to compare morphinofobia among the general population (GP) and health professionals (physicians and nurses) (HP) in a country where the consumption of morphine was multiplied by 4 over the last decade , though et al. [The survey was carried out between August and November 2005 using two structured questionnaires, developed based on the model of Musi et al. . One of The GP was recruited randomly on a given day in two shopping centres, three urban restaurants, the weekly marketplace and at the railroad station of Guarda. The participation criteria were: at least 18 years old, able to answer the questionnaire and living in the region of Beira Interior.As to the GP, a questionnaire was addressed to 800 HP (nurses and physicians) employed at four hospitals of Beira Interior  and ten community care centres  with the agreement of the regional Department of Health of Beira Interior.The HP were working in internal medicine, general surgery, paediatrics, oncology, orthopaedics, emergency and community home care. The participation criteria were: be employed in one of the hospitals or community home care centres for at least a year and having a completed training as a nurse or as a physician.The questionnaires were distributed via the management of the institutions and answers were returned by the same channel under ceiled envelope. The inquiry was anonymous. The study was approved by the Research Ethics Committee of the University Institute of Kurt Bösch Sion, Switzerland.et al. [For each group, we developed a specific questionnaire based on the study of Musi et al. .The first part of each questionnaire addresses socio-demographic data. The second part of the questionnaire addresses the perception people have of "morphine", its efficacy and its side effects. The questionnaire also explores the attitudes concerning the use of morphine and its acceptance. A judgment scale of 5 levels, ranging from "completely disagree" to "completely agree" was used.2of Pearson », « t-test for matched samples » and « correlation of Pearson » using the software program SPSS version 15.0. Significant differences  between categories or groups of variables were defined at 95%.Data was analyzed with « Khi The sampling among GP and HP yielded a total of 606 respondents.194 persons of GP answered the questionnaire. One questionnaire was discarded. About six out of ten respondents were women. Age range was between 18 and 80 years. About 20% of the respondents had not been to school and about 30% had only attended primary school. Almost half of the interviewed people lived in urban areas. A vast majority of respondents (87%) were Catholics  and 46 physicians (11%). The participation rate of nurses was 52,3% the physicians' 46,0%. On the average the participation rate was 51,5%. Three quarters of the respondents were women. The average age was 35,5 years. About 70% of the respondents lived in semi-urban areas. The majority of the HP (93%) were Catholics , whereas for GP it first means «drugs» . Other differences exist between GP and HP, such as «medication» , "sedation- somnolence» , «cancer» , «dependency»  «opiate» , «relief» . Some similarities also exist, such as «pain-suffering»  and «end of life - death» . One third of GP « does not know » what morphine stands for. The results are summarized in Table Significant differences exist between GP and HP in their perception of the word "morphine". For HP the word "morphine" first stands for « gesic » 3,9% , wheThe opinions among GP and HP concerning the use of morphine as an analgesic appear in Table it means that it is serious» , the smallest for «there is a risk of somnolence or sedation» GP shows more false beliefs than HP concerning the use of morphine as an analgesic. The largest difference exists for «Table sex of the respondents and the questions «risks of delirium» , «diminish the surviving period» , «risks of increasing doses»  and «the legal risks» . A weak negative relationship was seen between sex and the expressions «it means that it is serious» , «risks of dependency» , «risks of somnolence»  «limited life expectancy»  and «risks of discrimination» . Men are less prone to consider and use morphine as an analgesic than women.Data analysis shows an absence of a significant relationship between the age of the respondents and the perceptions of the use of morphine. The older the respondents, the more false beliefs exist about the use of morphine.A positive weak relationship was observed between the level of training of the respondents and the variable «legal risks»  was observed. A weak positive relationship was observed between place of living and the expressions «it means that it is serious» , «risks of dependency» , «diminish surviving period» , «limited life expectancy»  and «risk of discrimination» . No relationship was noticed with the variables «risk of delirium» , «risks of somnolence» , «risks of accustom»  and "legal risks» .A weak negative relationship between This study compared the use of morphine as perceived by GP and HP in the region of Beira Interior in North-Eastern Portugal. There are differences of perception but also common fears. It might well induce some reluctance regarding the use of morphine. This in turn might influence negatively patient care in general and pain management more specifically.et al. [et al. [et al. [et al. [Most studies reporting "false beliefs" regarding the use of morphine in pain management focus either on specific ethnics groups or on health professionals ,4,29-31.et al.  in North [et al.  reports  [et al.  and Robi [et al.  show a set al. [et al. [et al. [In our study morphinofobia among HP seems related to false beliefs on side effects of morphine, risks of addiction and legal constraints in the prescription of morphine. Yet the word morphine is principally associated with the notion of analgesia. Musi et al.  reports  [et al.  mention  [et al.  analysed [et al.  reports  [et al.  studying [et al.  in a revet al. [Many studies report fears and false beliefs concerning the use of morphine in pain management among HP ,22,38-40et al.  report fet al.  and fromet al. .et al. [et al. [et al. [et al. [The existence of false beliefs on pain, addiction and abuse of morphine have also been reported by Gilson et al.  in a stu [et al.  reported [et al.  studying [et al.  question [et al. ,46-49. S [et al. . Ripamon [et al.  concludesocio-demographic features and the perceptions of the use of morphine in pain management. Yet morphinofobia was highest among little-educated older men living in rural areas. The cultural and geographic influences on attitudes and beliefs regarding morphine among patients with non cancerous pains have been stressed by Monsivais et al. [et al. [Our results showed a rather weak relationship between s et al.  and Cice [et al. . However [et al.  is cauti [et al.  mentioneet al. [et al. [Health professionals play an important role as far as morphinofobia is concerned, be it through a possible lack of knowledge regarding morphine ,54, be iet al.  and Edwa [et al.  thereforThere are limits to our study. First a generalisation to the population of Beira Interior of our observations might not be indicated because of the small sample of GP and its opportunistic nature. Second, our study focused on attitudes and perceptions on morphine of GP  and HP and did not take in consideration the patients' vision. Third, it should be kept in mind that some of our results are matter of debate in the specialized literature ,52. LastThis study contributes to a better understanding of "the myths of morphine" among the general population and health professionals in the region of Beira Interior. It suggests that efficient pain management is not limited to the prescription of an adequate analgesic according to « the golden standard ». The success of a morphine prescription is influenced by a multitude of other factors.et al. [Our results are in accordance with the results of the study by Musi et al.  done in This leads us to suggest that there is a need for information campaigns targeting the general population and for better training programs targeting health care professionals based on the theory of planned clinical behaviour  in orderThe authors declare that they have no competing interests.HV carried out the study concept, drafted the manuscript, the data analysing and interpretation, the follow-up and participated in the questionnaire design and data collection. EKM carried out the design of the questionnaire, the study concept and participated in the draft of the manuscript. MF carried out the design and the translation of the questionnaires, survey and data collection and contributed in the data analysis and interpretation. CHR conceived the study, participated in the questionnaire design, data analysis and interpretation and the draft of the manuscript. PC carried out the draft of the manuscript and participated in the data analysis and interpretation. All the authors approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1472-684X/9/15/prepub


Adjunctive therapy with locally delivered antimicrobials has resulted in improved clinical outcomes. The aim of this study was to evaluate the efficacy and safety of locally administered minocycline microspheres (Arestin™) in the treatment of chronic periodontitis.A total of 60 sites from 15 patients in the age group of 35-50 years, who had periodontal pockets measuring 5-8 mm and had been diagnosed with chronic periodontitis, were selected for the study. The selected groups were randomly assigned to either the control group (group A) or the treatment/test group (group B). Only scaling and root planing were done at the base line visit for the control sites followed by local application of Arestin™ (1 mg). Clinical parameters such as plaque index, gingival index, and gingival bleeding index were recorded at baseline, day 30, day 90, and day 180 in the selected sites of both the groups. Probing pocket depth also was recorded at baseline, day 90, and day 180 for both the groups.A statistically significant reduction was observed in both groups. Group B showed better results than Group A and these differences were statistically significant.The results of this study clearly indicate that treatment with scaling and root planing plus minocycline microspheres (Arestin™) is more effective and safer than scaling and root planing alone in reducing the signs of chronic periodontitis. These are found in high levels in gingival tissues and gingival crevicular fluid of patients with periodontal disease.[Periodontal diseases are polymicrobial in nature and the complex interaction among many microbes makes the disease a challenging one to understand and treat. Host inflammatory response to plaque microorganisms causes tissue damage, leading to the destruction of the periodontal tissues in an episodic manner. Bacterial products have the ability to stimulate host cells to secrete a wide variety of inflammatory mediators that have numerous biological activities, some of which cause soft tissue and bone destruction. Cytokines such as tumor necrosis factor- α (TNF- α), interleukin-1β (IL-1β), and inflammatory mediators such as prostaglandin EThe extent and degree of periodontal destruction varies widely from patient to patient, and in different sites within the same patient. These variations could be due to the presence of complex subgingival populations of microorganisms in different sites. Periodontal diseases are characterized by the presence of periodontal pockets, which are not easily accessible for plaque removal.Bacteria in the subgingival area are organized in a complex microbial biofilm. Biofilms are matrix-enclosed bacterial populations that are adherent to each other and/or surfaces or interfaces. These microbial plaques are extraordinarily persistent, difficult to eliminate, and play a vital role in periodontal disease. PhysicalSuccessful treatment is dependent on halting tissue destruction through the elimination or control of etiological agents, together with microbial shift towards one typically present in health. Mechanical therapy alone may fail to eliminate invasive, pathogenic bacteria because of their location within the gingiva and dental tissues, which are inaccessible to periodontal instruments. Treatment strategies aiming primarily at suppressing or eliminating specific periodontal pathogens include local and systemic administration of antibiotics. In orderOne of the biggest benefits of any locally delivered drug is that it does not require patient compliance for regular drug intake. The clinician places the drug which releases the antimicrobial for an extended period of time at a steady pharmacological level. Another Arestin™ is made up of minocycline, a semi-derivative of tetracycline, and a very potent broad-spectrum antibiotic. Minocycline has significant antimicrobial activity against a wide range of organisms as well as an anticollagenase effect. MinocyclArestin™ delivers minocycline in a powdered microsphere delivery system. The microspheres have diameters ranging from 20 to 60 μ. The active ingredient is minocycline hydrochloride which exists as particles distributed throughout the interior of the microspheres. When Arestin™ is administered, it immediately adheres to the periodontal pocket.[Gingival crevicular fluid hydrolyzes the polymer, causing water-filled channels to form inside the microspheres. These holes provide escape routes for the encapsulated antibiotic for sustained release. The active drug dissolves and diffuses out of the microspheres through the channels into the surrounding tissues. After ten days, the microspheres are fragmented and continue to release minocycline for 14 days or longer; eventually, these microspheres completely bioresorb.Traditional therapies such as tooth brushing, flossing, subgingival irrigation, and mechanical debridement are successful for patients with mild periodontal diseases. However, as the periodontal pocket deepens, the patient's home care procedures as well as professional debridement loses effectiveness, making local drug delivery a viable option. The addition of local delivery can also help to maintain or control the disease between maintenance visits.The purpose of this study was to compare the clinical effects of scaling and root planing with those of scaling, root planing, and local administration of minocycline hydrochloride (1 mg) (Arestin™) delivered subgingivally in patients with chronic periodontitis.A total number of 15 patients aged 35-50 years diagnosed with chronic periodontitis and having probing depths ranging from 5 to 8 mm as well as radiographic evidence of bone loss, were selected for the study from the Department of Periodontics, Meenakshi Ammal Dental College and Hospitals, Chennai.Ethical approval was obtained from the Institutional ethical committee for the study.Inclusion criteria for patient selection.Patients in the age group of 35-50 years.Patients diagnosed as suffering from chronic periodontitis having a probing pocket depth of 5 to 8 mm with radiographic evidence of alveolar bone loss and without mobility of teeth.Patients willing to take part in the study and maintain appointments regularly.Exclusion criteria for patient selection.Patients having systemic diseases like diabetes mellitus, hypertension, bleeding disorders, hyperparathyroidism.Pregnant women and lactating mothers.Patients allergic to tetracyclines.Patients who have had periodontal treatment in last six months.Antibiotic therapy within three months prior to treatment.Long-term therapy within a month prior to enrollment with medications that could affect periodontal status or healing.Patients with medical or dental therapy scheduled or expected to occur during the course of this study that could have an impact on the subjects ability to complete the study.A total number of 60 sites from 15 patients were selected for the study. The duration of the study was for six months. Four sites were identified for the study in each patient: Two sites served as control sites (Group A) and two sites on the contralateral side served as test sites (Group B). For all patients, general, oral and full mouth periodontal examination was carried out and informed consent was obtained from the patients. On screening day (day 0), patient evaluation was followed by impressions for the fabrication of acrylic stents required for the measurement of pocket depths in the control and test sites during the study period . VariablThe following parameters were recorded:Plaque indexGingival indexGingival bleeding indexProbing pocket depthThe control and test sites were grouped and treated as follows:Group A (control) - Comprised of 30 sites; only scaling and root planing was done at the baseline visit.Group B (test) - Comprised of 30 sites; scaling and root planing was followed by local application of Arestin™ (1 mg) at the baseline visit.th day. During this visit, all clinical parameters, except probing depth, were measured. An additional application of Arestin™ (1 mg) was given in the test sites,. The control and test sites were also examined on the 90th and 180th days, and all clinical parameters including probing pocket depth were recorded.Both the control and test sites were again examined on the 30Application of minocycline microspheres .After insertion of the local drug delivery system, the patients were advised not to eat hard food that could traumatize the gingiva. They were also advised not to brush the area for 12 h or to floss or use interproximal cleaning devices for ten days. During the study period, the patients were instructed to continue regular tooth brushing and interdental cleansing. They were also instructed not to use any mouth washes for the duration of the study.t-test/Student's paired t-test wherever appropriate. The proportion of positivity of the gingival bleeding index was compared between control and test groups by Pearson's chi-square test with Yate's continuity correction/Fisher's exact test (two-tailed) wherever appropriate. In the present study, P < 0.05 was considered as the level of significance.Means and standard deviations were estimated from the samples for each study group. Mean values were compared by Student's independent P < 0.0001). The mean reduction in the gingival index score in group A was 0.23 ± 0.35 from day 0 to day 30, 0.28 ± 0.50 from day 0 to day 90, and 0.38 ± 0.49 from day 0 to day 180, all statistically significant differences (P < 0.0001). The mean reduction in probing pocket depth values for group A was 0.24 ± 1.07 from 0 to day 90, 0.37 ± 1.08 from day 0 to day 180, a difference that was not statistically significant. The mean reduction in plaque index scores in group B from day 0 to day 30 was 0.56 ± 0.45, 0.72 ± 0.32 from day 0 to day 90, and 0.78 ± 0.32 from day 0 to day 180, all statistically significant differences (P < 0.0001)%. The mean reduction in gingival index scores in group B was 0.72 ± 0.55 from day 0 to day 30, 0.80 ± 0.41 from day 0 to day 90, and 0.95 ± 0.49 from day 0 to day 180, all statistically significant differences (P < 0.0001). The mean reduction in probing pocket depth for group B was 1.73 ± 0.87 mm from 0 to day 90, and 1.66 ± 0.96 mm from day 0 to day 180, again a statistically significant difference (P < 0.0001) [The mean reduction in the plaque index score in group A from day 0 to day 30 was 0.46 ± 0.43, 0.42 ± 0.42 from day 0 to day 90, and 0.53 ± 0.39 from day 0 to day 180, all statistically significant differences ( 0.0001) .P < 0.0001). The reduction in bleeding on probing was significant in both groups A and B. The reduction in group B was significantly higher than the reduction seen in group A on the 30th day, 90th day, and 180th day.P < 0.0001). The mean reduction in probing pocket depth between days 0 to 90 and days 0 to 180 was statistically significant between the two groups (P < 0.0001).th day from the baseline, but there was a significant difference in the plaque index on the 90th and 180th days between the two groups [et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.[In our study, no statistically significant difference was observed between the two groups on the 30o groups . These f [et al., Mullur e,[et al., Saito et,[et al., Jones et,[et al., Timmerma,[et al., Hagiwara,[et al., and Vans.,[et al.et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.[In our study, the mean reduction in plaque index scores between days 0 and 30 for groups A and B was not statistically significant . Howeveret al., Vansteen,[et al., Saito et,[et al., Jones et,[et al., Timmerma,[et al., Radvar e,[et al., Hagiwara,[et al., Vansteen,[et al., and Kina.,[et al.et al.,[et al.,[et al.,[et al.[When group A and group B were compared, a reduction in bleeding was seen from the sites in both the groups, but the percentage of reduction in bleeding from the sites was more in group B compared to sites of group A . This waet al., Vansteen,[et al., by Mullu,[et al., and Timm.,[et al.et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.,[et al.[A significant reduction in probing pocket depth was found in group B when compared with group A . This waet al., Vansteen,[et al., Saito et,[et al., Jones et,[et al., Timmerma,[et al., Radvar e,[et al., Makoto U,[et al., Hey-Riye,[et al., Hagiwara,[et al., Vansteen,[et al., Kinane e,[et al., Williams,[et al., Dean et ,[et al., and Gree.,[et al.The above results show that scaling and root planing plus Minocycline microspheres provide significantly greater probing depth reduction than scaling and root planing alone. This significant change in all the clinical parameters examined in the test group, is because Arestin™ releases therapeutic doses of the drug for more than 14 days, well above the minimum inhibitory concentration needed to kill most putative pathogens for periodontal disease. A pharmaFrom the results of the study, the following conclusions can be drawn:Test sites where Minocycline microspheres were employed, displayed a statistically significant reduction in all the clinical parameters  after treatment as compared to control sites, which showed only minimal changes.A degradable, subgingivally placed drug delivery system containing 1 mg Minocycline microspheres, is a safe and efficient adjunct to scaling and root planing in the treatment of chronic periodontitis.The results of this study confirm that Minocycline microspheres are a safe and efficient adjunct to scaling and root planing, and can produce significant clinical benefits when compared to scaling and root planing alone.


Patients, who meet criteria 1 and 2 and possibly 4, but not criterion 3, can be designated as schizophrenia with secondary negative symptoms. Only those patients who satisfy all four criteria should be designated as schizophrenia with deficit syndrome. Those patients meeting criteria 1, 2 and 3, but not criterion 4, could either be schizophrenia with primary, non-enduring negative symptoms though these patients with passage of time may satisfy full criteria for schizophrenia with deficit syndrome and thus become schizophrenia with deficit syndrome.Carpenter To further distinguish deficit syndrome from primary, non-enduring negative symptoms, the authors suggesteOver the years, considerable research on deficit schizophrenia has been conducted. Patients with deficit schizophrenia differ from non-deficit schizophrenia on variables such as risk factors, symptom profiles, neuropsychological functioning, family history, course of illness, treatment response and structural and functional neurobiology. Studies have also shown that deficit schizophrenia has long-term diagnostic stability. Some resantecedent, concurrent and predictive validators.To address the question of validity of deficit schizophrenia, available data can be divided into three classes of potential validators. This scheme represents an adaptation and enlargement of the validating criteria for psychiatric illnesses as outlined by Robin and Guze. The poteet al.[et al.[et al.[There is evidence to suggest that patients with deficit schizophrenia differ from non-deficit schizophrenia on sociodemographic variables pertaining to gender and marital status; on other sociodemographic variables no significant differences have been reported. In an initial report, Carpenter et al. stated tl.[et al. reportedl.[et al.10 Furthel.[et al. Some of l.[et al.12 In a fl.[et al. found thOne study suggested that patients with deficit schizophrenia have lower rate of obstetric complications.Studies have shown that patients with deficit schizophrenia have poorer premorbid adjustment than patients with non-deficit schizophrenia before the appearance of positive psychotic symptoms.–1215–2112There is some evidence to suggest that when compared with non-deficit schizophrenia, the patients with deficit schizophrenia appear to have an increased family history of schizophrenia,22–24 wit1422A winter birth excess has repeatedly been associated with schizophrenia. However, it is interesting to note that subjects with deficit schizophrenia demonstrate summer birth as a risk factor for the deficit form of schizophrenia. This finding has been consistently replicated in population-based studies of incident cases of psychosis30 and prClinical description of the concept of deficit schizophrenia has been described earlier. Various studies have evaluated the construct validity of deficit and non-deficit subtypes and have shown that deficit schizophrenia is associated with greater social and physical anhedonia,33 more a2034161736On neurological examination compared to a matched non-deficit group, the deficit schizophrenia subjects were found to have higher level of soft neurological signs, higher i15et al.[22Patients with deficit schizophrenia exhibit selective impairments on a number of neurocognitive measures that are purportedly partly subserved by dorsolateral prefrontal basal ganglia-thalamocortical circuit. Buchanan et al. comparedet al. In anothet al. These diet al. Studies et al.2240 on set al.22 However,et al.22Oculomotor dysfunction, i.e. eye tracking disorder is significantly associated with deficit schizophrenia and it is suggested that both may have common pathophysiology of cerebral cortical-subcortical circuits.42 Furtheet al.[There are inconsistent findings from structural imaging studies with regard to deficit schizophrenia. Some studies have reported that patients with deficit and non-deficit groups differ significantly in prefrontal white matter volume, with the non-deficit group having smaller volumes and the deficit group having similar white matter volume compared to normal controls. Another et al. comparedet al. in whichet al.[N-acetylaspartate (NAA) to creatine plus phosphocreatine in deficit schizophrenia compared to healthy subjects or non-deficit patients, a finding suggesting a neuronal loss in the medial prefrontal cortex of deficit patients.[During the attempt to retrieve poorly encoded words, patients of non-deficit syndrome had significantly greater activation of the left frontal cortex compared to patients with the deficit syndrome. However, there was no difference between the two groups in the activity of the hippocampus during memory retrieval. Liddle eet al.54 reportpatients.et al.[et al.[Studies have suggested various biological markers/correlates of deficit schizophrenia. Waltrip et al. reportedet al. However,l.[et al. did not P = 0.006), which remained significant even when the data were corrected for covariates like positive psychotic symptoms and demographic features known to be associated with cytomegalovirus seropositivity.[Another study linked deficit schizophrenia with the presence of serum antibodies to cytomegalovirus  concentrations in deficit schizophrenia. Ribeyre et al. reportedet al. which in.[et al., who founet al.[Ozdemir et al. measuredet al.[Studies which have evaluated the genetic differences between deficit and non-deficit schizophrenia fail to suggest differences between the two groups. Wonodi et al. reportedet al.Studies have shown that patients with deficit schizophrenia continue to exhibit poorer social and occupational function than other patients with chronic schizophrenia161721 an161716934521et al.[Relatively few studies have attempted to examine the improvement of primary negative symptom with antipsychotics and even there the findings are conflicting. In clinical trials that used the SDS to distinguish deficit and non-deficit groups, the positive symptoms of patients with deficit schizophrenia showed the same therapeutic response to clozapine as patients with non-deficit schizophrenia, but there was no improvement in the negative symptoms of patients with deficit schizophrenia. However,et al. failed tet al. however,et al.et al.[Criteria for the deficit group were explicitly developed by Carpenter et al. Since thFrom available data, it can be concluded that there are meaningful and robust differences between deficit and non-deficit cohorts and the available data are consistent with both the separate disease hypothesis and the competing hypothesis of a disease severity continuum. Hence, further studies are required to firmly establish one or the other hypothesis. However, at present, it can be concluded that separating deficit and non-deficit groups reduces the heterogeneity of schizophrenia.


Thus computational approaches for detecting protein complexes from protein interaction data are useful complements to the limited experimental methods. They can be used together with the experimental methods for mapping the interactions of proteins to understand how different proteins are organized into higher-level substructures to perform various cellular functions.Most proteins form macromolecular complexes to perform their biological functions. However, experimentally determined protein complex data, especially of those involving more than two protein partners, are relatively limited in the current state-of-the-art high-throughput experimental techniques. Nevertheless, many techniques (such as yeast-two-hybrid) have enabled systematic screening of pairwise protein-protein interactions Given the abundance of pairwise protein interaction data from high-throughput genome-wide experimental screenings, a protein interaction network can be constructed from protein interaction data by considering individual proteins as the nodes, and the existence of a physical interaction between a pair of proteins as a link. This binary protein interaction graph can then be used for detecting protein complexes using graph clustering techniques. In this paper, we review and evaluate the state-of-the-art techniques for computational detection of protein complexes, and discuss some promising research directions in this field.Experimental results with yeast protein interaction data show that the interaction subgraphs discovered by various computational methods matched well with actual protein complexes. In addition, the computational approaches have also improved in performance over the years. Further improvements could be achieved if the quality of the underlying protein interaction data can be considered adequately to minimize the undesirable effects from the irrelevant and noisy sources, and the various biological evidences can be better incorporated into the detection process to maximize the exploitation of the increasing wealth of biological knowledge available. Most proteins form complexes to accomplish their biological functions -3. In faet al. [in vitro purification of whole-cell lysates [While there are a number of ways to detect protein complexes experimentally, Tandem Affnity Purification (TAP) with mass spectrometry  is the pet al.  have sho lysates . This meen masse have enabled the construction of PPI networks on a genomic scale. A graphical map of an entire organism's interactome can be constructed from such experiments by considering individual proteins as the nodes, and the existence of a physical interaction between a pair of proteins as a link between two corresponding nodes. Given that protein complexes are molecular groups of proteins that work together as "protein machines" for common biological functions, we may expect the protein complexes to be functionally and structurally cohesive substructures in the binary PPI networks [Recently, high-throughput methods  for networks . Researcnetworks , suggestnetworks . HoweverBefore we review the current computational approaches for protein complex detection, let us make a principled distinction between two biological concepts, namely, protein complexes and functional modules . A proteLet us now introduce some terminologies which are widely used in protein complex mining. Then, we will present the use of traditional graph clustering techniques for complex mining followed by some new emerging techniques for this task.G = , where V is the set of nodes (proteins) and E = {|u, v ∈V } is the set of edges (protein interactions). A graph G1 =  is a subgraph of G if and only if V1⊆V and E1⊆E. For a node v ⊆V , the set of v 's direct neighbors is denoted as vN where vN = {u |u ⊆V,  ⊆ E }. v 's degree in G, deg (v ), is the cardinality of vN, i.e., |vN|. Density. A PPI network is often modeled as an undirected graph G, denoted as density (G ), is defined to quantify the richness of edges within G as shown in equation (1) [density (G ) ≤ 1. If density (G ) = 1, then G is the fully connected graph or a clique, which has the maximum number of edges, i.e., every pair of distinct vertices is connected by an edge.The density of the graph tion (1) . BasicalClustering Coeffcient. The clustering coeffcient of a node v is the density of the subgraph formed by vN and their corresponding edges, which quantifies how close v 's neighbors are to being a clique (complete graph) [e graph) .Local Neighborhood. Given a node u ∈V, its local neighborhood graph uG is the subgraph formed by u and all its immediate neighbors with the corresponding interactions in G . It can be formally defined as uG= , where uV= {u } ∪u N, and uE= {| ∈j , vk E, v ∈u V}If the edges in the PPI network are weighted , thew (e ) is the weight of the edge e .where v is the weighted density of the subgraph formed by Nv and their corresponding edges.Similarly, the weighted clustering coeffcient of the node First, we review the conventional graph clustering approaches for protein complex mining. These methods mine for cliques or densely connected subgraphs in PPI networks which could correspond to protein complexes. While the methods mainly use the PPI networks for mining, additional information, such as gene expression data ,24, funcIn this section, let us describe the graph clustering approaches that use PPI networks as the sole underlying dataset for the mining task.MCODE.The MCODE algorithm proposed by Bader et al. [k-core in node 5's neighborhood graph with k=2 [d = 5/6 . Thus, node 5 has an initial weight w (5) = k × d = 2 × 5/6 = 1.67. Next, the node with the highest weight  is selected as an initial cluster. Node 2, as node 1's neighbor, satisfies the weight constraint to be included into the cluster because w (2) = 3 ≥ (1 – wT) × w (1). Here wT is a threshold for cluster formation that is set as 0.2 by default. Similarly, nodes 3 and 8 are also added into this cluster and finally MCODE predicts {1, 2, 3, 8} as a protein complex. Subsequently, {4, 5, 6, 7} is detected as another putative protein complex from this sample PPI graph.r et al.  is one owith k=2 ,29 and dThe experimental results of MCODE method showed that the number of predicted complexes is generally small and the size of many predicted complexes is often too large.Clique.					 Spirin and Mirny [nd Mirny  proposedMCL. Markov Clustering (MCL) [ng (MCL) ,31 can ang (MCL) , MCL is ng (MCL) -36.LCMA.					 Instead of adopting the over-constraining full cliques as the basis for protein complexes, Li et al. [i et al.  devised i et al.  describeDPClus. Amin et al. [n et al.  proposedPCP. Chua et al. [a et al.  proposeda et al.  to evalua et al.  and a paHub Duplication.						 Ucar et al. [r et al.  developer et al. ) are firCFinder. Adamcsek et al. [k-clique percolation clusters as functional modules using a Clique Percolation Method [k-clique is a clique with k nodes and two k-cliques are adjacent if they share (k – 1) common nodes. A k-clique percolation cluster is then constructed by linking all the adjacent k-cliques as a bigger subgraph.k et al.  providedn Method . In partSCAN.						Mete et al. [e et al.  proposede et al. . SCAN fiGS. Navlakha et al. [a et al.  applied a et al.  to clustCMC. Liu et al. [u et al.  recentlyu et al. . CMC theu et al. . TherefoProteins which interact with each other can be expected to be activated and repressed under the same conditions. In other words, interacting proteins are likely to exhibit similar gene-expression profiles. In fact, gene expression data has been widely exploited to annotate protein functions (guilt by association) and predict novel protein-protein interactions -52. We dGFA. Feng et al. [G = , two different density definitions as shown in equation (3) are used:g et al.  proposedw (v ) is the weight of the protein v weighted by –expressionev )  is the log fold change of v's gene-expression profile. GFA first applies DSA (Densest Subgraph Algorithm) [where gorithm)  to find DMSP. Maraziotis et al. [s, its neighbors and even its indirect neighbors are iteratively included based on different criteria to form the module.s et al.  developeMATISSE. Ulitsky et al. [k neighbors with the highest weights are picked to form a set of (k + 1) seeds. Last, after selecting the seeds, Jointly Active Connected Subnetworks (JACS) are obtained by several operations . Two small JACSs are merged to form a new one if they are closely connected.y et al.  also proFunctional information can also be incorporated to accurately detect protein complexes. Since proteins within the same protein complex are generally aggregated to perform a common function, the functional enrichment of a cluster can be used to indicate its tendency to be a real complex. The reliability of interactions, evaluated by the consistency of functional similarity between two proteins, can also help to provide cleaner PPI data for protein complex detection.RNSC. King et al. [g et al.  proposedDECAFF. Li et al. [i et al.  proposedi et al.  are procSWEMODE. Lubovac et al. [c et al.  presentec et al. -62. Secoc et al. .STM. Cho et al. [o et al.  extendedo et al.  to identet al. [The techniques discussed above have used pairwise physical interactions detected by high-throughput experiments such as Y2H as the PPI dataset for detecting protein complexes. More recently, there are some researchers who attempt to detect protein complexes from interaction data obtained solely from TAP experiments. Unlike Y2H method which detects direct physical interactions, using TAP data requires careful weighing of the detected links as TAP also detects indirect interactions in protein complexes. Krogan et al.  were oneet al. ,31 is thet al. [Caroline et al.  proposedet al. ,31 is apet al. [et al. [Pu et al.  also appet al. . Similar [et al.  used altet al. [G =  where U and V represent the sets of baits and preys respectively and E describes the bait-prey relationships detected in the experiments as shown in Figure Recently, Geva et al.  proposedIn this section, we review a number of emerging techniques for protein complex detection that are different from the application of traditional graph clustering described in the previous section.The previous graph clustering methods described above are unsupervised and are more or less based on the basic assumption that dense subgraphs in PPI networks are likely to be protein complexes. The protein complexes detected by many of these methods must be either cliques or defective cliques ,67 or aret al. [Qi et al.  proposedTo obtain the training data, they collect available known protein complexes and also generate some random subgraphs as non-complexes. Topological and biological properties of these training graphs are then summarized as features. A probabilistic Bayesian network (BN) is then applied to integrate all these features and the parameters of this BN model are learned from the training data.Given a graph candidate and its corresponding features, a log likelihood ratio score can thus be calculated by the BN model to show whether it is qualified to form a complex. A simulated annealing search  is furthIn the previous section, we have mentioned that some researchers have explored the use of TAP data instead of Y2H data for complex detection. However, as TAP does not detect direct pairwise protein-protein interactions (unlike Y2H), the PPI networks constructed using TAP data are not ideal for detecting protein complexes. Recently, several techniques are proposed to directly detect protein complexes from the TAP data without constructing the PPI networks.et al. [Rungsarityotin et al.  applied et al. [Z, where each entry ijz indicates that the thi  protein is in the complex j . The prior distribution of Z is learned from an infinite latent feature model. By considering the pairwise similarity between proteins obtained by a graph diffusion kernel [Z is further inferred to indicate the protein complex memberships by the Gibbs sampling.Chu et al.  used a Bn kernel , the posTwo adjacent interactions (those with a common protein) may be mutually exclusive ,74 due tet al. [Jung et al.  recentlyet al.  and LCMAet al.  to generet al. [Jin et al.  exploiteWith the increasing availability of PPI data for most species , it has become feasible to use cross-species analysis to derive insights into the evolution of the PPI networks for complex detection.et al. recently proposed a series of methods for comparative analysis in two or more species. They used these methods for conserved pathway detection [Sharan etection , proteinetection  and consetection -80. Basiu, v ) in the orthology graph is weighted by the sequence similarity between the protein pair u and v . An edge , ) is associated with a pair of weights , w ), where w  is the weight of the interaction . Two models, the protein-complex model and null model, are proposed to learn the weights of interactions and detect protein complexes in each species. In [In , each nocies. In , the rescies. In . A subgrcies. In .QNet was developed for queries in PPI networks. The similarity between two graphs is defined based on the node and edge similarity and the penalty scores for node deletion and insertion. QNet then performs tree queries and bounded-treewidth graph queries by the color coding algorithm [In , a tool lgorithm . Conservet al. [Another group of researchers, Dutkowski et al.  also proet al. [In the genome-wide screen for protein complexes using affnity purification and mass spectrometry  reportedet al. , they obet al. .et al. [Zhang et al.  proposedet al.  and someet al. [Recently, Leung et al.  proposedet al. [To provide insights into the organization of protein complexes, Wu et al.  presentsThe ability to detect overlapping cores is essential to understand how different cores are organized into the higher-level structures in PPI networks and how these cores communicate with each other to perform cellular functions. It also facilitates better detection of protein complexes from PPI networks, which will be shown in the evaluation results in the next section.Before we present the results of our comparative experiments, let us first introduce the various evaluation metrics that have been used to evaluate their computational methods for complex detection. We will then present the experimental results of comparing different state-of-the-art techniques using these evaluation metrics.Overall, there are three types of evaluation metrics used to evaluate the quality of the predicted complexes and compute the overall precision of the prediction methods.NA  between a predicted complex p =  and a real complex b =  in the benchmark complex set, as defined in equation (4) below, can be used to determine whether they match with each other. If NA  ≥ ω , they are considered to be matching . Let P and B denote the sets of complexes predicted by a computational method and real ones in the benchmark, respectively. Let cpN be the number of predicted complexes which match at least one real complex and cbN be the number of real complexes that match at least one predicted complex. Precision and Recall are then defined as follows: [Precision, recall and F-measure are commonly-used evaluation metrics in information retrieval and machine learning. For evaluating protein complex prediction, we need to define how well a predicted complex which consists of a set of protein members, matches an actual complex, which is another set of protein members. The neighborhood affnity score follows: ,66,87 :, positive predictive value (PPV ) and accuracy (Acc ) have also been proposed to evaluate the accuracy of the prediction methods [n benchmark complexes and m predicted complexes, let ijT denote the number of proteins in common between thi  benchmark complex and thj  predicted complex. Sn and PPV are then defined as follows:Recently, sensitivity  functional annotations. The statistical significance of the occurrence of a protein cluster (predicted protein complex) with respect to a given functional annotation can be computed by the following hypergeometric distribution in equation (9) ,89:(9)C contains k proteins in the functional group F and the whole PPI network contains |V | proteins. The functional homogeneity of a predicted complex is the smallest p-value over all the possible functional groups. A predicted complex with a low functional homogeneity indicates it is enriched by proteins from the same function group and it is thus likely to be true protein complex. By setting a common threshold which specifies the acceptable level of statistical significance, the numbers of predicted complexes with functional homogeneity under this threshold for the various methods can then be used for evaluating their respective overall performance.where a predicted complex Sn ), positive predictive value (PPV ) and Accuracy (Acc ). For sensitivity (Sn ), if a method predicts a giant complex which covers many proteins in the known real complex set, then this method will get a very high Sn score. As for PPV value (PPV ), it does not evaluate overlapping clusters properly. Here is a case in point: if the known gold standard MIPS complex set (with proteins that belong to multiple complexes) [PPV value is 0.772 instead of 1 (indicating an imperfect match) while the Precision and Recall are both correctly 1. As such, the Accuracy (Acc ) score, as the geometric average of Sn and PPV , will also not make good sense. In addition, all the evaluation metrics described above assumed that a complete set of true protein complexes is available, where in reality we are far from it. If a method predicts an unknown but real protein complex (which is not similar with any of the known complexes), all of these evaluation metrics will regard it as a false positive. Furthermore, for P-values, since its calculation relies on the availability of the proteins' functional information, its applicability would be limited in the less studied genomes. As such, so far it has mainly been used in the model organism yeast for which rich molecular functional information is available.It is important to realize that the evaluation metrics described above can only provide us some sense of how well the current graph mining techniques can be used to detect the protein complexes from protein interaction data. These metrics are by no means  absolute measures — they all have their own limitations, especially for sensitivity (mplexes)  is takenRelatively speaking, the Precision, Recall, F-measure and P-values are thus more acceptable for evaluating the performance of current techniques. Still, we need to treat the current evaluation metrics with caution, as more research is needed to come up with a robust evaluation metric for the protein complex prediction task.For this review, we have performed extensive experiments to compare the existing techniques for which we are able to obtain the software implementations — either source codes or binary executable systems. Those existing techniques that do not provide available software are not included in the comparison exercise. Fortunately, we have a good representative collection of implemented algorithms for comparison: MCODE , RNSC 5, MCL 3131, DPCluω is set as 0.20 to evaluate if a predicted complex matches with a gold standard protein complex (see equations (4) and (5)).In order to evaluate the predicted complexes, the set of real complexes from  was seleWe have compared these techniques over two publicly available benchmark yeast PPI datasets, namely DIP data  and KrogcpN) and the number of real complexes that match at least one predicted complex cbN. Taking MCODE on DIP data as an example, it has predicted 50 complexes, of which 44 match 21 real complexes. These 50 predicted complexes cover 844 proteins out of 4930 proteins in DIP. As shown in these two tables, MCL and RNSC assigned every protein (4930) into its predicted complexes as long as they are present in PPI networks  while all the other methods only assigned those highly interactive proteins (or the proteins that occurred in the dense subgraphs) into the predicted complexes. In fact, both MCL and RNSC basically partitioned the PPI network simultaneously into non-overlapping clusters while the remaining approaches are more sensible by generating clusters in a one-by-one manner and allowing overlaps in the clusters/complexes. We also noticed that for DECAFF algorithm the number of predicted complexes that matches at least one real complex (cpN) is significantly higher than the other methods — this is mainly because it is designed to search many dense and possibly overlapping complexes from the PPI networks.Tables Figures http://db.yeastgenome.org/cgi-bin/GO/goTermFinder.pl). The complexes with only one protein are discarded because calculating P-values for those complexes makes no sense according to the equation (9). We considered a predicted complex with a corrected P-value ≤ 0.01 to be statistically significant. The results showed that MCODE was able to obtain the highest proportion of significant complexes.Figure Unfortunately, this was an artefact of its predicting very few complexes as compared to all the other methods. Ignoring MCODE, then COACH and DECAFF have both achieved decent proportions of their predicted complexes as significant. As for DPClus, MCL and RNSC, because they predicted many protein complexes with extremely small size  which resulted in large P-values since they could occur by chance. For CORE, it generated many protein-complex cores with only one protein. Given such a core with one protein, CORE can only form a protein complex by including all the interacting partners of the protein as attachment. These protein complexes have low statistical significance, leading to the low performance of CORE.en masse have already become routine in the laboratories for generating large datasets of protein interaction data , while the high-throughput technologies for detecting protein complexes remained relatively immature. Hence computational approaches for detecting protein complexes are needed to help fill up the relatively empty map for the protein "complexome".Identifying protein complexes is important for biological knowledge discovery since many important biological processes in the cell are carried out through the formation of protein complexes. However, there is currently a wide gap between data on protein complexes and (pairwise) protein-protein interactions. High throughput technologies for detecting pairwise protein-protein interactions In this paper, we have reviewed current computational approaches that have been proposed to exploit the abundant protein interaction data to bridge the data gap for protein complexes. Protein interaction graph mining algorithms that identify graphical subcomponents in the protein-protein interaction networks can be used for predicting protein complexes. We have surveyed the state-of-the-art algorithms by describing the traditional graph clustering methods as well as the recent emerging techniques for computational detection of protein complexes from PPI and other data sources. Table On the other hand, our results also show that more further research is needed to improve these methods. In the following discussions, we describe three key challenges for further improvements .The computational methods are highly dependent on the quality of the underlying interaction data. Unfortunately, despite the abundance of PPI data, the data quality of these data still leaves much to be desired. For example, the experimental conditions in which the PPI detection methods are carried out may cause a bias towards detecting interactions that do not occur under physiological conditions, resulting in false positive detection rates that could be alarmingly high . At the PPI networks are very large graphs with thousands of vertices and tens of thousands of edges, even for a simple organism such as yeast. For the more complicated species such as the human being, the scale and complexity of the PPI networks are clearly overwhelming. Graph mining on the PPI networks is certain to test the limits of any computational methods. The fact that many graph-based problems, such as subgraph isomorphisms ,100 and Through integrating various independently obtained biological evidences, we can assess/weight the protein interactions by using appropriate confidence measures. For example, we can employ metrics from biological evidences such as reproducibility of the interactions from multiple experimental methods, support from such other non-interaction data as co-expression, co-localization and shared functions, as well as the conservation of the protein interactions across other genomes, etc to address the limitations in the current quality of PPI data. Computational methods, such as Bayesian network models  and kernFrom this review, it is clear that researchers have been tireless in devising new computational approaches for detecting protein complexes. It is indeed heartening that our evaluation results have showed that the proposed methods have generally improved in performance over the years. In time, we will be able to fill up the currently rather empty map of the complexome with combined efforts  from biologists as well as computational scientists computational scientists.The authors declare that they do not have any competing interests.XL and MW drafted the manuscript together. MW was responsible for performing experiments to compare the existing techniques. CKK and SKN participated in discussion and conceptualization as well as revising the draft. All authors have read and approved the manuscript.


Sir,et al. reported two male cousins from a consanguineous family.[Megarbane s family. In theirs family. is the os family..Waardenburg syndrome (WS) is a rare autosomal-dominant condition characterized by sensory/neural hearing loss, pigmentary abnormalities of the skin, hair, and eyes, and craniofacial anomalies. Our patiet al.[et al.[CHARGE syndrome was first described in 1979 by Hall et al. in 17 chl.[et al. proposedl.[et al.6 Our patAnother rare condition that could be considered in the differential diagnosis is Al Frayh-Anophthalmia, microcephaly, hypogonadism, MR syndrome. Al Frayh and Haque describeLenz syndrome is a rare X-linked recessive condition first reported by Lenz. All affeAlthough our patient has not skeletal malformations and inheritance of this case is uncertain, other many features thinking Megarbane syndrome. We described this case as a second Megarbane syndrome paper to the literature.


The Golden Spike data set has been used to validate a number of methods for summarizing Affymetrix data sets, sometimes with seemingly contradictory results. Much less use has been made of this data set to evaluate differential expression methods. It has been suggested that this data set should not be used for method comparison due to a number of inherent flaws.We have used this data set in a comparison of methods which is far more extensive than any previous study. We outline six stages in the analysis pipeline where decisions need to be made, and show how the results of these decisions can lead to the apparently contradictory results previously found. We also show that, while flawed, this data set is still a useful tool for method comparison, particularly for identifying combinations of summarization and differential expression methods that are unlikely to perform well on real data sets. We describe a new benchmark, AffyDEComp, that can be used for such a comparison.We conclude with recommendations for preferred Affymetrix analysis tools, and for the development of future spike-in data sets. The issue of method validation is of great importance to the microarray community; arguably more important than the development of new methods . The micPerhaps the most well-known and widely used benchmark for Affymetrix analysis methods is Affycomp . This is1. It uses data sets which only have a small number of DE spike-in probesets.2. It only uses fold change (FC) as a metric for DE detection, and hence cannot be used to compare other competing DE methods.More recently, the MicroArray Quality Control (MAQC) study  has deveet al.   et al. [ [et al.  has sugget al. [Irizarry et al.  detail t1. Spike-in concentrations are unrealistically high.2. DE spike-ins are all one-way (up-regulated).3. Nominal concentrations and FC sizes are confounded.While we agree that these are indeed undesirable characteristics, and would recommend the creation of new spike-in data sets that do not have these characteristics, we do not believe that these completely invalidate the use of the Golden Spike data set as a useful comparison tool.et al. [et al. [Perhaps more serious is the artifact identified by Irizarry et al. . They sh [et al.  have recet al. [et al. [et al. [et al. [et al. [et al. [The Golden Spike data set has been used to validate many different methods for summarizing Affymetrix data sets. Choe et al.  originalet al. , GCRMA [et al.  and MBEIet al. . Liu et  [et al.  used the [et al.  can outp [et al.  used the [et al. . Chen et [et al.  used the [et al. , FARMS a [et al. . All of et al. [et al. [The reason for the differing results arise from the different choices made at various stages of the analysis pipeline. In particular, different DE methods have been used in the papers cited above. Only Choe et al.  and Liu  [et al.  have com [et al.  and Cybe [et al. ; and the [et al. . In addiet al. [1. Summary statistic used . Note that Choe et al.  broke thet al. [2. Post-summarization normalization method. Choe et al.  comparedet al. [3. Differential expression (DE) method. Choe et al.  comparedet al.  and SAM et al. .et al. [4. Direction of differential expression. Choe et al. [5. Choice of true positives. Choe et al.  used allet al. [6. Choice of true negatives. Choe et al.  used allet al. [et al. [et al. [et al. paper [et al. paper [Table et al. , Hochrei [et al.  and Chen [et al.  papers. l. paper . There al. paper  that we l. paper  use diffThe most commonly used metric for assessing a DE detection method's performance is the Area Under the standard ROC Curve (AUC). This is typically calculated for the full ROC chart , but can also be calculated for a small portion of the chart (e.g. FPRs between 0 and 0.05). Other metrics that might be used are the number or proportion of true positives for a fixed number or proportion of false positives, or conversely the number or proportion of false positives for a fixed number or proportion of true positives.In this study we have analyzed all combinations of the various options shown in the last row of Table et al. [et al. [et al. [We can see from Table et al. . Figure  [et al. . This ap [et al. . There wThe choice of whether 1-sided or 2-sided tests should be used for comparison of methods is debatable. A 1-sided test for down-regulation is clearly not a sensible choice given that all the known DE genes are up-regulated. We would expect a 1-sided test of up-regulation to give the strongest results, given that all the unequal spike-ins are up-regulated. However, in most real microarray data sets, we are likely to be interested in genes which show the highest likelihood of being DE, regardless of the direction of change. As such, we will continue to use both a 2-sided test, and a 1-sided test of up-regulation in the remainder of the paper. In our comprehensive analysis, however, we also include results for 1-sided tests of down-regulation for completeness.Figure et al. [et al. [et al. [Irizarry et al.  showed t [et al. ), these  [et al. , leads uet al. [et al. [Thus far, we have not considered the effect of post-summarization normalization, which was shown by Choe et al.  to have  [et al. . Furtheret al. should not have included the empty null probesets". As such, for the remainder of this paper will we not use the empty probesets in loess normalization. In our comprehensive analysis we also include, for completeness, results when using all of the following post-summarization normalization strategies: no post-summarization normalization, a loess normalization based on all spike-in probesets, a loess normalization based on all the unchanging probesets and a loess normalization based on the equal-valued spike-ins.We agree with Gaile and Miecznikowski  that "thWe turn now to the issue of DE detection methods. Figure The end goal of an analysis is often to identify a small number of genes for further analysis. As such, we might be interested not in how well a method performs on the whole of a data set, but specifically in how well it performs in identifying those genes determined to be most likely to be DE. As such we are particularly interested in the ROC chart at the lowest values of FPR. Figure Figure So far we have used all of the genes that are spiked-in at higher concentrations in the S samples relative to the C samples as our true positives. This is perhaps the best and fairest way to determine overall performance of a DE detection method. However, we might also be interested in whether certain methods perform particularly well in "easier" or "more difficult" cases. Indeed, many analysts are only interested in genes which are determined not only to have a probability of being DE that is significant, but also have a FC which is greater than some pre-determined threshold. In order to determine which methods perform more strongly in "easy" or "difficult" cases, we can restrict our true positives to just those genes than are known to be DE by just a small FC, or to those that are very highly DE.Figure We have created ROC charts for each combination of analysis choices from the final row of Table 1. AUC where equal-valued spike-ins are used as true negatives, spike-ins with FC > 1 are used as true positives, a post-summarization loess normalization based on the equal-valued spike-ins is used, and a 1-sided test of up-regulation is the DE metric. This gives the values shown in Table 2. as 1. but using a 2-sided test of DE. This gives the values shown in Table 3. as 1. but with low FC spike-ins used as true positives. This gives the values shown in Figure 4. as 1. but with medium FC spike-ins used as true positives. This gives the values shown in Figure 5. as 1. but with high FC spike-ins used as true positives. This gives the values shown in Figure 6. as 1. but with all unchanging probesets used as true negatives.7. as 1. but with all unchanging probesets used as true negatives, and a post-summarization loess normalization based on the unchanging probesets.8. as 1. but with a post-summarization loess normalization based on all spike-in probesets.9. as 1. but with a no post-summarization normalization.10. as 1. but giving the AUC for FPRs up to 0.01.11. the proportion of true positives without any false positives (i.e. the TPR for a FPR of 0), using the same conditions as 1.12. the TPR for a FPR of 0.5, using the same conditions as 1.13. the FPR for a TPR of 0.5, using the same conditions as 1.We are happy to include other methods if they are made available through Bioconductor packages. We also intend to extend AffyDEComp to include future spike-in data sets as they become available. In this way we expect this web resource to become a valuable tool in comparing the performance of both summarization and DE detection methods.et al. [One of the main problems with comparing different analyses of the same data sets is knowing exactly what code has been used to create results. As an example, the loess normalization used in a number of the papers shown in Table et al.  have mad1. provide full details of all parameter choices used in the papers Methods section, or2. make the code used to create the results available, ideally as supplementary information to ensure a permanent record.We recommend that journals should not accept method comparison papers unless either of these is done. This paper was prepared as a "Sweave" document . The souet al. [We have performed the most comprehensive analysis to date of the Golden Spike data set. In doing so we have identified six stages in the analysis pipeline where choices need to be made. We have made firm recommendations about the choices that should be made for just one of these stages if using the Golden Spike data for comparison of summarization and DE expression detection methods using ROC curves: we recommend that only the probesets that have been spiked-in should be used as the true negatives for the ROC curves. By doing this we overcome the problems due to the artifact identified by Irizarry et al. . We woul1. The use of a post-summarization loess normalization, with the equal spike-in probesets used as the subset to normalize with. This is also recommended by Gaile and Miecznikowski .2. The use of a 1-sided test for up-regulation of genes between the C and S conditions. This mimics the actual situation because all the non-equal spike-ins are up-regulated.3. The use of all up-regulated probesets as the true positives for the ROC chart.Using the above recommendations, we created ROC charts for all combinations of summarization and DE methods Figure . This shIt should be noted that the design of this experiment could favor certain methods. We have seen that the intensities of the spike-in probesets are particularly high. Estimates of expression levels are known to be more accurate for high intensity probesets. This could favor the FC method of determining DE.Furthermore, the replicates in the Golden Spike study are technical rather than biological, and hence the variability between arrays might be expected to be lower in this data set than in a typical data set. Again, this might favor the FC DE method.et al. [We agree with Irizarry et al.  that theWe encourage the community to develop further spike-in data sets with large numbers of DE probesets. In particular, we encourage the generation of data sets where:1. Spike-in concentrations are realistic2. DE spike-ins are a mixture of up- and down-regulated3. Nominal concentrations and FC sizes are not confounded4. The number of arrays used is large enough to be representative of some of the larger studies being performed todayet al. [We believe that only by creating such data sets will we be able to ascertain whether the artifact noted by Irizarry et al.  is a pecet al. [ affy package (version 1.16.0). GCRMA expression measures were created using the Bioconductor gcrma package (version 2.10.0). PLIER expression measures were created using the Bioconductor plier package (version 1.8.0). multi-mgMOS expression measures were created using the Bioconductor puma package (version 1.4.1). FARMS expression measures were created using the FARMS package (version 1.1.1) from the author's website [affy package and code from the author's website [goldenspike package (version 0.4) [puma package (version 1.4.1).The raw data from the Choe et al.  study waet al. . All anaet al.  affy pac website . DFW exp website . Cyber-Tion 0.4) . All othThe code used to create all results in this document is included as Additional file DE – differentially expressed or differential expression, as appropriate. FC – fold change. MAQC -MicroArray Quality Control. ROC – receiver-operator characteristic. FPR – false-positive rate. TPR -true-positive rate. FDR – false-discovery rate. AUC – area under curve (in this paper this refers to the area under the ROC curve).RDP designed the study, performed all analysis, developed the AffyDEComp website, and wrote the manuscript.Source code used to create this paper and AffyDEComp. This is a zip file containing R and Sweave code. Sweave code is a text document which contains both LaTeX and R code, and as such can be used to recreate exactly all the results in this paper using open source tools. Also included is R code to recreate all the charts available through AffyDEComp. See the README file for further details.Click here for file


Hypospadias is a highly prevalent congenital anomaly. The impact of the defect and operative interventions on sexual and reproductive function has been addressed by few publications. It is essential to know the possible outcomes of intervention for appropriate counseling, operative planning, and follow-up. English articles indexed in Pubmed dealing with the long-term sexual and reproductive outcome following hypospadias repair from 1965 to 2007 were reviewed. To our knowledge, there was no prospective trial comparing the impact of various techniques on sexual outcome. There is considerable discordance in literature regarding the effects on sexual function. A few publications report patient and partner dissatisfaction with the appearance of genitalia. Sexual dissatisfaction is often attributed to penile size. Ejaculatory disturbances range between 6 and 37% of operated individuals. There is no convincing evidence for impaired fertility. The long-term follow-up is essential to identify problems and to address them appropriately. Literature documenting the outcome of specific operative procedures and analysis based on severity of hypospadias will be informative. The long-term follow-up of the newer techniques which are more commonly used are awaited. In hypospadias, the inherent difficulties to reconstruct the urethra, straighten the penis, and to restore the appearance of the penis are evident from the number of techniques and modifications described in the literature. However, the impact of the deformity extends beyond the realms of a structural defect, by virtue of the diverse functions of the penis. To counsel parents and patients appropriately, it is essential to know the effect on sexual function and reproduction. Literature on the long-term outcome, impact on sexual function and reproduction continues to be sparse. We reviewed the published literature on the sexual and reproductory outcome of hypospadias.et al.[P = 0.809). The single reason for dissatisfaction in hypospadias group was smaller penile size. Mureau et al.[et al.[et al.[Publications on the psychological, social, and sexual development of patients operated on for hypospadias are still rare and the results are somewhat discordant. The possible explanations for these discrepancies are mainly methodological, with too small series, low rates of response to questionnaires, study populations of different ages and above all the absence of a control group, which prevents any comparison of the results with those of a reference population. Another et al. observedau et al. interviel.[et al. used a gl.[et al. observedet al.[et al.[et al.[et al.[Berg et al. in the el.[et al. comparedl.[et al. assessedl.[et al. comparedet al.[et al.[Sexual sensation has not been well documented in most articles. Bubanj et al. noted thl.[et al. noted thet al.[et al.[P < 0.05) and those with complications had been more often ridiculed than those in the distal group and those without complications . In a comparative study, Mureau et al.[The social and sexual life of adults operated for hypospadias during childhood has been studied by a few authors. Aho et al. comparedl.[et al. observedau et al. comparedet al. observed that though the frequency of intercourse during 4 weeks was significantly lesser for those who were operated for hypospadias, there were no significant difference between patients with hypospadias and controls regarding inhibition in seeking sexual contacts or patterns of sexual relationships. Those with distal hypospadias were more satisfied with their sexual life.[et al. noted that the commonest sexual complaints included short penis, increased curvature, painful erection, and no erection. The erectile problems were more in those who had proximal hypospadias.[et al.[et al.[et al. They noted that the long-term sexual function and satisfaction were excellent, in spite of them having undergone multiple procedures.[et al.[et al. noted that 10 out of 25 who underwent re-operation for hypospadias had recurrence of chordee.[et al. followed up patients following hypospadias repair after puberty. They found that higher number of study patients had ventral curvature during erection (40% vs. 18%) compared to controls.[The erectile problems in hypospadias may be attributed to surgically correctable and noncorrectable causes. More commonly encountered correctable causes include persistent chordee, torsion, inadequate cosmetic outcome, etc. Commonest surgically uncorrectable cause is the size of the penis. Achieving a straight penis is one of the objectives of hypospadias correction. With a constant move toward achieving a normal-looking penis, the results of contemporary repairs are likely to be different. Sommerlad reviewedual life. Of the 7ospadias. They alss.[et al. studied l.[et al. Zaontz iocedures. The longs.[et al. Six of t chordee. Bubanj econtrols. This undcontrols. With a det al.[et al.[et al.[et al.[Inability to achieve satisfactory ejaculation is documented in almost all publications. Reported incidence ranges from 6 to 37%. Problems reported include weak or dribbling ejaculation, having to milk out ejaculate after orgasm, quantity of semen passing after intercourse, anejaculation with or without orgasm, etc. Liu et aet al. observedl.[et al. assessedl.[et al. documentl.[et al. studied l.[et al. whether et al. found that men who had hypospadias during childhood were less likely to live with a partner and that they had fewer children (0.8 vs. 1.1).[Literature is scant on the fertility of men who had hypospadias. Aho vs. 1.1). The diffvs. 1.1). Of the 3vs. 1.1).5Genital perception is mostly unaffected, especially in those with distal hypospadias operated in childhood. An adverse effect on sexual life has been noted, but the results are discordant. Disturbance in sexual performance seems to be attributed to small penile size. Ejaculatory disturbance has been noted in almost all series. There is no convincing evidence for impaired fertility. The operative procedures based on which these studies were conducted have mostly been replaced by modern techniques which are more anatomical. Furthermore, the operations are being performed at an earlier age. When hypospadias reconstruction is performed in early childhood, it essential to keep in mind the possible long-term sexual and reproductive implications and to choose options that are least likely to impair sexual and reproductive functions. The long-term follow-up of newer operative techniques are awaited. Evaluation of psychosexual, erectile, ejaculatory and reproductive function of specific techniques, and for varying degrees of hypospadias will give a better idea of the outcome of various procedures. Using a validated objective scoring system will help compare the results of various techniques.


Intracranial vascular anomalies involving the middle cerebral artery (MCA) are relatively rare, as such knowledge will be helpful for planning the optimal surgical procedures.We herein present the first case of a ruptured internal carotid artery aneurysm arising at the origin of the hypoplastic duplicated MCA associated with accessory MCA and main MCA aplasia, which was revealed by angiograms and intraoperative findings.In practice, this case highlights the urgent need to preoperatively recognize such vascular anomalies as well as understand the collateral blood supply in cerebral ischemia associated with these MCA anomalies. Teal et al. establiset al.9 AlthougA 66-year-old female suffered a sudden onset of headache and a loss of consciousness. On admission, a computed tomography (CT) scan revealed a diffuse subarachnoid hemorrhage (SAH) with laterality on the right Sylvian fissure . A threeet al.[Intracranial vascular anomalies involving the MCA are relatively rare. Teal et al. establiset al.9 The coeet al.[6Uchino et al. diagnoseet al. However,et al.69 The caet al.[The embryologic explanation for anomalies and variations of the MCA remains unclear. The MCA develops after the ACA, and the ACA is considered a continuation of the primitive ICA. Thus, the MCA can be regarded as a branch of the ACA. Embryoloet al. suggesteet al.[The association between the dup-MCA, or the acc-MCA, and cerebral aneurysms has been well documented.8 Howeveret al. reported


We aimed to provide a summary of the existing published knowledge on the association between adverse birth outcomes and the development of wheezing during the first two years of life. We carried out a systematic review of epidemiological studies within the MEDLINE database. Epidemiological studies on human subjects, published in English, were included in the review. A comprehensive literature search yielded 72 studies for further consideration. Following the application of the eligibility criteria we identified nine studies. A positive association and an excess risk of wheezing during the first two years of life were revealed for adverse birth outcomes. Prem2.A systematic review of the existing literature on adverse birth outcomes related and wheezing was carried out. We posed the following review question: “Given the existing epidemiological evidence, is there a link between adverse birth outcomes and the occurrence of wheezing during the first two years of life?”. We drew up a review protocol in advance following standards outlined in the MOOSE Guidelines for Meta-Analyses and Systematic Reviews of Observational Studies . We carrSearch terms used were chosen from the USNLM Institutes of Health list of Medical Subject Headings (MeSH) for 2007. These were: “Infant, Low Birth Weight” OR “Infant, Very Low Birth Weight” OR “Premature Birth” OR “Fetal Growth Retardation” OR “Infant, Extremely Low Birth Weight” AND “Respiratory Sounds”, OR “Signs and Symptoms, Respiratory” OR “Wheezing”. Although not officially MeSH terms, “Wheezing” and “Small for gestational age” was also added as key terms so as to broaden the scope of the search. Retrieved studies were checked against a list of eligibility criteria, while the references of each retrieved study were also checked by hand for additional studies that met the eligibility criteria.a priori eligibility criteria to restrict the studies included. Studies were only included if they referred to humans, were published in English after 1990, were epidemiological studies (of any study design) and they examined the presence of wheezing up to two years old. Studies not meeting these criteria were excluded from the review. Data were extracted systematically from each included study by two researchers separately using a standardized data extraction form. The following data were extracted from each study: study main characteristics, study population, study topic, and measures of effect and confidence intervals for each outcome.We defined 3.The main characteristics of the studies included in the analysis are given in et al. [et al. [et al. [et al. [et al. [et al.  used ges [et al.  gestatio [et al. , the <34 [et al.  and the  [et al. , respect [et al. ,26,32. H [et al.  was not  [et al.  while teAll studies examined wheezing as an outcome although the time period of wheezing presence was different. Four studies examined wheezing at first year of life ,26,30, fet al. [et al. [et al. [et al. [et al. [et al. [Four studies measured the outcome as an odds ratio ,29,31,32 [et al.  underlin [et al.  reportedet al. [et al. [et al. [The prevalence of wheezing was also estimated by five studies ,26,27,30et al.  in the t4.As indicated through this systematic review, we have gathered the existing epidemiological evidence in order to examine the possible association between adverse birth outcomes and the development of wheezing during early childhood. Furthermore we identified a positive association between adverse birth outcomes such as LBW, VLBW, PD, VPD and the development of wheezing during early childhood. No studies examining the association of term low birth weight and small for gestational age infants with wheezing were revealed and thus these outcomes were not further investigated into.Considerable variation in the prevalence of wheezing has been observed in previous studies. A prevalence increase has been noticed between countries and over time specifically from the 1970s up to the early 1990s . These dThere are many potential causes of wheezing including genetic/familial or environmental factors, and viral respiratory infections . GeneralThe majority of children who develop wheeze in early childhood are free of symptoms by adolescence or early adulthood ,37. In aEarly life events are important since the origin of airway abnormalities occurs early in infancy. Prospective birth cohort studies clarify the incidence of an illness by evaluating the risk factors and the possible confounders and/or modifiers related to the disease. This kind of studies may allow us to shed light on the primary factors that initiate wheezing and its correlation to long term implications such as chronic obstructive lung disease.Conclusively, this study area is of high importance due to the fact that long term implications are unknown. It is therefore desirable to determine the correlation between adverse birth outcomes and wheezing during early childhood and identify whether there are preventable or treatable risk factors. For the purpose of this study, review was restricted to wheezing as a health outcome while other important causes of wheezing during early childhood other than adverse birth outcomes  were not examined. As mentioned above, well designed epidemiological studies which will evaluate the relevant confounders and possible exposures and risk factors during pregnancy are needed. This estimation of summary should be considered by epidemiologists, health care specialists and research community as the most interesting areas for further research work.


The most important and widely utilized system for providing prognostic information following surgical management for renal cell carcinoma (RCC) is currently the tumor, nodes, and metastasis (TNM) staging system. An accurate and clinically useful staging system is an essential tool used to provide patients with counseling regarding prognosis, select treatment modalities, and determining eligibility for clinical trials. Data published over the last few years has led to significant controversies as to whether further revisions are needed and whether improvements can be made with the introduction of new, more accurate predictive prognostic factors. Staging systems have also evolved with an increase in the understanding of RCC tumor biology. Molecular tumor biomarkers are expected to revolutionize the staging of RCC by providing more effective prognostic ability over traditional clinical variables alone. This review will examine the components of the TNM staging system, current staging modalities including comprehensive integrated staging systems, and predictive nomograms, and introduce the concept of molecular staging for RCC. Over 200,000 new cases of kidney cancer are diagnosed and more than 100,000 deaths occur from this disease each year globally. RCC is a37et al.[Anatomical criteria have traditionally been used to stage RCC. Flocks and Kadesky were theet al. later moet al.et al.[The primary size of the tumor is a key component of the TNM staging system and remains one of the most important prognostic factors for RCC.8 In 199712et al. attempteet al.–19 As a et al. Althoughet al.22et al.[et al.[Several investigators have attempted to further improve the prognostic accuracy of T2 tumors by stratifying based on size. Frank, et al. found thl.[et al. reportedet al.[et al.[et al.[et al.[A 5-year cancer-specific survival rate for T3 disease ranges from 37% to 67%, which reflects this broad category that includes various clinical situations that involve tumor extension beyond the renal capsule.26 Tumorset al. reportedl.[et al. reportedl.[et al.–31 Leibol.[et al. reportedl.[et al. reportedet al.[et al.[et al.[et al.[et al.[The role of tumor size in T3a tumors has attracted little attention in literature. Siemer, et al. analyzedl.[et al. reportedl.[et al. also repl.[et al. investigl.[et al. reportedet al.[4338A few patients presented with RCC involving the ipsilateral adrenal gland at the time of diagnosis.38 The cu39et al. Others het al.42 Severaet al.4344 CurrRCC invades the venous system in 4–9% of newly diagnosed patients.46 In 19947485455et al.[The overall risk of lymph node metastasis is approximately 20% and 5-year survival rates of patients with lymph node involvement ranges from 11–35%.–59 Howev57et al.[et al.[et al.[Although it has been specified since the 6th edition of the TNM classification that histological examination of a regional lymphadenectomy specimens should routinely include 8 or more lymph nodes, few studies have challenged the N1-N2 subclassification. Previous studies have focused on the number of lymph nodes that were required for accurate staging as well as the utility and extent of the lymphadenectomy. Terrone,et al. reportedl.[et al. analyzedl.[et al. examinedThe anatomical, histological, and clinical factors that influence disease recurrence and survival in RCC make counseling patients particularly challenging. Many centers have aimed to integrate these independent prognostic indicators into comprehensive outcome models for both non metastatic and metastatic RCC to assist clinicians in facilitating patient counseling and identifying those patients who might benefit from treatment. The first report addressing this issue appeared in 1986 in which the factors predicting outcome for patients with metastatic RCC included performance status (PS), presence of pulmonary metastases, and metastatic-free interval. More recet al.[vs. 2 to 3), time from initial diagnosis (>1 year vs. 1 year), number of metastatic sites, prior cytotoxic chemotherapy, and recent weight loss. The Karnofsky or ECOG-PS scales are a convenient common denominator for the overall impact of multiple objective and subjective symptoms and signs on patients. Using this system, median survival times ranging from 2.1 to 12.8 months were observed across the five separate categories. As this cohort was examined prior to the initiation of immunotherapy, its validity for today's patient population is questionable.Elson, et al. presenteet al.[Motzer, et al. developeet al.[To analyze prognostic factors that would benefit modern day clinical trials, Motzer, et al. reviewedvs. two or three sites), the MSKCC definitions of risk groups were expanded to accommodate these two additional prognostic factors. Using this expanded criteria, favorable-risk was defined as zero or one poor prognostic factor, intermediate-risk was defined as two poor prognostic factors, and poor-risk was defined as more than two poor prognostic factors.A study of 353 patients with previously untreated advanced RCC at the Cleveland Clinic was conducted to assess and validate the model proposed from MSKCC. Four of The International Kidney Cancer Working Group is currently establishing a comprehensive database from centers that treat patients with metastatic RCC. This will be used to develop a set of prognostic factors in patients with metastatic RCC and ultimately to derive a single validated model. Preliminary studies were performed to determine the availability of a database that could be used for the planned analysis of prognostic factors, which involved the examination of 782 patients treated by the Groupe Francais d'Immunotherapie and patiThe Kattan postoperative prognostic nomogram was creaThe UCLA integrated staging system (UISS) is an extensive prognostic system that has been created for both localized and metastatic RCC. The initThe Mayo Clinic created an extensive outcome prediction model for patients with clear cell RCC who are undergoing a radical nephrectomy. Accordin7981et al.[In the metastatic setting, it is well accepted that PS is a strong predictor for survival. Similarly, several studies have shown that cancer-related symptoms were independent prognostic parameters in localized RCC.–85 Recen8688et al. recentlyet al.[et al.[The presence of distant metastases at diagnosis substantially changes the prognosis of patients with RCC.92 Leibovet al. reportedl.[et al. recentlyet al.[et al.[The outcome of patients with RCC nodal metastases is substantially worse than that of patients with localized disease. Hutterer, et al. developel.[et al. demonstrin situ detection of DNA, RNA, and protein in the same set of specimens, which can be correlated to clinical data with respect to disease progression, treatment response, and survival. The evaluation of protein expression in a high-throughput TMA is a natural extension to the efforts for molecular staging. Accurate models for predicting survival can be constructed using multiple molecular biomarkers. Kim, et al.[Molecular biomarkers may prove more effective for predicting survival than traditional clinical parameters such as tumor stage and grade. The nextm, et al.103 have Two nomograms were proposed that could be used to predict disease-specific survival. One nomogram is based on metastasis status and molecular markers . The second nomogram combines clinical and molecular variables . By including metastasis status, the nomograms accurately predict cancer-specific survival in patients with both localized and metastatic RCC. Both nomograms can be used to calculate 2- and 4-year cancer-specific survival rates as well as median survival. This study shows that accurate models for molecular staging of a solid tumor can be developed using a very limited number of markers. Although these nomograms are useful for visualizing our predictive models, they need to be validated on independent patient populations prior to being applied to patient care.et al.[et al.[et al.[et al.[Gene expression analysis studies have also demonstrated the ability to define patient prognosis. Takahashi, et al. showed tl.[et al. also idel.[et al. reportedl.[et al. identifiOver the last 10 years, there has been a gradual transition from the use of solitary clinical factors as prognostic markers for patients with RCC to the introduction of systems that integrate multiple factors to the introduction of molecular and genetic markers with the goal of improving patient prognostication. The field of RCC is rapidly undergoing a revolution led by molecular biomarkers. The understanding of tumor biology gleaned from molecular biomarker research will be critical to the future treatment of patients with RCC.