MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation

The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users. The intended generation can be expressed in natural language, with the model producing faithful interpretations of text prompts. However, expressing complex or nuanced ideas in text alone can be difficult. To ease image generation, we propose MultiFusion that allows one to express complex and nuanced concepts with arbitrarily interleaved inputs of multiple modalities and languages. MutliFusion leverages pre-trained models and aligns them for integration into a cohesive system, thereby avoiding the need for extensive training from scratch. Our experimental results demonstrate the efficient transfer of capabilities from individual modules to the downstream model. Specifically, the fusion of all independent components allows the image generation module to utilize multilingual, interleaved multimodal inputs despite being trained solely on monomodal data in a single language

Control of mitogenic and motogenic pathways by miR-198, diminishing hepatoma cell growth and migration

Abstract Hepatocellular carcinoma (HCC) is one of the leading causes of cancer deaths, worldwide. MicroRNAs, inhibiting gene expression by targeting various transcripts, are involved in genomic dysregulation during hepatocellular tumorigenesis. In previous studies, microRNA-198 (miR-198) was shown to be significantly downregulated in HCV-positive hepatocellular carcinoma (HCC). Herein, the function of miR-198 in hepatocellular carcinoma cell growth and gene expression was studied. In hepatoma cell-types with low levels of liver-specific transcription factor HNF1α indicating a low differentiation grade, miR-198 expression was most downregulated. However, miR-198 treatment did not restore the expression of the liver-specific transcription factors HNF1α or HNF4α. Importantly, overexpression of miR-198 in Pop10 hepatoma cells markedly reduced cell growth. In agreement, comprehensive gene expression profiling by microarray hybridisation and real-time quantification revealed that central signal transducers of proliferation pathways were downregulated by miR-198. In contrast, genes mediating cellular adherence were highly upregulated by miR-198. Thus, the low expression of E-cadherin and claudin-1, involved in cell adhesion and cell-cell contacts, was abolished in hepatoma cells after miR-198 overexpression. This definite induction of both proteins by miR-198 was shown to be accompanied by a significantly impaired migration activity of hepatoma Pop10 cells. In conclusion, miR-198 acts as a tumor suppressor by repression of mitogenic and motogenic pathways diminishing cell growth and migration

Involving patients via the "Austrian Patient Council"

<p>A poster presented at the <i>Citizen Science 4 Health 2023</i> conference.</p><p><strong>Abstract</strong></p><p>Patients and loved ones are experts by experience and complete the picture next to healthcare professionals. To increase the involvement of patients in health research we have established the Austrian Patient Council (APC) and accompanied the process scientifically to demonstrate our learnings in its first year of existence.</p><p>In April 2022 we issued a call for applications. Members were selected based on predefined criteria (patient experience, participation motivation, age, gender). We did one online survey at the beginning (expectations about the work as APC members) and one at the end of the APC's first year (experiences and satisfaction). Furthermore, we heard intermediate feedback and did 5 individual interviews with members to collect more structured feedback.</p><p>We received 44 applications and invited 18 members fitting the predefined criteria. We selected 10 men and 8 women, aged 27 to 78 (mean 50.4 years) from 5 federal provinces with a variety of lived patient experiences. Although, we headed for a mixed group, only formally highly educated persons that are moreover very eager to be empowered applied. After the kick-off in May 2022, we gathered quarterly and did three educational workshops.</p><p>Thanks to the LBG OIS Center funding, we could remunerate the council members' work. The evaluation shows that the success of the first cycle was facilitated by discussing interesting topics, good time management, joint activities and very little administrative effort for the members. After the completion of the first year in April 2023, 13 council members showed an active interest in further activity.</p&gt

Levels, Predictors, and Distribution of Interpersonal Solidarity during the COVID-19 Pandemic

Since introducing the first non-pharmaceutical interventions (NPIs) to decelerate the spread of the virus, European governments have highlighted the role of “solidarity”. However, the role and levels of solidarity, especially during the past lockdowns, is uncertain. The present study thus explores the levels, the role, and the distribution of received and demonstrated interpersonal solidarity during the COVID-19 pandemic. This pooled cross-sectional study was conducted from March 2020 to March 2021 in Germany, including 19,977 participants. Levels of solidarity between the first and the second lockdowns in Germany were compared, possible predictors were examined, and three clusters were defined to unveil distributional patterns of solidarity reception and/or demonstration. To compare solidarity levels between the first and the second lockdowns in Germany, a dummy-coded lockdown variable was introduced and regressed on the two solidarity items. To identify predictors of received and demonstrated solidarity, two multiple linear regression models were computed, testing several demographic and psychological factors. For further exploratory analyses, clusters of “helpers”, “non-helpers”, and “help-receivers and helpers” were computed based on a k-means cluster analysis. Results revealed a lower level of solidarity during the second lockdown compared with the first one. Demonstrated solidarity was positively predicted by adherent safety behavior to avoid COVID-19 infection and by middle age, and negatively by depression symptoms, male gender, and high age. Received solidarity was positively predicted by higher age, by both adherent and dysfunctional safety behavior in avoidance of COVID-19 infection, and by lower educational level. “Helpers” reported little received solidarity but demonstrated high solidarity, “non-helpers” showed both little demonstrated and received solidarity, and “help-receivers and helpers” showed middle–high received and demonstrated solidarity. The three clusters differed the most regarding the variables of age, adherent and dysfunctional safety behavior, fear of COVID-19, subjective risk perceptions regarding contraction of COVID-19 and the respective consequences, and trust in governmental interventions in response to COVID-19. The decrease in interpersonal solidarity over the course of the COVID-19 pandemic, as well as its predictors, should be considered regarding prospective impositions. Furthermore, as depressive symptoms were identified to negatively predict interpersonal solidarity, the adequate provision of mental health services, especially during the COVID-19 pandemic, becomes even more important

Comparison of synthetic dataset generation methods for medical intervention rooms using medical clothing detection as an example

Abstract Purpose The availability of real data from areas with high privacy requirements, such as the medical intervention space is low and the acquisition complex in terms of data protection. To enable research for assistance systems in the medical intervention room, new methods for data generation for these areas must be researched. Therefore, this work presents a way to create a synthetic dataset for the medical context, using medical clothing object detection as an example. The goal is to close the reality gap between the synthetic and real data. Methods Methods of 3D-scanned clothing and designed clothing are compared in a Domain-Randomization and Structured-Domain-Randomization scenario using two different rendering engines. Additionally, a Mixed-Reality dataset in front of a greenscreen and a target domain dataset were used while the latter is used to evaluate the different datasets. The experiments conducted are to show whether scanned clothing or designed clothing produce better results in Domain Randomization and Structured Domain Randomization. Likewise, a baseline will be generated using the mixed reality data. In a further experiment it is investigated whether the combination of real, synthetic and mixed reality image data improves the accuracy compared to real data only. Results Our experiments show, that Structured-Domain-Randomization of designed clothing together with Mixed-Reality data provide a baseline achieving 72.0% mAP on the test dataset of the clinical target domain. When additionally using 15% (99 images) of available target domain train data, the gap towards 100% (660 images) target domain train data could be nearly closed 80.05% mAP (81.95% mAP). Finally, we show that when additionally using 100% target domain train data the accuracy could be increased to 83.35% mAP. Conclusion In conclusion, it can be stated that the presented modeling of health professionals is a promising methodology to address the challenge of missing datasets from medical intervention rooms. We will further investigate it on various tasks, like assistance systems, in the medical domain

Acceptance, drivers, and barriers to use eHealth interventions in patients with post-COVID-19 syndrome for management of post-COVID-19 symptoms: a cross-sectional study

Background: Post-COVID-19 syndrome is a new and debilitating disease without adequate treatment options. eHealth could be a reasonable approach for symptom management. Objectives: This study aims to evaluate the acceptance for eHealth interventions for symptom management in individuals with post-COVID-19 syndrome, as well as drivers and barriers influencing acceptance. Design: Cross-sectional study. Methods: This study was conducted from January 19 until 24 May 2022. Recruitment took place with a web-based survey. Acceptance and predictors of eHealth interventions were measured by the extended UTAUT model. Included in the model were the core predictor performance expectancy, social influence, and effort expectancy. Previously diagnosed mental illness was estimated and mental health by using the well-established Generalized Anxiety Disorder Scale-7 and the Patient Health Questionnaire Depression Scale. The effect of sociodemographic and medical data was assessed. Multiple hierarchical regression analyses as well as group comparisons were performed. Results: 342 individuals with post-COVID-19 syndrome were examined. The acceptance of eHealth interventions for symptom management was moderate to high (M = 3.60, SD = 0.89). Acceptance was significantly higher in individuals with lower/other education, patients with moderate to severe symptoms during initial COVID-19 infection, still significantly impaired patients, and individuals with a mental illness. Identified predictors of acceptance were age (β = .24, p  < .001), current condition including moderate (β = .49, p  = .002) and still significantly impaired (β = .67, p  < .001), digital confidence (β = .19, p  < .001), effort expectancy (β = .26, p  < .001), performance expectancy (β = .33, p  < .001), and social influence (β = .26, p  < .001). Conclusion: Patients with post-COVID-19 syndrome reported a satisfying level of acceptance and drivers and barriers could be identified. These factors need to be considered for the implementation and future use of eHealth interventions

Participative development and evaluation of a communication skills-training program for oncologists-patient perspectives on training content and teaching methods

Background Using the 6-step approach to curriculum development for medical education, we developed a communication skills training (CST) curriculum for oncology and evaluated this curriculum from the perspective of cancer patients. Methods We conducted a qualitative interview study with cancer patients, collecting data using semi-structured face-to-face or telephone interviews with a short standardized survey. We fully transcribed the audiotaped interviews and conducted the content analysis using MAXQDA 2020. We analyzed the quantitative sociodemographic data descriptively. Results A total of 22 cancer patients participated, having a mean age of 60.6 (SD, 13.2) years and being predominantly female (55%). The patients believed that the CST curriculum addressed important aspects of patient-centered communication in cancer care. They emphasized the importance of physicians acquiring communication skills to establish a trusting relationship between doctor and patient, show empathy, inform patients, and involve them in treatment decisions. The patients had some doubts concerning the usefulness of strict protocols or checklists (e.g., they feared that protocol adherence might disturb the conversation flow). Discussion Although it was a challenge for some participants to take the perspective of a trainer and comment on the CST content and teaching methods, the patients provided a valuable perspective that can help overcome blind spots in CST concepts

Mental health burden of patients with diabetes before and after the initial outbreak of COVID-19: predictors of mental health impairment

Background!#!The COVID-19 pandemic is affecting people's mental health worldwide. Patients with diabetes are at risk for a severe course of illness when infected with SARS-CoV-2. The present study aims to retrospectively examine mental health changes in patients with diabetes in Germany before and after the initial COVID-19 outbreak, and to furthermore explore potential predictors of such changes.!##!Methods!#!Over the course of eight weeks from April to June 2020, 253 individuals diagnosed with diabetes participated in an online cross-sectional study. Participants completed an anonymous survey including demographics, depression (PHQ-2) and generalized anxiety symptoms (GAD-2), distress (DT), and health status (EQ-5D-3L). In addition, all instruments used were modified to retrospectively ask participants to recall their mental health and health status before the outbreak had started. Additionally examined factors were COVID-19-related fear, trust in governmental actions to face the pandemic, and the subjective level of information about COVID-19.!##!Results!#!This study shows a significant increase in prevalence of depression symptoms, generalized anxiety symptoms and distress, as well as significantly decreased health statuses in diabetes patients after the initial COVID-19 outbreak. Increased depression symptoms, generalized anxiety symptoms and distress were predicted by COVID-19-related fear, whereas trust in governmental actions to face COVID-19 predicted higher depression symptoms.!##!Conclusions!#!The results indicate a negative impact of the initial COVID-19 outbreak on mental health and health status in patients with diabetes. In order to improve the efficacy of psychological support strategies for diabetes patients during the pandemic, possible predictors of mental health impairment such as the aforementioned should be examined more thoroughly and addressed more openly

Mental Health Burden of German Cancer Patients before and after the Outbreak of COVID-19: Predictors of Mental Health Impairment

The aim of this study was to analyze individual changes in cancer patients’ mental health before and after the COVID-19 outbreak, and to explore predictors of mental health impairment. Over a two-week period (16–30 March 2020), 150 cancer patients in Germany participated in this study. Validated instruments assessed demographic and medical data, depression and anxiety symptoms (PHQ-2, GAD-2), distress (DT), and health status (EQ-5D-3L). All instruments were adapted to measure the individual mental health before the COVID-19 outbreak. COVID-19-related fear, trust in governmental actions to face COVID-19, and the subjective level of information regarding COVID-19 were measured. Cancer patients showed a significant increase in depression and anxiety symptoms and distress, while health status deteriorated since the COVID-19 outbreak. Increased depression and generalized anxiety symptoms were predicted by COVID-19-related fear. Trust in governmental actions to face COVID-19 and COVID-19-related fear predicted increases in distress. Higher subjective levels of information predicted less increasing anxiety symptoms and distress. Present data suggests that cancer patients experienced a significant increase in mental health burden since the COVID-19 outbreak. Observed predictors of mental health impairment and protective factors should be addressed, and appropriate interventions established, to maintain mental health of cancer patients during the pandemic

Increased Safety Behavior and COVID-19-Related Fear in Adults with Cystic Fibrosis during the Pandemic

People with cystic fibrosis (pwCF) face great challenges during the ongoing COVID-19 pandemic. Recent research found equal levels of distress in pwCF and healthy controls (HC). The current study aimed to investigate the mental health burden and safety behavior in pwCF. Sixty-nine adult pwCF and sixty-nine propensity-score-matched HC participated in this study. Participants completed an anonymous online questionnaire assessing distress, generalized anxiety, depressive symptoms, COVID-19-related variables, self-reported adherent safety behavior (ASB), and dysfunctional safety behavior (DSB). PwCF showed equal amounts of distress (W = 2481.0, p = 0.669), depressive symptoms (W = 2632.5, p = 0.268), and generalized anxiety symptoms (W = 2515.5, p = 0.565) compared to the HC. COVID-19-related fear (W = 1872.0, p = 0.028), ASB (W = 1630.0, p = 0.001), and DSB (W = 1498.5, p &lt; 0.001) were significantly elevated in pwCF. The pwCF estimated that the probability of suffering from symptoms (W = 954.5, p &lt; 0.001), experiencing a severe course (W = 806.5, p &lt; 0.001), or dying (W = 1079.0, p &lt; 0.001) from COVID-19 is significantly higher than that of the HC. ASB was associated with a CF diagnosis, COVID-19-related fear, and a subjective level of information (R2 = 0.414, F(13, 124) = 6.936, p &le; 0.001). DSB was associated with a diagnosis of CF and COVID-19-related fear (R2 = 0.196, F(13, 124) = 3.169, p &le; 0.001). The data suggest that pwCF show functional and adequate behaviors towards the risk caused by the pandemic. Therefore, functional coping behaviors may provide advantages in addressing pandemic challenges