The impact of visual dysfunctions in recent-onset psychosis and clinical high-risk state for psychosis

Subtle subjective visual dysfunctions (VisDys) are reported by about 50% of patients with schizophrenia and are suggested to predict psychosis states. Deeper insight into VisDys, particularly in early psychosis states, could foster the understanding of basic disease mechanisms mediating susceptibility to psychosis, and thereby inform preventive interventions. We systematically investigated the relationship between VisDys and core clinical measures across three early phase psychiatric conditions. Second, we used a novel multivariate pattern analysis approach to predict VisDys by resting-state functional connectivity within relevant brain systems. VisDys assessed with the Schizophrenia Proneness Instrument (SPI-A), clinical measures, and resting-state fMRI data were examined in recent-onset psychosis (ROP, n = 147), clinical high-risk states of psychosis (CHR, n = 143), recent-onset depression (ROD, n = 151), and healthy controls (HC, n = 280). Our multivariate pattern analysis approach used pairwise functional connectivity within occipital (ON) and frontoparietal (FPN) networks implicated in visual information processing to predict VisDys. VisDys were reported more often in ROP (50.34%), and CHR (55.94%) than in ROD (16.56%), and HC (4.28%). Higher severity of VisDys was associated with less functional remission in both CHR and ROP, and, in CHR specifically, lower quality of life (Qol), higher depressiveness, and more severe impairment of visuospatial constructability. ON functional connectivity predicted presence of VisDys in ROP (balanced accuracy 60.17%, p = 0.0001) and CHR (67.38%, p = 0.029), while in the combined ROP + CHR sample VisDys were predicted by FPN (61.11%, p = 0.006). These large-sample study findings suggest that VisDys are clinically highly relevant not only in ROP but especially in CHR, being closely related to aspects of functional outcome, depressiveness, and Qol. Findings from multivariate pattern analysis support a model of functional integrity within ON and FPN driving the VisDys phenomenon and being implicated in core disease mechanisms of early psychosis states.Subject terms: Predictive markers, Psychosis     

Machine learning approach to identify adverse events in scientific biomedical literature

Monitoring the occurrence of adverse events in the scientific literature is a mandatory process in drug marketing surveillance. This is a very time‐consuming and complex task to fulfill the compliance and, most importantly, to ensure patient safety. Therefore, a machine learning (ML) algorithm has been trained to support this manual intellectual review process, by automatically providing a classification of the literature articles into two types. An algorithm has been designed to automatically classify “relevant articles” which are reporting any kind of drug safety relevant information, and those which are not reporting an adverse drug reaction as “not relevant.” The review process is consisted of many rules and aspects which needed to be taken into consideration. Therefore, for the training of the algorithm, thousands of documents from previous screenings have been used. After several iterations of adjustments and fine tuning, the ML approach is definitively a great achievement in pre‐sorting the articles into “relevant” and “non‐relevant” and supporting the intellectual review process.

Study Highlights

• WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

Using machine learning (ML) to make decisions based on previous decisions is becoming more prominent in the digital world. However, to implement such a workflow in a very regulated field is a big challenge.

• WHAT QUESTION DID THIS STUDY ADDRESS?

To what extend is it possible to replace human decisions needing intellectual input by ML?

• WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

It shows that it is to a certain extent possible to detect drug safety‐related information to the drugs in focus in written text. Furthermore, it combines the methodologies to show which technical solutions are best.

• HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

Using ML in more and more processes will gain efficiency and will make drug discovery, drug development, and postmarketing surveillance more efficient and, most importantly, it will increase the patients’ safety.     

Head and neck squamous carcinomas with exophytic and endophytic type of growth have the same prognosis after surgery and adjuvant radiotherapy

Head and neck squamous cell carcinomas (HNSCC) are characterized by exophytic or endophytic growth. We hypothesized that the growth pattern predicts outcome and associates with distinct clinical and immunological profiles. Tumors obtained from 60 HNSCC patients treated with surgery and adjuvant radiotherapy were identified as exophytic or endophytic. Recurrence-free survival (RFS) at 42 months was determined. In a subsets of 30 patients (22 exophytic and 8 endophytic) tumor stroma and parenchyma were evaluated for infiltrating CD4⁺ and CD8⁺ T, dendritic, myeloid and FOXP3⁺ regulatory T cells (Treg) and expression of immunosuppressive cytokines by immunohistochemistry. The localization and frequency of positive cells were determined microscopically and analyzed by hierarchical clustering to distinguish exophytic versus endophytic tumors. 34/60 patients had exophytic and 26/60 endophytic tumors. No differences in clinicopathologic data, disease progression or RFS were seen between the two cohorts. Infiltrates of CD3⁺CD8⁺ T cells were larger in endophytic than exophytic tumors, while FOXP3⁺ Treg, TGF-β⁺, IL-10⁺, Arg-1⁺, CD11b⁺ cells were equally prominent in both. FOXP3⁺ Treg accumulated in endophytic tumor nests, while the exophytic tumor stroma was enriched in IL-10⁺ cells (both at p < 0.05). Hierarchical clustering based on immunophenotyping failed to identify different clusters in these two tumor types. However, CD68⁺ macrophages and FOXP3⁺ Treg showed a distinct distribution. The HNSCC growth pattern did not predict RFS. Although higher numbers and differences in localization of immunosuppressive cells in endophytic versus exophytic tumors were observed, no significant relationship was established between the growth pattern and the immune profile of infiltrating lymphocytes.     

Academic Progression and Retention Policies of Colleges and Schools of Pharmacy

Objective. To describe academic progression and retention policies used by US colleges and schools of pharmacy.Methods. Student handbooks on the Web sites of 122 colleges and schools of pharmacy were reviewed between February 2012 and May 2012.Results. Data were available and obtained from 98 (80%) programs. Most used grade point average (GPA) as a criterion for progression, with 66% requiring a minimum GPA of 2.0. Cumulative GPA was the most frequently used criteria for probation. Most handbooks did not address remediation, but 38% noted that a failed course could only be retaken once. The most common criteria for dismissal were the cumulative number of times a student was on probation. The graduation requirements of most programs were a cumulative GPA of 2.0 and completion of the program within 6 years of enrollment. Conclusions. Colleges and schools of pharmacy use various criteria for academic progression and retention and frequently provide incomplete or inadequate information related to probation, progression, and dismissal. Information regarding remediation and academic performance during experiential learning is lacking. A clearinghouse containing institutional data related to progression and retention would assist programs in developing academic policies. The study also highlights the need for ACPE to ensure this information is provided to students.