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A Fe-binding protein belonging to the Dps family (DNA binding protein from starved cells) in the N2-fixing marine cyanobacterium Trichodesmium erythraeum is described. A dps gene encoding a protein with significant levels of identity to the members of the Dps family was identified in the genome of T. erythraeum

Background: Type 2 diabetes affects nearly 34.2 million adults and is the seventh leading cause of death in the United States. Digital health communities have emerged as avenues to provide social support to individuals engaging in diabetes self-management (DSM). The analysis of digital peer interactions and social connections can improve our understanding of the factors underlying behavior change, which can inform the development of personalized DSM interventions., Objective: Our objective is to apply our methodology using a mixed methods approach to (1) characterize the role of context-specific social influence patterns in DSM and (2) derive interventional targets that enhance individual engagement in DSM., Methods: Using the peer messages from the American Diabetes Association support community for DSM (n=~73,000 peer interactions from 2014 to 2021), (1) a labeled set of peer interactions was generated (n=1501 for the American Diabetes Association) through manual annotation, (2) deep learning models were used to scale the qualitative codes to the entire datasets, (3) the validated model was applied to perform a retrospective analysis, and (4) social network analysis techniques were used to portray large-scale patterns and relationships among the communication dimensions (content and context) embedded in peer interactions., Results: The affiliation exposure model showed that exposure to community users through sharing interactive communication style speech acts had a positive association with the engagement of community users. Our results also suggest that pre-existing users with type 2 diabetes were more likely to stay engaged in the community when they expressed patient-reported outcomes and progress themes (communication content) using interactive communication style speech acts (communication context). It indicates the potential for targeted social network interventions in the form of structural changes based on the user's context and content exchanges with peers, which can exert social influence to modify user engagement behaviors., Conclusions: In this study, we characterize the role of social influence in DSM as observed in large-scale social media datasets. Implications for multicomponent digital interventions are discussed., (© Tavleen Singh, Kirk Roberts, Kayo Fujimoto, Jing Wang, Constance Johnson, Sahiti Myneni. Originally published in JMIR Diabetes (https://diabetes.jmir.org).)

Background: Glioblastoma patients may develop functional deficits post-operatively that affect activities of daily living and result in worse outcomes. The Activity Measure for Post-Acute Care (AM-PAC) instrument assigns patients basic mobility and daily activity scores, but it is unknown if these scores correlate with post-operative outcomes in glioblastoma patients., Methods: Adult (≥18 years) glioblastoma patients evaluated by physical/occupational therapy after resection at a single instution (June 2008-December 2020) were identified. Patient demographics, post-operative AM-PAC scores, and clinical outcomes were collected. Multivariate regression identified associations between AM-PAC scores and post-operative outcomes., Results: 600 patients were included (mean age 59.3 years, 59.2 % male); 151 (25.3 %) and 246 (43.8 %) patients had low mobility (<42.9) and activity (<39.4) scores, respectively. 103 (17.2 %) and 177 (29.5 %) patients experienced extended lengths of stay (LOS) in the ICU (≥2 days) and overall (≥7 days), respectively. 154 (25.7 %) patients had non-home discharges. The 30-day readmission rate was 13.7 %. In multivariate analysis, low mobility scores correlated with increased odds of extended overall (p < 0.0001) and ICU (p = 0.0004) LOS, non-home discharge (p < 0.0001), and 30-day readmission (p = 0.0405). Low activity scores correlated with extended overall LOS (<0.0001) and non-home discharge (p < 0.0001). In log-rank analysis, median survival time was shorter for patients with low mobility (9.5 vs. 14.7 months, p < 0.0001) and activity (10.6 vs. 16.3 months, p < 0.0001) scores than for high-scoring patients., Conclusion: AM-PAC basic mobility and daily activity scores are associated with outcomes after glioblastoma resection. These easily obtainable scores may be useful for prognosticating and guiding decision making in post-operative glioblastoma patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Advanced molecular testing has increasingly become an integral component for accurate diagnosis of central nervous system (CNS) tumors. We sought to establish the current state of molecular testing availability and approaches for the diagnosis of CNS tumors in US hospitals that conduct high volumes of CNS tumor resections. We distributed a 16-item survey inquiring about molecular testing approaches for CNS tumors to 115 neuropathologists at US hospitals with neurosurgery residency programs. Thirty-five neuropathologists (30.4%) responded to the survey, all of whom indicated their institutions perform molecular testing on CNS tumor tissue. The most commonly offered tests were MGMT methylation profiling and next-generation sequencing. Fourteen respondents (40%) indicated that their institution is able to test for and report all of the molecular alterations included in our survey. Nine (25.7%) respondents indicated that molecular testing is performed as standard of care for all patients with resected CNS tumors. Our results suggest that even in academic hospitals with a high volume of CNS tumor resections, molecular testing for these tumors is limited. Continued initiatives are necessary to expand the availability of molecular testing for CNS tumors to ensure diagnostic accuracy and guide targeted therapy., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Association of Neuropathologists, Inc.)

Health disparities cause significant strain on the wellbeing of individuals and society. In this study, we focus on the health disparities present in the condition of Peripartum Depression (PPD), a significant public health issue. While PPD can be managed through therapy and medication, many women do not receive adequate PPD treatment due to issues of social stigma and limited access to healthcare resources. Digital health technologies can offer practical tools for PPD management. However, current solutions do not integrate behavior theory and are rarely responsive to the transient information needs stemming from women's unique sociodemographic, clinical and psychosocial profiles. We describe a pilot acceptability evaluation of MomMind, a health-disparities focused digital health intervention for the prevention and management of PPD. A crucial MomMind advantage is its basis on behavior change theory and patient engagement as enabled by the Digilego digital health framework. Following an internal usability evaluation, MomMind was evaluated by patients through cross-sectional acceptability surveys, pre-and-post PPD health literacy surveys, and interviews. Survey respondents included n = 30 peripartum women, of whom n = 16 (53.3%) were Hispanic and n = 17 (56.7%) of low-income. Survey results show that 96.6% of participants (n = 29) approved and welcomed MomMind, and 90% (n = 27) found MomMind to be an appealing intervention. Additionally, significant improvements (p< = 0.05) were observed in participants' PPD health literacy, specifically their ability to recognize PPD symptoms and knowledge of how to seek PPD information. Interview main themes include MomMind's straightforward design and influence of others (family members, providers) on use of technology. Results suggest that enhancement of a digital health framework with health literacy theory can support production of digital health solutions acceptable to vulnerable populations. This study incorporates existing theories from different disciplines into a unified approach for mitigating health disparities, and produced a novel solution for promotion of health in a vulnerable population., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Bromine (Br) is widely distributed through the lithosphere and hydrosphere, and its chemistry in the environment is affected by natural processes and anthropogenic activities. While the chemistry of Br in the atmosphere has been comprehensively explored, there has never been an overview of the chemistry of Br in soil and aquatic systems. This review synthesizes current knowledge on the sources, geochemistry, health and environmental threats, remediation approaches, and regulatory guidelines pertaining to Br pollution in terrestrial and aquatic environments. Volcanic eruptions, geothermal streams, and seawater are the major natural sources of Br. In soils and sediments, Br undergoes natural cycling between organic and inorganic forms, with bromination reactions occurring both abiotically and through microbial activity. For organisms, Br is a non-essential element; it is passively taken up by plant roots in the form of the Br - anion. Elevated Br - levels can limit plant growth on coastal soils of arid and semi-arid environments. Br is used in the chemical industry to manufacture pesticides, flame retardants, pharmaceuticals, and other products. Anthropogenic sources of organobromine contaminants in the environment are primarily wastewater treatment, fumigants, and flame retardants. When aqueous Br - reacts with oxidants in water treatment plants, it can generate brominated disinfection by-products (DBPs), and exposure to DBPs is linked to adverse human health effects including increased cancer risk. Br - can be removed from aquatic systems using adsorbents, and amelioration of soils containing excess Br - can be achieved by leaching, adding various amendments, or phytoremediation. Developing cost-effective methods for Br - removal from wastewater would help address the problem of toxic brominated DBPs. Other anthropogenic organobromines, such as polybrominated diphenyl ether (PBDE) flame retardants, are persistent, toxic, and bioaccumulative, posing a challenge in environmental remediation. Future research directives for managing Br pollution sustainably in various environmental settings are suggested here., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2024. Published by Elsevier B.V. All rights reserved.)

Objective: High-risk pregnancy (HRP) conditions such as gestational diabetes mellitus (GDM), hypertension (HTN), and peripartum depression (PPD) affect maternal and neonatal health. Patient engagement is critical for effective HRP management (HRPM). While digital technologies and analytics hold promise, emerging research indicates limited and suboptimal support offered by the highly prevalent pregnancy digital solutions within the commercial marketplace. In this article, we describe our efforts to develop a portfolio of digital products leveraging advances in social computing, data science, and digital health., Methods: We describe three studies that leverage core methods from Digilego digital health development framework to (1) conduct large-scale social media analysis ( n  = 55 301 posts) to understand population-level patterns in women's needs, (2) architect a digital repository to enable women curate HRP related information, and (3) develop a digital platform to support PPD prevention. We applied a combination of qualitative coding, machine learning, theory-mapping, and programmatic implementation of theory-linked digital features. Further, we conducted preliminary testing of the resulting products for acceptance with sample of pregnant women for GDM/HTN information management ( n  = 10) and PPD prevention ( n  = 30)., Results: Scalable social computing models using deep learning classifiers with reasonable accuracy have allowed us to capture and examine psychosociobehavioral drivers associated with HRPM. Our work resulted in two digital health solutions, MyPregnancyChart and MomMind are developed. Initial evaluation of both tools indicates positive acceptance from potential end users. Further evaluation with MomMind revealed statistically significant improvements ( P  < .05) in PPD recognition and knowledge on how to seek PPD information., Discussion: Digilego framework provides an integrative methodological lens to gain micro-macro perspective on women's needs, theory integration, engagement optimization, as well as subsequent feature and content engineering, which can be organized into core and specialized digital pathways for women engagement in disease management., Conclusion: Future works should focus on implementation and testing of digital solutions that facilitate women to capture, aggregate, preserve, and utilize, otherwise siloed, prenatal information artifacts for enhanced self-management of their high-risk conditions, ultimately leading to improved health outcomes., Competing Interests: The authors have no competing interests to declare., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

Background: Risky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions., Methods: In this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior change techniques (BCTs) and speech act (SA) theory to uncover the socio-behavioral and linguistic context embedded within the online social discourse. Further, we uncovered the sequential patterns of BCTs and SAs from social conversations (n = 339,067). We utilized grounded theory-based techniques for extracting the scenarios that best describe individuals' needs and mapped them into the architecture of the virtual CA., Results: The frequently occurring sequential patterns for BCTs were comparison of behavior and feedback and monitoring ; for SAs were directive and assertion . Five cravings-related scenarios describing users' needs as they deal with nicotine cravings were identified along with the kinds of behavior change constructs that are being elicited within those scenarios., Conclusions: AI-led virtual CAs focusing on behavior change need to employ data-driven and theory-linked approaches to address issues related to engagement, sustainability, and acceptance. The sequential patterns of theory and intent manifestations need to be considered when developing effective behavior change CAs., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2024.)

Objective: Careful hematologic management is required in surgical patients with traumatic acute subdural hematoma (aSDH) taking antithrombotic medications. We sought to compare outcomes between patients with aSDH taking antithrombotic medications at admission who received antithrombotic reversal with patients with aSDH not taking antithrombotics., Methods: Retrospective review identified patients with traumatic aSDH requiring surgical evacuation. The cohort was divided based on antithrombotic use and whether pharmacologic reversal agents or platelet transfusions were administered. A 3-way comparison of outcomes was performed between patients taking anticoagulants who received pharmacologic reversal, patients taking antiplatelets who received platelet transfusion, and patients not taking antithrombotics. Multivariable regressions, adjusted for injury severity, further investigated associations with outcomes., Results: Of 138 patients who met inclusion criteria, 13.0% (n = 18) reported taking anticoagulants, 16.7% (n = 23) reported taking antiplatelets, and 3.6% (n = 5) reported taking both. Patients taking antiplatelets who received platelet transfusion had longer intraoperative times (P = 0.040) and higher rates of palliative care consultations (P = 0.046) compared with patients taking anticoagulants who received pharmacologic reversal and patients not taking antithrombotics. Across groups, no significant differences were found in frequency of in-hospital intracranial hemorrhage and venous thromboembolism, length of hospital stay, rate of inpatient mortality, or follow-up health status. In multivariable analysis, intraoperative time remained longest for the antiplatelets with platelet transfusion group. Other outcomes were not associated with patient group., Conclusions: Among surgical patients with traumatic aSDH, those taking antiplatelet medications who receive platelet transfusions experience longer intraoperative procedure times and higher rates of palliative care consultation. Comparable outcomes were observed between patients receiving antithrombotic reversal and patients not taking antithrombotics., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background and Objectives: Acute subdural hematoma (aSDH) after traumatic brain injury frequently requires emergent craniotomy (CO) or decompressive craniectomy (DC). We sought to determine the variables associated with either surgical approach and to compare outcomes between matched patients., Methods: A multi-center retrospective review was used to identify traumatic aSDH patients who underwent CO or DC. Patient variables independently associated with surgical approach were used for coarsened exact matching.Multivariate logistic regression and multivariate Cox proportional-hazards regression wereconducted on matched patients to determine independent predictors of mortality., Results: Seventy-six patients underwent CO and sixty-two underwent DC for aSDH evacuation. DC patients were21.4 years younger (P < 0.001), more likely to be male (80.6 % vs 60.5 %,P = 0.011), and present with GCS ≤ 8 (64.5 % vs 36.8 %,P = 0.001). Age (P < 0.001), epidural hematoma (P = 0.01), skull fracture (P = 0.001), and cisternal effacement (P = 0.02) were independently associated with surgical approach. After coarsened exact matching, DC (P = 0.008), older age (P = 0.007), male sex (P = 0.04), and intraventricular hemorrhage (P = 0.02), were independently associated with inpatient mortality. Multivariate Cox proportional-hazards regression demonstrated that DC was independently associated with mortality at 90-days (P = 0.001) and 1-year post-operation (P = 0.003)., Conclusion: aSDH patients who receive surgical evacuation via DC as opposed to CO are younger, more likely to be male, and have worse clinical exam. After controlling for patient differences via coarsened exact matching, DC is independently associated with mortality., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Peripartum Depression (PPD) affects approximately 10-15% of perinatal women in the U.S., with those of low socioeconomic status (low-SES) more likely to develop symptoms. Multilevel treatment barriers including social stigma and not having appropriate access to mental health resources have played a major role in PPD-related disparities. Emerging advances in digital technologies and analytics provide opportunities to identify and address access barriers, knowledge gaps, and engagement issues. However, most market solutions for PPD prevention and management are produced generically without considering the specialized needs of low-SES populations. In this study, we examine and portray the information and technology needs of low-SES women by considering their unique perspectives and providers' current experiences. We supplement our understanding of women's needs by harvesting online social discourse in PPD-related forums, which we identify as valuable information resources among these populations., Methods: We conducted (a) 2 focus groups (n = 9), (b) semi-structured interviews with care providers (n = 9) and low SES women (n = 10), and (c) secondary analysis of online messages (n = 1,424). Qualitative data were inductively analyzed using a grounded theory approach., Results: A total of 134 open concepts resulted from patient interviews, 185 from provider interviews, and 106 from focus groups. These revealed six core themes for PPD management, including "Use of Technology/Features", "Access to Care", and "Pregnancy Education". Our social media analysis revealed six PPD topics of importance in online messages, including "Physical and Mental Health" (n = 725 messages), and "Social Support" (n = 674)., Conclusion: Our data triangulation allowed us to analyze PPD information and technology needs at different levels of granularity. Differences between patients and providers included a focus from providers on needing better support from administrative staff, as well as better PPD clinical decision support. Our results can inform future research and development efforts to address PPD health disparities., (© 2023. The Author(s).)

Background: Online health communities (OHCs) have emerged as prominent platforms for behavior modification, and the digitization of online peer interactions has afforded researchers with unique opportunities to model multilevel mechanisms that drive behavior change. Existing studies, however, have been limited by a lack of methods that allow the capture of conversational context and socio-behavioral dynamics at scale, as manifested in these digital platforms., Objective: We develop, evaluate, and apply a novel methodological framework, Pragmatics to Reveal Intent in Social Media (PRISM), to facilitate granular characterization of peer interactions by combining multidimensional facets of human communication., Methods: We developed and applied PRISM to analyze peer interactions (N = 2.23 million) in QuitNet, an OHC for tobacco cessation. First, we generated a labeled set of peer interactions (n = 2,005) through manual annotation along three dimensions: communication themes (CTs), behavior change techniques (BCTs), and speech acts (SAs). Second, we used deep learning models to apply our qualitative codes at scale. Third, we applied our validated model to perform a retrospective analysis. Finally, using social network analysis (SNA), we portrayed large-scale patterns and relationships among the aforementioned communication dimensions embedded in peer interactions in QuitNet., Results: Qualitative analysis showed that the themes of social support and behavioral progress were common. The most used BCTs were feedback and monitoring and comparison of behavior, and users most commonly expressed their intentions using SAs-expressive and emotion. With additional in-domain pre-training, bidirectional encoder representations from Transformers (BERT) outperformed other deep learning models on the classification tasks. Content-specific SNA revealed that users' engagement or abstinence status is associated with the prevalence of various categories of BCTs and SAs, which also was evident from the visualization of network structures., Conclusions: Our study describes the interplay of multilevel characteristics of online communication and their association with individual health behaviors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objective: We provide a scoping review of Digital Health Interventions (DHIs) that mitigate COVID-19 misinformation and disinformation seeding and spread., Materials and Methods: We applied our search protocol to PubMed, PsychINFO, and Web of Science to screen 1666 articles. The 17 articles included in this paper are experimental and interventional studies that developed and tested public consumer-facing DHIs. We examined these DHIs to understand digital features, incorporation of theory, the role of healthcare professionals, end-user experience, and implementation issues., Results: The majority of studies (n = 11) used social media in DHIs, but there was a lack of platform-agnostic generalizability. Only half of the studies (n = 9) specified a theory, framework, or model to guide DHIs. Nine studies involve healthcare professionals as design or implementation contributors. Only one DHI was evaluated for user perceptions and acceptance., Discussion: The translation of advances in online social computing to interventions is sparse. The limited application of behavioral theory and cognitive models of reasoning has resulted in suboptimal targeting of psychosocial variables and individual factors that may drive resistance to misinformation. This affects large-scale implementation and community outreach efforts. DHIs optimized through community-engaged participatory methods that enable understanding of unique needs of vulnerable communities are urgently needed., Conclusions: We recommend community engagement and theory-guided engineering of equitable DHIs. It is important to consider the problem of misinformation and disinformation through a multilevel lens that illuminates personal, clinical, cultural, and social pathways to mitigate the negative consequences of misinformation and disinformation on human health and wellness., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)