Disparity between General Symptom Relief and Remission Criteria in the Positive and Negative Syndrome Scale (PANSS): A Post-treatment Bifactor Item Response Theory Model.

Objective: Total scale scores derived by summing ratings from the 30-item PANSS are commonly used in clinical trial research to measure overall symptom severity, and percentage reductions in the total scores are sometimes used to document the efficacy of treatment. Acknowledging that some patients may have substantial changes in PANSS total scores but still be sufficiently symptomatic to warrant diagnosis, ratings on a subset of 8 items, referred to here as the "Remission set," are sometimes used to determine if patients' symptoms no longer satisfy diagnostic criteria. An unanswered question remains: is the goal of treatment better conceptualized as reduction in overall symptom severity, or reduction in symptoms below the threshold for diagnosis? We evaluated the psychometric properties of PANSS total scores, to assess whether having low symptom severity post-treatment is equivalent to attaining Remission. Design: We applied a bifactor item response theory (IRT) model to post-treatment PANSS ratings of 3,647 subjects diagnosed with schizophrenia assessed at the termination of 11 clinical trials. The bifactor model specified one general dimension to reflect overall symptom severity, and five domain-specific dimensions. We assessed how PANSS item discrimination and information parameters varied across the range of overall symptom severity (θ), with a special focus on low levels of symptoms (i.e., θ<-1), which we refer to as "Relief" from symptoms. A score of θ=-1 corresponds to an expected PANSS item score of 1.83, a rating between "Absent" and "Minimal" for a PANSS symptom. Results: The application of the bifactor IRT model revealed: (1) 88% of total score variation was attributable to variation in general symptom severity, and only 8% reflected secondary domain factors. This implies that a general factor may provide a good indicator of symptom severity, and that interpretation is not overly complicated by multidimensionality; (2) Post-treatment, 534 individuals (about 15% of the whole sample) scored in the "Relief" range of general symptom severity, but more than twice that number (n = 1351) satisfied Remission criteria (37%). 2 in 3 Remitted patients had scores that were not in a low symptom range (corresponding to Absent or Minimal item scores); (3) PANSS items vary greatly in their ability to measure the general symptom severity dimension; while many items are highly discriminating and relatively "pure" indicators of general symptom severity (delusions, conceptual disorganization), others are better indicators of specific dimensions (blunted affect, depression). The utility of a given PANSS item for assessing a patient depended on the illness level of the patient. Conclusion: Satisfying conventional Remission criteria was not strongly associated with low levels of symptoms. The items providing the most information for patients in the symptom Relief range were Delusions, Preoccupation, Suspiciousness Persecution, Unusual Thought Content, Conceptual Disorganization, Stereotyped Thinking, Active Social Avoidance, and Lack of Judgment and Insight. Lower scores on these items (item scores ≤2) were strongly associated with having a low latent trait θ or experiencing overall symptom relief. The inter-rater agreement between Remission and Relief subjects suggested that these criteria identified different subsets of patients. Alternative subsets of items may offer better indicators of general symptom severity and provide better discrimination (and lower standard errors) for scaling individuals and judging symptom relief, where the "best" subset of items ultimately depends on the illness range and treatment phase being evaluated

Electronic health record phenotyping improves detection and screening of type 2 diabetes in the general United States population: A cross-sectional, unselected, retrospective study

Objectives: In the United States, 25% of people with type 2 diabetes are undiagnosed. Conventional screening models use limited demographic information to assess risk. We evaluated whether electronic health record (EHR) phenotyping could improve diabetes screening, even when records are incomplete and data are not recorded systematically across patients and practice locations. Methods: In this cross-sectional, retrospective study, data from 9,948 US patients between 2009 and 2012 were used to develop a pre-screening tool to predict current type 2 diabetes, using multivariate logistic regression. We compared (1) a full EHR model containing prescribed medications, diagnoses, and traditional predictive information, (2) a restricted EHR model where medication information was removed, and (3) a conventional model containing only traditional predictive information (BMI, age, gender, hypertensive and smoking status). We additionally used a random-forests classification model to judge whether including additional EHR information could increase the ability to detect patients with Type 2 diabetes on new patient samples. Results: Using a patient's full or restricted EHR to detect diabetes was superior to using basic covariates alone (p<0.001). The random forests model replicated on out-of-bag data. Migraines and cardiac dysrhythmias were negatively associated with type 2 diabetes, while acute bronchitis and herpes zoster were positively associated, among other factors. Conclusions: EHR phenotyping resulted in markedly superior detection of type 2 diabetes in a general US population, could increase the efficiency and accuracy of disease screening, and are capable of picking up signals in real-world records

Defining and distinguishing infant behavioral states using acoustic cry analysis: is colic painful?

BackgroundTo characterize acoustic features of an infant's cry and use machine learning to provide an objective measurement of behavioral state&nbsp;in a cry-translator. To apply the&nbsp;cry-translation algorithm to colic hypothesizing that these cries sound painful.MethodsAssessment of 1000 cries in a mobile app (ChatterBabyTM). Training a cry-translation&nbsp;algorithm by evaluating &gt;6000 acoustic features to predict whether infant cry was due to a pain (vaccinations, ear-piercings), fussy, or hunger states. Using the algorithm to predict the behavioral state of infants with reported colic.ResultsThe cry-translation&nbsp;algorithm was 90.7% accurate for identifying pain cries, and achieved 71.5% accuracy in discriminating cries from fussiness, hunger, or pain. The ChatterBaby&nbsp;cry-translation&nbsp;algorithm overwhelmingly predicted that colic cries were most likely from pain, compared to fussy and hungry states. Colic cries had average pain ratings of 73%, significantly greater than the pain measurements found in fussiness and hunger (p &lt; 0.001, 2-sample t test). Colic cries outranked pain cries by measures of acoustic intensity, including energy, length of voiced periods, and fundamental frequency/pitch, while fussy and hungry cries showed reduced intensity measures compared to pain and colic.ConclusionsAcoustic features of cries are consistent across a diverse infant population and can be utilized as objective markers of pain, hunger, and fussiness. The&nbsp;ChatterBaby algorithm detected significant acoustic similarities between colic and painful cries, suggesting that they may share a neuronal pathway

Fusarium: more than a node or a foot-shaped basal cell

Recent publications have argued that there are potentially serious consequences for researchers in recognising distinct genera in the terminal fusarioid clade of the family Nectriaceae. Thus, an alternate hypothesis, namely a very broad concept of the genus Fusarium was proposed. In doing so, however, a significant body of data that supports distinct genera in Nectriaceae based on morphology, biology, and phylogeny is disregarded. A DNA phylogeny based on 19 orthologous protein-coding genes was presented to support a very broad concept of Fusarium at the F1 node in Nectriaceae. Here, we demonstrate that re-analyses of this dataset show that all 19 genes support the F3 node that represents Fusarium sensu stricto as defined by F. sambucinum (sexual morph synonym Gibberella pulicaris). The backbone of the phylogeny is resolved by the concatenated alignment, but only six of the 19 genes fully support the F1 node, representing the broad circumscription of Fusarium. Furthermore, a re-analysis of the concatenated dataset revealed alternate topologies in different phylogenetic algorithms, highlighting the deep divergence and unresolved placement of various Nectriaceae lineages proposed as members of Fusarium. Species of Fusarium s. str. are characterised by Gibberella sexual morphs, asexual morphs with thin- or thick-walled macroconidia that have variously shaped apical and basal cells, and trichothecene mycotoxin production, which separates them from other fusarioid genera. Here we show that the Wollenweber concept of Fusarium presently accounts for 20 segregate genera with clear-cut synapomorphic traits, and that fusarioid macroconidia represent a character that has been gained or lost multiple times throughout Nectriaceae. Thus, the very broad circumscription of Fusarium is blurry and without apparent synapomorphies, and does not include all genera with fusarium-like macroconidia, which are spread throughout Nectriaceae (e.g., Cosmosporella, Macroconia, Microcera). In this study four new genera are introduced, along with 18 new species and 16 new combinations. These names convey information about relationships, morphology, and ecological preference that would otherwise be lost in a broader definition of Fusarium. To assist users to correctly identify fusarioid genera and species, we introduce a new online identification database, Fusarioid-ID, accessible at www.fusarium.org. The database comprises partial sequences from multiple genes commonly used to identify fusarioid taxa (act1, CaM, his3, rpb1, rpb2, tef1, tub2, ITS, and LSU). In this paper, we also present a nomenclator of names that have been introduced in Fusarium up to January 2021 as well as their current status, types, and diagnostic DNA barcode data. In this study, researchers from 46 countries, representing taxonomists, plant pathologists, medical mycologists, quarantine officials, regulatory agencies, and students, strongly support the application and use of a more precisely delimited Fusarium (= Gibberella) concept to accommodate taxa from the robust monophyletic node F3 on the basis of a well-defined and unique combination of morphological and biochemical features. This F3 node includes, among others, species of the F. fujikuroi, F. incarnatum-equiseti, F. oxysporum, and F. sambucinum species complexes, but not species of Bisifusarium [F. dimerum species complex (SC)], Cyanonectria (F. buxicola SC), Geejayessia (F. staphyleae SC), Neocosmospora (F. solani SC) or Rectifusarium (F. ventricosum SC). The present study represents the first step to generating a new online monograph of Fusarium and allied fusarioid genera (www.fusarium.org)

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival