A cellular system for spatial signal decoding in chemical gradients.

Directional cell growth requires that cells read and interpret shallow chemical gradients, but how the gradient directional information is identified remains elusive. We use single-cell analysis and mathematical modeling to define the cellular gradient decoding network in yeast. Our results demonstrate that the spatial information of the gradient signal is read locally within the polarity site complex using double-positive feedback between the GTPase Cdc42 and trafficking of the receptor Ste2. Spatial decoding critically depends on low Cdc42 activity, which is maintained by the MAPK Fus3 through sequestration of the Cdc42 activator Cdc24. Deregulated Cdc42 or Ste2 trafficking prevents gradient decoding and leads to mis-oriented growth. Our work discovers how a conserved set of components assembles a network integrating signal intensity and directionality to decode the spatial information contained in chemical gradients.

Quality assessment of primary care for common mental disorders in isolated communities: Taking advantage of health records.

INTRODUCTION: This article is part of a research study on the organization of primary health care (PHC) for mental health in two of Quebec's remote regions. It introduces a methodological approach based on information found in health records, for assessing the quality of PHC offered to people suffering from depression or anxiety disorders. METHODS: Quality indicators were identified from evidence and case studies were reconstructed using data collected in health records over a 2-year observation period. Data collection was developed using a three-step iterative process: (1) feasibility analysis, (2) development of a data collection tool, and (3) application of the data collection method. The adaptation of quality-of-care indicators to remote regions was appraised according to their relevance, measurability and construct validity in this context. RESULTS: As a result of this process, 18 quality indicators were shown to be relevant, measurable and valid for establishing a critical quality appraisal of four recommended dimensions of PHC clinical processes: recognition, assessment, treatment and follow-up. CONCLUSIONS: There is not only an interest in the use of health records to assess the quality of PHC for mental health in remote regions but also a scientific value for the rigorous and meticulous methodological approach developed in this study. From the perspective of stakeholders in the PHC system of care in remote areas, quality indicators are credible and provide potential for transferability to other contexts. This study brings information that has the potential to identify gaps in and implement solutions adapted to the context.

Enhanced capture of healthcare-related harms and injuries in the 11th revision of the International Classification of Diseases (ICD-11).

The World Health Organization (WHO) plans to submit the 11th revision of the International Classification of Diseases (ICD) to the World Health Assembly in 2018. The WHO is working toward a revised classification system that has an enhanced ability to capture health concepts in a manner that reflects current scientific evidence and that is compatible with contemporary information systems. In this paper, we present recommendations made to the WHO by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. The Q&S TAG has grouped causes of healthcare-related harm and injuries into four categories that relate to the source of the event: (a) medications and substances, (b) procedures, (c) devices and (d) other aspects of care. Under the proposed multiple coding approach, one of these sources of harm must be coded as part of a cluster of three codes to depict, respectively, a healthcare activity as a 'source' of harm, a 'mode or mechanism' of harm and a consequence of the event summarized by these codes (i.e. injury or harm). Use of this framework depends on the implementation of a new and potentially powerful code-clustering mechanism in ICD-11. This new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions, and the overall quality of coded health data.