A Survey on Blood Pressure Measurement Technologies: Addressing Potential Sources of Bias

Regular blood pressure (BP) monitoring in clinical and ambulatory settings plays a crucial role in the prevention, diagnosis, treatment, and management of cardiovascular diseases. Recently, the widespread adoption of ambulatory BP measurement devices has been driven predominantly by the increased prevalence of hypertension and its associated risks and clinical conditions. Recent guidelines advocate for regular BP monitoring as part of regular clinical visits or even at home. This increased utilization of BP measurement technologies has brought up significant concerns, regarding the accuracy of reported BP values across settings. In this survey, focusing mainly on cuff-based BP monitoring technologies, we highlight how BP measurements can demonstrate substantial biases and variances due to factors such as measurement and device errors, demographics, and body habitus. With these inherent biases, the development of a new generation of cuff-based BP devices which use artificial-intelligence (AI) has significant potential. We present future avenues where AI-assisted technologies can leverage the extensive clinical literature on BP-related studies together with the large collections of BP records available in electronic health records. These resources can be combined with machine learning approaches, including deep learning and Bayesian inference, to remove BP measurement biases and to provide individualized BP-related cardiovascular risk indexes

Research conference summary from the 2014 International Task Force on

OBJECTIVE: METHODS: In 2014, the Alternating Hemiplegia of Childhood Foundation hosted a multidisciplinary workshop intended to address fundamental challenges surrounding the diagnosis and management of individuals with RESULTS: Workshop attendees were charged with the following: (1) to achieve consensus on expanded diagnostic criteria to facilitate the identification of additional patients, intended to supplement existing syndrome-specific diagnostic paradigms; (2) to standardize definitions for the broad range of paroxysmal manifestations associated with AHC to disseminate to families; (3) to create clinical recommendations for common recurrent issues facing families and medical care providers; (4) to review data related to the death of individuals in the Alternating Hemiplegia of Childhood Foundation database to guide future efforts in identifying at-risk subjects and potential preventative measures; and (5) to identify critical gaps where we most need to focus national and international research efforts. CONCLUSIONS: This report summarizes recommendations of the workshop committee, highlighting the key phenotypic features to facilitate the diagnosis of possibl

Pathway and network analysis of more than 2500 whole cancer genomes

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments

Pangolins in global camera trap data: Implications for ecological monitoring

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (<0.05) for all species. Occupancy was associated with distance from rivers for M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological advances in camera trapping facilitate greater sampling efforts and/or higher probabilities of detection. In particular, targeted camera placement for pangolins is likely to make pangolin monitoring more feasible with moderate sampling efforts

An inclusive Research and Education Community (iREC) model to facilitate undergraduate science education reform

Funding: This work was supported by Howard Hughes Medical Institute grants to DIH is GT12052 and MJG is GT15338.Over the last two decades, there have been numerous initiatives to improve undergraduate student outcomes in STEM. One model for scalable reform is the inclusive Research Education Community (iREC). In an iREC, STEM faculty from colleges and universities across the nation are supported to adopt and sustainably implement course-based research – a form of science pedagogy that enhances student learning and persistence in science. In this study, we used pathway modeling to develop a qualitative description that explicates the HHMI Science Education Alliance (SEA) iREC as a model for facilitating the successful adoption and continued advancement of new curricular content and pedagogy. In particular, outcomes that faculty realize through their participation in the SEA iREC were identified, organized by time, and functionally linked. The resulting pathway model was then revised and refined based on several rounds of feedback from over 100 faculty members in the SEA iREC who participated in the study. Our results show that in an iREC, STEM faculty organized as a long-standing community of practice leverage one another, outside expertise, and data to adopt, implement, and iteratively advance their pedagogy. The opportunity to collaborate in this manner and, additionally, to be recognized for pedagogical contributions sustainably engages STEM faculty in the advancement of their pedagogy. Here, we present a detailed pathway model of SEA that, together with underpinning features of an iREC identified in this study, offers a framework to facilitate transformations in undergraduate science education.Peer reviewe

Pangolins in Global Camera Trap Data: Implications for Ecological Monitoring

Despite being heavily exploited, pangolins (Pholidota: Manidae) have been subject to limited research, resulting in a lack of reliable population estimates and standardised survey methods for the eight extant species. Camera trapping represents a unique opportunity for broad-scale collaborative species monitoring due to its largely non-discriminatory nature, which creates considerable volumes of data on a relatively wide range of species. This has the potential to shed light on the ecology of rare, cryptic and understudied taxa, with implications for conservation decision-making. We undertook a global analysis of available pangolin data from camera trapping studies across their range in Africa and Asia. Our aims were (1) to assess the utility of existing camera trapping efforts as a method for monitoring pangolin populations, and (2) to gain insights into the distribution and ecology of pangolins. We analysed data collated from 103 camera trap surveys undertaken across 22 countries that fell within the range of seven of the eight pangolin species, which yielded more than half a million trap nights and 888 pangolin encounters. We ran occupancy analyses on three species (Sunda pangolin Manis javanica, white-bellied pangolin Phataginus tricuspis and giant pangolin Smutsia gigantea). Detection probabilities varied with forest cover and levels of human influence for P. tricuspis, but were low (M. javanica and S. gigantea, elevation for P. tricuspis and S. gigantea, forest cover for P. tricuspis and protected area status for M. javanica and P. tricuspis. We conclude that camera traps are suitable for the detection of pangolins and large-scale assessment of their distributions. However, the trapping effort required to monitor populations at any given study site using existing methods appears prohibitively high. This may change in the future should anticipated technological and methodological advances in camera trapping facilitate greater sampling efforts and/or higher probabilities of detection. In particular, targeted camera placement for pangolins is likely to make pangolin monitoring more feasible with moderate sampling efforts

Pathway and network analysis of more than 2500 whole cancer genomes.

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancer across 38 tumor types, we perform multi-faceted pathway and network analyses of non-coding mutations across 2583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project that was motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes. While few non-coding genomic elements are recurrently mutated in this cohort, we identify 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We find that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing is primarily altered by non-coding mutations in this cohort, and samples containing non-coding mutations in well-known RNA splicing factors exhibit similar gene expression signatures as samples with coding mutations in these genes. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments