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Abstract Fatigue is prevalent in immune-mediated inflammatory and neurodegenerative diseases, yet its assessment relies largely on patient-reported outcomes, which capture perception but not fluctuations over time. Wearable sensors, like inertial measurement units (IMUs), offer a way to monitor daily activities and evaluate functional capacity. This study investigates the relationship between sit-to-stand and stand-to-sit transitions and self-reported physical and mental fatigue in participants with Parkinson’s, Huntington’s, rheumatoid arthritis, systemic lupus erythematosus, primary Sjögren’s syndrome and inflammatory bowel disease. Over 4 weeks, participants wore an IMU and reported fatigue levels four times daily. Using mixed-effects models, associations were identified between fatigue and specific kinematic features, such as 5th and 95th percentiles of sit-to-stand performance, suggesting that fatigue alters the control and effort of movement. These kinematic features show promise as indicators for fatigue in these patient populations.

Abstract Background Cancer is the second most common cause of death in Germany, and treatment in certified cancer networks is recommended to ensure high-quality care. This study sought to (1) determine the percentage of all primary tumors that might potentially have been treated in certified cancer networks and (2) assess the development and current state of quality-assured cancer care for all cancer patients from a locally defined region in Upper Franconia, Germany. Methods This study was a population-centered retrospective cohort analysis based on data from the Bavarian Cancer Registry (2017–2023). First, we determined all potentially available cancer network certifications and calculated the percentage of cancer care that could potentially have been conducted in certified cancer networks. Second, we considered the certification status of the involved healthcare providers and analyzed whether or not cancer care was actually carried out in certified cancer networks. Results Overall, 90.1% (62,119/68,973) of all primary tumors, from a total of 63,372 patients, might potentially have been treated in certified cancer networks. The percentage of patients actually receiving care in certified cancer center networks was 40.7% for initial diagnosis, 59.0% for surgery, 53.2% for chemotherapy, and 50.7% for radiotherapy; the weighted mean was 50.3%. The results thus ranged between 46.9% (2023) and 52.8% (2022). The highest proportions of patients who received quality-assured treatment in certified cancer center networks were determined for breast cancer (79.5%), colon cancer (73.1%), and lymphoma (60.1%); in contrast, the lowest results were shown for lung cancer (2.7%), anal cancer (0.0%), and mesothelioma (0.0%). Female patients as well as younger patients were significantly more likely to receive care in certified care networks compared with their counterparts. In addition, we did not find a clear trend whether patients in different tumor stages were more or less likely to receive care in certified care networks. Conclusions We found meaningful differences in the proportion of patients who received quality-assured treatment in certified cancer center networks. Following this, patients should receive comprehensive information about receiving care in certified cancer center networks and consider longer travel distances, especially for those cancer types without locally available certified cancer networks.

Abstract Background Well-trained public health professionals are key to addressing both global and local public health challenges of the twenty-first century. Though availability of programs has increased, the population health science (PHS) and public health (PH) higher education landscape in Germany remains scattered. To date, no comprehensive overview of programs exists. Objectives This study aimed to map PHS and PH master’s and structured doctoral programs in Germany, including selected program characteristics, curricula and target competencies. Methods We conducted a systematic mapping of PHS and PH programs in Germany following a prospectively registered protocol ( https://doi.org/10.17605/OSF.IO/KTCBA ). Relevant master’s and doctoral programs were identified by two study authors independently searching a comprehensive higher education database, which was, for doctoral programs, supplemented with a google search. For PHS programs, general characteristics were mapped and for the subset of PH programs, in-depth characteristics were extracted. Results Overall, 75 master’s and 18 structured doctoral PHS programs were included. Of these, 23 master’s and 8 doctoral programs focused specifically on PH. The majority of PHS master’s programs awarded a Master of Science degree (55 out of 75 programs). The PH master’s program curricula offered various courses, allowing for different specializations. Courses on topics like public health, epidemiology, health systems (research) and research methods were common for the majority of the master’s programs, while courses on physical activity, behavioral science, nutrition, and mental health were offered less frequently. Structured PH doctoral programs were mainly offered by medical faculties (6 out of 8 programs) and awarded a doctorate of philosophy (Ph.D.) (6 out of 8 programs). PH doctoral programs were very heterogeneous regarding curricula, entry, and publication requirements. There was a broad geographical distribution of programs across Germany, with educational clusters in Munich, Berlin, Bielefeld and Düsseldorf. Conclusion Germany offers a diverse landscape of PHS and PH master’s programs, but only few structured doctoral programs. The variety of mandatory courses and competencies in these programs reflect Germany’s higher education system’s answer to the evolving demands of the PH sector. This review may aid in advancing PH education both in Germany and globally.

Physics-informed neural networks (PINNs) represent a significant advancement at the intersection of machine learning and physical sciences, offering a powerful framework for solving complex problems governed by physical laws. This survey provides a comprehensive review of the current state of research on PINNs, highlighting their unique methodologies, applications, challenges, and future directions. We begin by introducing the fundamental concepts underlying neural networks and the motivation for integrating physics-based constraints. We then explore various PINN architectures and techniques for incorporating physical laws into neural network training, including approaches to solving partial differential equations (PDEs) and ordinary differential equations (ODEs). Additionally, we discuss the primary challenges faced in developing and applying PINNs, such as computational complexity, data scarcity, and the integration of complex physical laws. Finally, we identify promising future research directions. Overall, this survey seeks to provide a foundational understanding of PINNs within this rapidly evolving field.

Keratinocytes (KCs) from healthy donors stimulated with type 2 cytokines are often used to experimentally study atopic dermatitis (AD) inflammatory responses. Owing to potential intrinsic alterations, it seems favorable to use KCs from patients with AD. KCs isolated from hair follicles offer a noninvasive approach to investigate AD-derived KCs. To evaluate whether such AD-derived KCs are suitable to mimic AD inflammatory responses, we compared hair follicle–derived KCs from healthy donors with those from patients with AD in a type 2 cytokine environment. Stimulation of AD-derived KCs with IL-4 and IL-13 induced higher expression changes of AD-associated markers than that of healthy KCs. The combination of IL-4 and IL-13 generally induced highest expression changes, but IL-13 alone also induced significant changes of AD-specific markers. Similar to the 2-dimensional cultures, IL-4/IL-13 stimulation of 3-dimensional skin models generated with AD-derived KCs modulated the expression of several AD-relevant factors. Whole-transcriptome analysis revealed that IL-4 and IL-13 acted similarly on these 3-dimensional skin models. Histologically, IL-13 alone and in combination with IL-4 increased epidermal spongiosis, a histological hallmark of AD skin. Taken together, our pilot study suggests that hair follicle–derived KCs from patients with AD represent a useful model system to study AD-related inflammation in a personalized in vitro model.

Background/Purpose: Informed consent is a fundamental ethical requirement in medical research, ensuring that participants have a comprehensive understanding of the risks and benefits associated with their participation. Clinical researchers must ensure effective and efficient communication of the implications of participation, but the complexity and length of traditional research consent forms can impede comprehension and create barriers to effective communication between researchers and participants. For this reason, the American Medical Association recommends a 6th grade reading level for all patient-facing medical information. Can the large language model, ChatGPT-3.5, improve readability while simultaneously preserving information necessary for adequate informed consent?. Methods: Nineteen IRB approved Orthopedic surgery research consent forms were entered into ChatGPT with instructions to make the form “readable at a 6th-grade level.” Post ChatGPT consent forms were assessed using commonly used readability metrics. Additionally, a single Orthopedic surgeon who has practiced independently for 15 years assessed the forms for accuracy and retention of imperative informed consent elements. Results: The median differences between pre-ChatGPT and post-ChatGPT were statistically significant for every readability metric (all p

As the demand for food surges and the agricultural sector undergoes a transformative shift towards sustainability and efficiency, the need for precise and proactive measures to ensure the health and welfare of livestock becomes paramount. In the egg and hatchery industry, hyperspectral imaging (HSI) has emerged as a cutting-edge, non-destructive technique for fast and accurate egg quality analysis, including detecting chick embryo mortality. However, the high cost and operational complexity compared to conventional RGB imaging are significant bottlenecks in the widespread adoption of HSI technology. To overcome these hurdles and unlock the full potential of HSI, a promising solution is hyperspectral image reconstruction from standard RGB images. This study aims to reconstruct hyperspectral images from RGB images for non-destructive early prediction of chick embryo mortality. Initially, the performance of different image reconstruction algorithms, such as HRNET, MST++, Restormer, and EDSR were compared to reconstruct the hyperspectral images of the eggs in the early incubation period. Later, the reconstructed spectra were used to differentiate live from dead embryos eggs using the XGBoost and Random Forest classification methods. Among the reconstruction methods, HRNET showed impressive reconstruction performance with MRAE of 0.0955, RMSE of 0.0159, and PSNR of 36.79 dB. This study motivated the idea that harnessing imaging technology integrated with smart sensors and data analytics has the potential to improve automation, enhance biosecurity, and optimize resource management towards sustainable agriculture 4.0.

Null hypothesis significance testing (NHST) is among the most prominent and widely used methods for analyzing data. At the same time, NHST has been criticized since many years because of misuses and misconceptions that can be found extensively in the scholarly literature. Furthermore, in recent years, NHST has been identified as one reason for the replication crisis because many studies place too much emphasis on statistical significance for drawing conclusions. As a response to those problems, calls for actions have been raised, among others by the American Statistical Association (ASA), to rectify these issues, for instance, by modifying or even abandoning NHST. In this paper, we study the reaction of the community on these discussions. Specifically, we conduct a scientometric analysis of bibliographic records to investigate the publication behavior about the usage of NHST. We conduct a trend analysis for the general community, for specific subject areas and for individual journals. Furthermore, we conduct a change-point analysis to investigate if there are continued movements or actual changes. As a result, we find that for the general community NHST is more popular than ever, however, for particular subject-areas and journals there is a clear heterogeneity and no uniform publication behavior is observable.

Abstract Background Evaluating sugar-sweetened beverage (SSB) taxation often relies on simulation models. We assess how assumptions about the response to SSB taxation affect the projected body weight change and subsequent health and economic impacts related to type 2 diabetes mellitus (T2DM) using Germany as an example. Methods In the main analysis, we estimated changes in energy intake by age and sex under a 20% value-added tax on SSBs in Germany using marginal price elasticities (PE) and applied an energy equilibrium model to predict body weight changes. We then quantified the impact of several assumption modifications: SSB own-PE adjusted for consumption (M1)/based on alternative meta-analysis (M2); SSB consumption adjusted for underreporting (M3); substitution via marginal (M4a) or adjusted (M4b) cross-PE/as % of calorie change (M4c). We also assessed scenarios with alternative tax rates of 10% (S1) or 30% (S2) and including fruit juice (S3). We calculated overweight and obesity rates per modification and scenario. We simulated the impact on T2DM, associated healthcare costs, and disability-adjusted life years (DALYs) over the lifetime of the 2011 German adult population with a Markov model. Data included official demographics, national surveys, and meta-analyses. Results A 20% value-added tax in Germany could reduce the number of men and women with obesity by 210,800 [138,800; 294,100] and 80,800 [45,100; 123,300], respectively. Over the population’s lifetime, this would lead to modest T2DM-related health and economic impacts (76,700 DALYs [42,500; 120,600] averted; €2.37 billion [1.33; 3.71] costs saved). Policy impacts varied highly across modifications (all in DALYs averted): (M1) 94,800 [51,500; 150,700]; (M2) 164,200 [99,500; 243,500]; (M3) 52,600 [22,500; 91,100]; (M4a) -18,100 [-111,500; 68,300]; (M4b) 25,800 [-31,400; 81,500]; (M4c) 46,700 [25,300; 77,200]. The variability in policy impact related to modifications was similar to the variability between alternative policy scenarios (all in DALYs averted): (S1) 26,400 [9,300; 47,600]; (S2) 126,200 [73,600; 194,500]; (S3) 342,200 [234,200; 430,400]. Conclusions Predicted body weight reductions under SSB taxation are sensitive to assumptions by researchers often needed due to data limitations. Because this variability propagates to estimates of health and economic impacts, the resulting structural uncertainty should be considered when using results in decision-making.

Abstract Background Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. Methods Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren’s syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. Results Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. Conclusions Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.

Abstract The success of the conversational AI system ChatGPT has triggered an avalanche of studies that explore its applications in research and education. There are also high hopes that, in addition to such particular usages, it could lead to artificial general intelligence (AGI) that means to human-level intelligence. Such aspirations, however, need to be grounded by actual scientific means to ensure faithful statements and evaluations of the current situation. The purpose of this article is to put ChatGPT into perspective and to outline a way forward that might instead lead to an artificial special intelligence (ASI), a notion we introduce. The underlying idea of ASI is based on an environment that consists only of text. We will show that this avoids the problem of embodiment of an agent and leads to a system with restricted capabilities compared to AGI. Furthermore, we discuss gated actions as a means of large language models to moderate ethical concerns.

Abstract Many applications require diagnostics that can quantify the distribution of chemical gas species and gas temperature along a single line-of-sight, which is challenging in process environments with limited optical access. To this end, we present an approach that combines time-of-flight Light Detection and Ranging (LiDAR) with Tunable Diode Laser Absorption Spectroscopy (TDLAS) to scan individual gas molecular transition lines. This method is applicable in situations where scattering objects are distributed along the beam path, such as solid fuel combustion, or when dealing with multiple gas volumes separated by weakly reflecting windows. The approach is demonstrated through simulation studies and an initial experimental proof of concept for separated gas volumes.

Abstract Upon implanting tissue-engineered heart valves (TEHVs), blood-derived macrophages are believed to orchestrate the remodeling process. They initiate the immune response and mediate the remodeling of the TEHV, essential for the valve’s functionality. The exact role of another macrophage type, the tissue-resident macrophages (TRMs), has not been yet elucidated even though they maintain the homeostasis of native tissues. Here, we characterized the response of hTRM-like cells in contact with a human tissue engineered matrix (hTEM). HTEMs comprised intracellular peptides with potentially immunogenic properties in their ECM proteome. Human iPSC-derived macrophages (iMφs) could represent hTRM-like cells in vitro and circumvent the scarcity of human donor material. iMφs were derived and after stimulation they demonstrated polarization towards non-/inflammatory states. Next, they responded with increased IL-6/IL-1β secretion in separate 3/7-day cultures with longer production-time-hTEMs. We demonstrated that iMφs are a potential model for TRM-like cells for the assessment of hTEM immunocompatibility. They adopt distinct pro- and anti-inflammatory phenotypes, and both IL-6 and IL-1β secretion depends on hTEM composition. IL-6 provided the highest sensitivity to measure iMφs pro-inflammatory response. This platform could facilitate the in vitro immunocompatibility assessment of hTEMs and thereby showcase a potential way to achieve safer clinical translation of TEHVs.

Extensive nutritional analyses were conducted for palm kernel meal (PKM) sourced from 5 countries. Two precision-fed rooster trials were conducted to evaluate the nitrogen-corrected true metabolizable energy (TMEn) and standardized amino acid (AA) digestibility of 10 PKM samples (PKM 1 to 10). The TMEn was determined using conventional Single Comb White Leghorn roosters, and standardized AA digestibility was determined using cecectomized roosters. Roosters were fasted for 26 h prior to crop intubation with 25 g of each PKM. Excreta were then collected for 48 h post-intubation and freeze dried for analysis. Statistical analyses were conducted using a one-way ANOVA for a completely randomized design. The least significant difference test was conducted to determine if differences between or among individual treatments were significant at P < 0.05. The PKM samples were found to have an average (DM basis) of 14% CP, 7.5 % fat, and 64% neutral detergent fiber, 0.4% Ca, 0.7% P, and 1.3% phytic acid. Average TMEn for PKM samples was 2082 kcal/kg (DM basis)(range was 1,644 to 2,511). Average Lys, Met, Cys, and Thr digestibility values (%), with ranges in parentheses, for PKM samples were 47 (34 to 60), 73 (66 to 80), 47 (29 to 58), and 65 (54 to 77), respectively. The PKM samples contained highly variable levels of TMEn and digestible AA within and among countries. Nutrient composition also varied substantially among PKM samples.

Introduction To examine the long-term health and economic impact of a lifestyle diabetes prevention program in people with high risk of developing type 2 diabetes in Germany.Research design and methods We assessed the lifetime cost-effectiveness of a 2-year pragmatic lifestyle program for preventing type 2 diabetes targeting German adults aged 35–54 and 55–74 years old with hemoglobin A1c (HbA1c) from 6.0% to 6.4%. We used the Centers for Disease Control and Prevention RTI Diabetes Cost-Effectiveness Model to run a simulation on the program effectiveness. We estimated incremental health benefits in quality-adjusted life years (QALYs) and costs using an established simulation model adapted to the German context, from a healthcare system and societal perspective. The cost-effectiveness of the program was measured by incremental cost-effectiveness ratios (ICERs) in cost per QALY. We projected the number of type 2 diabetes cases prevented by participation rate if the program was implemented nationwide.Results The lifestyle program would result to more QALYs and higher costs. The lifetime ICERs were 14 690€ (35–54 years old) and 14 372€ (55–74 years old) from a healthcare system perspective and cost saving (ICER=−3805€) and cost-effective (ICER=4579€), respectively, from a societal perspective. A total of 10 527 diabetes cases would be prevented over lifetime if the program was offered to all eligible people nationwide and 25% of those would participate in the program.Conclusions Implementing the lifestyle intervention for people with HbA1c from 6.0% to 6.4% could be a cost-effective at standard willingness to pay level strategy for type 2 diabetes prevention. The intervention in the younger cohort could be cost saving from a societal perspective. The successful implementation of a lifestyle-based diabetes prevention program could be an important component of a successful National Diabetes Strategy in Germany.

IntroductionAlthough cardiovascular surgery societies in Europe and the USA constantly strive for the exchange of knowledge and best practices in coronary artery bypass grafting (CABG), the available evidence on whether such efforts result in similar patient outcomes is limited. Therefore, in the present analysis, we sought to compare patient profiles and overall survival outcomes for up to 3 years between large European and US patient cohorts who underwent isolated CABG.MethodsPatients from the European DuraGraft Registry (n = 2,522) who underwent isolated CABG at 45 sites in eight different European countries between 2016 and 2019 were compared to randomly selected patients from the US STS database who were operated during the same period (n = 294,725). Free conduits (venous and arterial grafts) from the DuraGraft Registry patients were intraoperatively stored in DuraGraft, an endothelial damage inhibitor, before anastomosis, whereas grafts from the STS Registry patients in standard-of-care solutions (e.g., saline). Propensity score matching (PSM) models were used to account for differences in patient baseline and surgical characteristics, using a primary PSM with 35 variables (2,400 patients matched) and a secondary PSM with 25 variables (2,522 patients matched, sensitivity analysis). The overall survival for up to 3 years after CABG was assessed as the primary endpoint.ResultsThe comparison of patient profiles showed significant differences between the European and US cohorts. The European patients had more left main disease, underwent more off-pump CABG, and received more arterial grafts together with more complete arterial grafting procedures. In contrast, the US patients received more distal anastomoses with more saphenous vein grafts (SVGs) that were mainly harvested endoscopically. Such differences, however, were well balanced after PSM for the mortality comparison. Mortality comparison at 30 days, 12 months, and 24 months between the European and US patients was 2.38% vs. 1.96%, 4.32% vs. 4.79%, and 5.38% vs. 6.96%, respectively. At 36 months, the mortality was significantly lower in the European patients than that of their US counterparts (7.37% vs. 9.65%; p-value = 0.016). The estimated hazard ratio (HR) was 1.29 (95% CI 1.05–1.59).ConclusionThis large-scale transatlantic comparative analysis shows that there are some significant differences in patient profiles between large cohorts of European and US patients. These differences were adjusted by using PSM for the mortality analysis. No significant difference in mortality was detected between groups through 2 years, but survival was significantly better in the European DuraGraft Registry patients at 3 years post-CABG.

ABSTRACT Single-rule management is often adopted for various tropical forest timber species due to limited knowledge on species-specific growth and the relationship between logging intensity and recovery time. This study provides information to support sustainable management of Goupia glabra by simulating its wood stock recovery over a 35-year period following logging using data from six areas in the Brazilian Amazon. Monitoring periods after the first harvest cycle varyed from 16 to 29 years, and logging intensity from 0.000 to 0.696 m² ha-1. Tree density of G. glabra varied from 0 to 22 trees ha-1 and dominance from 0.00 to 7.39 m² ha-¹. Frequency of tree diameters was almost evenly distributed across diameter classes, slightly higher in the first (20-30 cm) class. These parameters generated estimations of recovery rate from 12 to 85%, showing that 35 years is insufficient for trees with DBH ≥ 20 cm in all study areas to grow and replace the stock of trees with DBH ≥ 50 cm harvested during the first cycle. Minimum recovery periods from 48 to 83 years were estimated to guarantee the recovery of the wood stock in the study areas. These findings reinforce the need to adapt management rules according to the population dynamics of each timber species and each logging area, and suggest the need for changes in the current legal requirements that define forest management in the Amazon.

Abstract Background People with opioid use disorder have substantially higher standardised mortality rates compared to the general population; however, lack of clear individual prognostic information presents challenges to prioritise or target interventions within drug treatment services. Previous prognostic models have been developed to estimate the risk of developing opioid use disorder and opioid-related overdose in people routinely prescribed opioids but, to our knowledge, none have been developed to estimate mortality risk in people accessing drug services with opioid use disorder. Initial presentation to drug services is a pragmatic time to evaluate mortality risk given the contemporaneous routine collection of prognostic indicators and as a decision point for appropriate service prioritisation and targeted intervention delivery. This study aims to develop and internally validate a model to estimate 6-month mortality risk for people with opioid use disorder from prognostic indicators recorded at initial assessment in drug services in England. Methods An English national dataset containing records from individuals presenting to drug services between 1 April 2013 and 1 April 2023 (n > 800,000) (the National Drug Treatment Monitoring System (NDTMS)) linked to their lifetime hospitalisation and death records (Hospital Episode Statistics-Office of National Statistics (HES-ONS)). Twelve candidate prognostic indicator variables were identified based on literature review of demographic and clinical features associated with increased mortality for people in treatment for opioid use disorder. Variables will be extracted at initial presentation to drug services with mortality measured at 6 months. Two multivariable Cox regression models will be developed one for 6-month all-cause mortality and one for 6-month drug-related mortality using backward elimination with a fractional polynomial approach for continuous variables. Internal validation will be undertaken using bootstrapping methods. Discrimination of both models will be reported using Harrel’s c and d-statistics. Calibration curves and slopes will be presented comparing expected and observed event rates. Discussion The models developed and internally validated in this study aim to improve clinical assessment of mortality risk for people with opioid use disorder presenting to drug services in England. External validation in different populations will be required to develop the model into a tool to assist future clinical decision-making.

Introduction: Skin cancer is often fatal, which motivates new therapy avenues. Recent advances in cancer treatment are indicative of the importance of combination treatments in oncology. Previous studies have identified small molecule-based therapies and redox-based technologies, including photodynamic therapy or medical gas plasma, as promising candidates to target skin cancer. Objective: We aimed to identify effective combinations of experimental small molecules with cold gas plasma for therapy in dermato-oncology. Methods: Promising drug candidates were identified after screening an in-house 155-compound library using 3D skin cancer spheroids and high content imaging. Combination effects of selected drugs and cold gas plasma were investigated with respect to oxidative stress, invasion, and viability. Drugs that had combined well with cold gas plasma were further investigated in vascularized tumor organoids in ovo and a xenograft mouse melanoma model in vivo. Results: The two chromone derivatives Sm837 and IS112 enhanced cold gas plasma-induced oxidative stress, including histone 2A.X phosphorylation, and further reduced proliferation and skin cancer cell viability. Combination treatments of tumor organoids grown in ovo confirmed the principal anti-cancer effect of the selected drugs. While one of the two compounds exerted severe toxicity in vivo, the other (Sm837) resulted in a significant synergistic anti-tumor toxicity at good tolerability. Principal component analysis of protein phosphorylation profiles confirmed profound combination treatment effects in contrast to the monotherapies. Conclusion: We identified a novel compound that, combined with topical cold gas plasma-induced oxidative stress, represents a novel and promising treatment approach to target skin cancer.

Background: Fatigue is a prominent symptom in many diseases and is strongly associated with impaired daily function. The measurement of daily function is currently almost always done with questionnaires, which are subjective and imprecise. With the recent advances of digital wearable technologies, novel approaches to evaluate daily function quantitatively and objectively in real-life conditions are increasingly possible. This also creates new possibilities to measure fatigue-related changes of daily function using such technologies. Summary: This review examines which digitally assessable parameters in immune-mediated inflammatory and neurodegenerative diseases may have the greatest potential to reflect fatigue-related changes of daily function. Key Messages: Results of a standardized analysis of the literature reporting about perception-, capacity-, and performance-evaluating assessment tools indicate that changes of the following parameters: physical activity, independence of daily living, social participation, working life, mental status, cognitive and aerobic capacity, and supervised and unsupervised mobility performance have the highest potential to reflect fatigue-related changes of daily function. These parameters thus hold the greatest potential for quantitatively measuring fatigue in representative diseases in real-life conditions, e.g., with digital wearable technologies. Furthermore, to the best of our knowledge, this is a new approach to analysing evidence for the design of performance-based digital assessment protocols in human research, which may stimulate further systematic research in this area.

Abstract The accurate determination of the size and depth of infiltration is critical to the treatment and excision of melanoma and other skin cancers. However, current techniques, such as skin biopsy and histological examination, pose invasiveness, time-consumption, and have limitations in measuring at the deepest level. Non-invasive imaging techniques like dermoscopy and confocal microscopy also present limitations in accurately capturing contrast and depth information for various skin types and lesion locations. Thus, there is a pressing need for non-invasive devices capable of obtaining high-resolution 3D images of skin lesions. In this study, we introduce a novel device that combines 18 MHz ultrasound and photoacoustic tomography into a single unit, enabling the acquisition of colocalized 3D images of skin lesions. We performed in vivo measurements on 25 suspicious human skin nevi that were promptly excised following measurements. The combined ultrasound/photoacoustic tomography imaging technique exhibited a strong correlation with histological Breslow thickness between 0.2 and 3 mm, achieving a coefficient of determination (R $$^2$$ 2 ) of 0.93, which is superior to the coefficients from the individual modalities. The results procured in our study underscore the potential of combined ultrasound and photoacoustic tomography as a promising non-invasive 3D imaging approach for evaluating human nevi and other skin lesions. Furthermore, the system allows for integration of other optical modalities such as optical coherence tomography, microscopy, or Raman spectroscopy in future applications.

Abstract Numerous genetic and epidemiologic studies have demonstrated an association between elevated levels of lipoprotein(a) (Lp[a]) and cardiovascular disease. As a result, lowering Lp(a) levels is widely recognized as a promising strategy for reducing the risk of new-onset coronary heart disease, stroke, and heart failure. Lp(a) consists of a low-density lipoprotein-like particle with covalently linked apolipoprotein A (apo[a]) and apolipoprotein B-100, which explains its pro-thrombotic, pro-inflammatory, and pro-atherogenic properties. Lp(a) serum concentrations are genetically determined by the apo(a) isoform, with shorter isoforms having a higher rate of particle synthesis. To date, there are no approved pharmacological therapies that effectively reduce Lp(a) levels. Promising treatment approaches targeting apo(a) expression include RNA-based drugs such as pelacarsen, olpasiran, SLN360, and lepodisiran, which are currently in clinical trials. In this comprehensive review, we provide a detailed overview of RNA-based therapeutic approaches and discuss the recent advances and challenges of RNA therapeutics specifically designed to reduce Lp(a) levels and thus the risk of cardiovascular disease.