Wastewater-based drug epidemiology to estimate societal drug use: A critical review

Illicit drug use has many consequences resulting in social, health, and economic harm. An objective method of quantifying societal drug use would be useful for the efficient directing of the efforts of law enforcement, medical facilities and policy makers, and to inform the community. To this end, efforts to ascertain societal drug use have relied upon community surveys and extrapolation from law enforcement seizures, which often present the data as biased or skewed due to a small sample size and other associated limitations. In recent times, wastewater-based drug epidemiology (WBDE) has been proposed as a suitable means to objectively quantify societal drug use. WBDE is the study of the incidence and distribution of drug use within a population and the its factors affecting the health and welfare. It is a method contingent upon the concept of measuring drug metabolites or biomarkers in wastewater (WW), from which levels of societal drug use are estimated and quantified through extrapolation and back-calculations. The aim of this study was to critically review the various methods of WBDE that have been applied in Australia and in Europe. The outcomes of the assessment pertaining to their validity in directly and objectively measuring societal drug use will be presented. Keywords: wastewater-based drug epidemiology, wastewater-based epidemiology, illicit drugs, drug abuse, estimate, societal drug use, populatio

Embodying the Other: Effects of Experiencing the Rubber Hand Illusion in Virtual Reality on Implicit Racial Biases

Research on the Rubber Hand Illusion (RHI) has recently begun to explore induced body ownership exercises as a means for experimentally changing implicit social attitudes. Similarly, recent innovations in Virtual Reality (VR) have lead researchers to begin investigating VR as a tool for empathy training and perspective taking. The present study addresses these two fields of research by replicating the RHI in VR, with the goal of inducing body ownership over virtual hands of racial outgroups. A race Implicit Association Test was administered to measure racial biases before and after the illusion. It was predicted that participants who experienced the illusion with the virtual hand of a race different than their own would show greater changes in performance on the post-illusion Implicit Association Test. By and large, results did not show a significant difference between the different hand conditions, though there was a marginally significant effect of racial membership on the strength of ownership during the illusion. Future research should focus on assessing pre-existing implicit attitudes, in order to clarify the question concerning which types of people benefit the most from these body ownership exercises that aim to change social biases

Health Preferences and Culturally Appropriate Strategies to Reduce Bear Bile Demand in Northern Vietnam

Animal products, such as pangolin scales, rhinoceros horns, tiger bones, and bear bile have been used in East Asian traditional medicine (TM) for more than 2,000 years. However, markets for medicinal wildlife products have expanded dramatically in countries like China and Vietnam in recent decades where economic prosperity has enabled a larger proportion of the population to afford wildlife products (Olmedo et al. 2017). Related new farming and commercialization practices to meet growing international demand pose environmental and human health risks. Animal products also symbolize shared cultural and historical medical practices that are distinct from the dominant Western medical model

Enhancing interoperability and harmonisation of nuclear medicine image data and associated clinical data

Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions

eSano – An eHealth Platform for Internet- and Mobile-based Interventions

The prevention and treatment of mental disorders and chronic somatic diseases is a core challenge for health care systems of the 21th century. Mental- and behavioral health interventions provide the means for lowering the public health burden. However, structural deficits, reluctance to use existing services, perceived stigma and further personal and environmental reasons restrict the uptake of these evidence-based approaches. Internet- and mobile-based interventions (IMIs) might overcome some of the limitations of on-site interventions by providing an anonymous, scalable, time- and location-independent, yet evidence-based approach. In order to implement digital mental and behavioral health concepts across the life-span into practice, a technical solution to support the design, creation, and execution of IMIs is needed. However, there are various conceptual, technical as well as legal challenges to implementing a corresponding software solution in the healthcare domain. Therefore, the work at hand (1) identifies these challenges and derives a number of respective requirements, (2) introduces the eHealth platform eSano, a software project developed by an interdisciplinary team of computer scientists, psychologists, therapists, and other domain experts, with the aim to serve as a flexible basis for mental and behavioral research and health care, and (3) provides technical insights into the developed platform and its approach to address the aforementioned requirements

Using Affective Content to Promote High-Involvement Services on Social Media

Service providers’ communication on social media has become a viable method to influence customer purchasing behavior and firm outcomes. Because services are intangible, one of the most pertinent challenges is to design text-based social media content to reduce customers’ perceived risk and enhance desired outcomes. According to Emotions as Social Information (EASI) theory, affective expression can positively influence observer’s reactions. Yet, evidence suggests that affective content (i.e., the use of affective words) is less helpful in high-involvement situations, as customers prefer cognitive information to reduce risk. However, four experiments reveal that high-involvement service providers can enhance customers’ purchase intentions by employing affective content in their online communication. This is because affective content signals effort of the provider, reducing perceived risk, and increasing purchase intentions. Results also demonstrate affective content works better for prevention- (vs. promotion) focused customers and for providers with high-quality reputations, indicating the relative primacy of inferential over affective processes when evaluating affective content. Practically, service providers should carefully rebalance their communication to increase affective content in social media posts

Enhancing Interoperability and Harmonisation of Nuclear Medicine Image Data and Associated Clinical Data

Nuclear imaging techniques such as positron emission tomography (PET) and single photon emission computed tomography (SPECT) in combination with computed tomography (CT) are established imaging modalities in clinical practice, particularly for oncological problems. Due to a multitude of manufacturers, different measurement protocols, local demographic or clinical workflow variations as well as various available reconstruction and analysis software, very heterogeneous datasets are generated. This review article examines the current state of interoperability and harmonisation of image data and related clinical data in the field of nuclear medicine. Various approaches and standards to improve data compatibility and integration are discussed. These include, for example, structured clinical history, standardisation of image acquisition and reconstruction as well as standardised preparation of image data for evaluation. Approaches to improve data acquisition, storage and analysis will be presented. Furthermore, approaches are presented to prepare the datasets in such a way that they become usable for projects applying artificial intelligence (AI) (machine learning, deep learning, etc.). This review article concludes with an outlook on future developments and trends related to AI in nuclear medicine, including a brief research of commercial solutions

Clinical and Cost-Effectiveness of PSYCHOnlineTHERAPY: Study Protocol of a Multicenter Blended Outpatient Psychotherapy Cluster Randomized Controlled Trial for Patients With Depressive and Anxiety Disorders

Introduction: Internet- and mobile-based interventions (IMIs) and their integration into routine psychotherapy (i.e., blended therapy) can offer a means of complementing psychotherapy in a flexible and resource optimized way. Objective: The present study will evaluate the non-inferiority, cost-effectiveness, and safety of two versions of integrated blended psychotherapy for depression and anxiety compared to standard cognitive behavioral therapy (CBT). Methods: A three-armed multicenter cluster-randomized controlled non-inferiority trial will be conducted comparing two implementations of blended psychotherapy (PSYCHOnlineTHERAPYfix/flex) compared to CBT. Seventy-five outpatient psychotherapists with a CBT-license will be randomized in a 1:1:1 ratio. Each of them is asked to include 12 patients on average with depressive or anxiety disorders resulting in a total sample size of N = 900. All patients receive up to a maximum of 16 psychotherapy sessions, either as routine CBT or alternating with Online self-help sessions (fix: 8/8; flex: 0–16). Assessments will be conducted at patient study inclusion (pre-treatment) and 6, 12, 18, and 24 weeks and 12 months post-inclusion. The primary outcome is depression and anxiety severity at 18 weeks post-inclusion (post-treatment) using the Patient Health Questionnaire Anxiety and Depression Scale. Secondary outcomes are depression and anxiety remission, treatment response, health-related quality of life, patient satisfaction, working alliance, psychotherapy adherence, and patient safety. Additionally, several potential moderators and mediators including patient characteristics and attitudes toward the interventions will be examined, complemented by ecological day-to-day digital behavior variables via passive smartphone sensing as part of an integrated smart-sensing sub-study. Data-analysis will be performed on an intention-to-treat basis with additional per-protocol analyses. In addition, cost-effectiveness and cost-utility analyses will be conducted from a societal and a public health care perspective. Additionally, qualitative interviews on acceptance, feasibility, and optimization potential will be conducted and analyzed. Discussion: PSYCHOnlineTHERAPY will provide evidence on blended psychotherapy in one of the largest ever conducted psychotherapy trials. If shown to be non-inferior and cost-effective, PSYCHOnlineTHERAPY has the potential to innovate psychotherapy in the near future by extending the ways of conducting psychotherapy. The rigorous health care services approach will facilitate a timely implementation of blended psychotherapy into standard care

Co-occurrence of Myocardial Sarcoidosis and Left Ventricular Non-compaction in a Patient with Advanced Heart Failure

A 46-year-old man with systolic heart failure, end-stage renal disease on dialysis, ventricular tachycardia and pulmonary sarcoidosis presented with decompensated heart failure and cardiogenic shock of unknown aetiology. The hospital course was complicated by worsening shock requiring inotropic and mechanical circulatory support, as well as eventual dual heart and kidney transplantation. Cardiac imaging was used to assess the aetiology of the patient’s non-ischaemic cardiomyopathy, including a PET scan and cardiac MRI. Imaging demonstrated findings consistent with left ventricular non-compaction, but was inconclusive for cardiac sarcoidosis. After eventual heart transplantation, histopathology of the patient’s explanted heart showed evidence of both non-compaction and cardiac sarcoidosis. In this case report, the authors review the pathophysiology of both cardiac sarcoidosis and left ventricular non-compaction, and highlight a multimodality approach to the diagnosis of non-ischaemic cardiomyopathy

Proteogenomics decodes the evolution of human ipsilateral breast cancer

Ipsilateral breast tumor recurrence (IBTR) is a clinically important event, where an isolated in-breast recurrence is a potentially curable event but associated with an increased risk of distant metastasis and breast cancer death. It remains unclear if IBTRs are associated with molecular changes that can be explored as a resource for precision medicine strategies. Here, we employed proteogenomics to analyze a cohort of 27 primary breast cancers and their matched IBTRs to define proteogenomic determinants of molecular tumor evolution. Our analyses revealed a relationship between hormonal receptors status and proliferation levels resulting in the gain of somatic mutations and copy number. This in turn re-programmed the transcriptome and proteome towards a highly replicating and genomically unstable IBTRs, possibly enhanced by APOBEC3B. In order to investigate the origins of IBTRs, a second analysis that included primaries with no recurrence pinpointed proliferation and immune infiltration as predictive of IBTR. In conclusion, our study shows that breast tumors evolve into different IBTRs depending on hormonal status and proliferation and that immune cell infiltration and Ki-67 are significantly elevated in primary tumors that develop IBTR. These results can serve as a starting point to explore markers to predict IBTR formation and stratify patients for adjuvant therapy