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Background: Telemedicine remains an underused tool in rural emergency medical servces (EMS) systems. Rural emergency medical technicians (EMT) and paramedics cite concerns that telemedicine could increase Advanced Life Support (ALS) transports, extend on-scene times, and face challenges related to connectivity as barriers to implementation. Our aim in this project was to implement a telemedicine system in a rural EMS setting and assess the impact of telemedicine on EMS management of patients with chest pain while evaluating some of the perceived barriers.Methods: This study was a mixed-methods, retrospective review of quality assurance data collected prior to and after implementation of a telemedicine program targeting patients with chest pain. We compared quantitative data from the 12-month pre-implementation phase to data from 15 months post-implementation. Patients were included if they had a chief complaint of chest pain or a 12-lead electrocardiogram had been obtained. The primary outcome was the rate of ALS transport before and after program implementation. Secondary outcomes included EMS call response times and EMS agency performance on quality improvement benchmarks. Qualitative data were also collected after each telemedicine encounter to evaluate paramedic/EMT and EMS physician perception of call quality.Results: The telemedicine pilot project was implemented in September 2020. Overall, there were 58 successful encounters. For this analysis, we included 38 patients in both the pre-implementation period (September 9, 2019–September 10, 2020) and the post-implementation period (September 11, 2020–December 5, 2021). Among this population, the ALS transport rate was 42% before and 45% after implementation (odds ratio 1.11; 95% confidence interval 0.45–2.76). The EMS median out-of-service times were 47 minutes before, and 33 minutes after (P = 0.07). Overall, 64% of paramedics/EMTs and 89% of EMS physicians rated the telemedicine call quality as “good.”Conclusion: In this rural EMS system, a telehealth platform was successfully used to connect paramedics/EMTs to board-certified EMS physicians over a 15-month period. Telemedicine use did not alter rates of ALS transports and did not increase on-scene time. The majority of paramedics/EMTs and EMS physicians rated the quality of the telemedicine connection as “good.”

There is growing awareness of the unique etiology, biology, and clinical presentation of invasive lobular breast cancer (ILC), but additional research is needed to ensure translation of findings into management and treatment guidelines. We conducted a survey with input from breast cancer physicians, laboratory-based researchers, and patients to analyze the current understanding of ILC, and identify consensus research questions. 1774 participants from 66 countries respondents self-identified as clinicians (N = 413), researchers (N = 376), and breast cancer patients and advocates (N = 1120), with some belonging to more than one category. The majority of physicians reported being very/extremely (41%) to moderately (42%) confident in describing the differences between ILC and invasive breast cancer of no special type (NST). Knowledge of histology was seen as important (73%) and as affecting treatment decisions (51%), and most agreed that refining treatment guidelines would be valuable (76%). 85% of clinicians have never powered a clinical trial to allow subset analysis for histological subtypes, but the majority would consider it, and would participate in an ILC clinical trials consortium. The majority of laboratory researchers, reported being and very/extremely (48%) to moderately (29%) confident in describing differences between ILC and NST. They reported that ILCs are inadequately presented in large genomic data sets, and that ILC models are insufficient. The majority have adequate access to tissue or blood from patients with ILC. The majority of patients and advocates (52%) thought that their health care providers did not sufficiently explain the unique features of ILC. They identified improvement of ILC screening/early detection, and identification of better imaging tools as top research priorities. In contrast, both researchers and clinicians identified understanding of endocrine resistance and identifying novel drugs that can be tested in clinical trials as top research priority. In summary, we have gathered information from an international community of physicians, researchers, and patients/advocates that we expect will lay the foundation for a community-informed collaborative research agenda, with the goal of improving management and personalizing treatment for patients with ILC.

Current global reanalyses show marked discrepancies in snow mass and snow cover extent for the Northern Hemisphere. Here, benchmark snow datasets are produced by driving a simple offline snow model, the Brown Temperature Index Model (B-TIM), with temperature and precipitation from three reanalyses. The B-TIM offline snow performs comparably to or better than online (coupled land–atmosphere) reanalysis snow when evaluated against in situ snow measurements. Sources of discrepancy in snow climatologies, which are difficult to isolate when comparing online reanalysis snow products amongst themselves, are partially elucidated by separately bias-adjusting temperature and precipitation in the B-TIM. Interannual variability in snow mass and snow spatial patterns is far more self-consistent amongst offline B-TIM snow products than amongst online reanalysis snow products, and the self-consistent products are more similar to in situ observations, as evaluated in a validation study. Specific artifacts related to temporal inhomogeneity in snow data assimilation are revealed in the analysis. The B-TIM, released here as an open-source, self-contained Python package, provides a simple benchmarking tool for future updates to more sophisticated online and offline snow datasets.

The Arctic poses many challenges for Earth system and snow physics models, which are commonly unable to simulate crucial Arctic snowpack processes,such as vapour gradients and rain-on-snow-induced ice layers. These limitations raise concerns about the current understanding of Arctic warming and its impact on biodiversity, livelihoods, permafrost, and the global carbon budget. Recognizing that models are shaped by human choices, 18 Arctic researchers were interviewed to delve into the decision-making process behind model construction. Although data availability, issues of scale, internal model consistency, and historical and numerical model legacies were cited as obstacles to developing an Arctic snowpack model, no opinion was unanimous. Divergences were not merely scientific disagreements about the Arctic snowpack but reflected the broader research context. Inadequate and insufficient resources, partly driven by short-term priorities dominating research landscapes, impeded progress. Nevertheless, modellers were found to be both adaptable to shifting strategic research priorities – an adaptability demonstrated by the fact that interdisciplinary collaborations were the key motivation for model development – and anchored in the past. This anchoring and non-epistemic values led to diverging opinions about whether existing models were “good enough” and whether investing time and effort to build a new model was a useful strategy when addressing pressing research challenges. Moving forward, we recommend that both stakeholders and modellers be involved in future snow model intercomparison projects in order to drive developments that address snow model limitations currently impeding progress in various disciplines. We also argue for more transparency about the contextual factors that shape research decisions. Otherwise, the reality of our scientific process will remain hidden, limiting the changes necessary to our research practice.

Background: Telemedicine remains an underused tool in rural emergency medical servces (EMS) systems. Rural emergency medical technicians (EMT) and paramedics cite concerns that telemedicine could increase Advanced Life Support (ALS) transports, extend on-scene times, and face challenges related to connectivity as barriers to implementation. Our aim in this project was to implement a telemedicine system in a rural EMS setting and assess the impact of telemedicine on EMS management of patients with chest pain while evaluating some of the perceived barriers. Methods: This study was a mixed-methods, retrospective review of quality assurance data collected prior to and after implementation of a telemedicine program targeting patients with chest pain. We compared quantitative data from the 12-month pre-implementation phase to data from 15 months post-implementation. Patients were included if they had a chief complaint of chest pain or a 12-lead electrocardiogram had been obtained. The primary outcome was the rate of ALS transport before and after program implementation. Secondary outcomes included EMS call response times and EMS agency performance on quality improvement benchmarks. Qualitative data were also collected after each telemedicine encounter to evaluate paramedic/EMT and EMS physician perception of call quality. Results: The telemedicine pilot project was implemented in September 2020. Overall, there were 58 successful encounters. For this analysis, we included 38 patients in both the pre-implementation period (September 9, 2019–September 10, 2020) and the post-implementation period (September 11, 2020–December 5, 2021). Among this population, the ALS transport rate was 42% before and 45% after implementation (odds ratio 1.11; 95% confidence interval 0.45–2.76). The EMS median out-of-service times were 47 minutes before, and 33 minutes after (P = 0.07). Overall, 64% of paramedics/EMTs and 89% of EMS physicians rated the telemedicine call quality as “good.” Conclusion: In this rural EMS system, a telehealth platform was successfully used to connect paramedics/EMTs to board-certified EMS physicians over a 15-month period. Telemedicine use did not alter rates of ALS transports and did not increase on-scene time. The majority of paramedics/EMTs and EMS physicians rated the quality of the telemedicine connection as “good.”

Accurate snow information at high spatial and temporal resolution is needed to support climate services, water resource management, and environmental prediction services. However, snow remains the only element of the water cycle without a dedicated Earth observation mission. The snow scientific community has shown that Ku-band radar measurements provide quality snow information with its sensitivity to snow water equivalent and the wet/dry state of snow. With recent developments of tools like the snow micropenetrometer (SMP) to retrieve snow microstructure data in the field and radiative transfer models like the Snow Microwave Radiative Transfer (SMRT) model, it becomes possible to properly characterize the snow and how it translates into radar backscatter measurements. An experiment at Trail Valley Creek (TVC), Northwest Territories, Canada, was conducted during the winter of 2018/19 in order to characterize the impacts of varying snow geophysical properties on Ku-band radar backscatter at a 100 m scale. Airborne Ku-band data were acquired using the University of Massachusetts radar instrument. This study shows that it is possible to calibrate SMP data to retrieve statistical information on snow geophysical properties and properly characterize a representative snowpack at the experiment scale. The tundra snowpack measured during the campaign can be characterize by two layers corresponding to a rounded snow grain layer and a depth hoar layer. Using RADARSAT-2 and TerraSAR-X data, soil background roughness properties were retrieved (msssoil=0.010±0.002), and it was shown that a single value could be used for the entire domain. Microwave snow grain size polydispersity values of 0.74 and 1.11 for rounded and depth hoar snow grains, respectively, were retrieved. Using the geometrical optics surface backscatter model, the retrieved effective soil permittivity increased from C-band (εsoil=2.47) to X-band (εsoil=2.61) and to Ku-band (εsoil=2.77) for the TVC domain. Using the SMRT and the retrieved soil and snow parameterizations, an RMSE of 2.6 dB was obtained between the measured and simulated Ku-band backscatter values when using a global set of parameters for all measured sites. When using a distributed set of soil and snow parameters, the RMSE drops to 0.9 dB. This study thus shows that it is possible to link Ku-band radar backscatter measurements to snow conditions on the ground using a priori knowledge of the snow conditions to retrieve snow water equivalent (SWE) at the 100 m scale.

Abstract The quick Sequential Organ Failure Assessment (qSOFA) system identifies an individual’s risk to progress to poor sepsis-related outcomes using minimal variables. We used Support Vector Machine, Learning Using Concave and Convex Kernels, and Random Forest to predict an increase in qSOFA score using electronic health record (EHR) data, electrocardiograms (ECG), and arterial line signals. We structured physiological signals data in a tensor format and used Canonical Polyadic/Parallel Factors (CP) decomposition for feature reduction. Random Forests trained on ECG data show improved performance after tensor decomposition for predictions in a 6-h time frame (AUROC 0.67 ± 0.06 compared to 0.57 ± 0.08, $$p = 0.01$$ p = 0.01 ). Adding arterial line features can also improve performance (AUROC 0.69 ± 0.07, $$p < 0.01$$ p < 0.01 ), and benefit from tensor decomposition (AUROC 0.71 ± 0.07, $$p = 0.01$$ p = 0.01 ). Adding EHR data features to a tensor-reduced signal model further improves performance (AUROC 0.77 ± 0.06, $$p < 0.01$$ p < 0.01 ). Despite reduction in performance going from an EHR data-informed model to a tensor-reduced waveform data model, the signals-informed model offers distinct advantages. The first is that predictions can be made on a continuous basis in real-time, and second is that these predictions are not limited by the availability of EHR data. Additionally, structuring the waveform features as a tensor conserves structural and temporal information that would otherwise be lost if the data were presented as flat vectors.

Abstract Opioid withdrawal is a liability of chronic opioid use and misuse, impacting people who use prescription or illicit opioids. Hyperactive autonomic output underlies many of the aversive withdrawal symptoms that make it difficult to discontinue chronic opioid use. The locus coeruleus (LC) is an important autonomic centre within the brain with a poorly defined role in opioid withdrawal. We show here that pannexin-1 (Panx1) channels expressed on microglia critically modulate LC activity during opioid withdrawal. Within the LC, we found that spinally projecting tyrosine hydroxylase (TH)-positive neurons (LCspinal) are hyperexcitable during morphine withdrawal, elevating cerebrospinal fluid (CSF) levels of norepinephrine. Pharmacological and chemogenetic silencing of LCspinal neurons or genetic ablation of Panx1 in microglia blunted CSF NE release, reduced LC neuron hyperexcitability, and concomitantly decreased opioid withdrawal behaviours in mice. Using probenecid as an initial lead compound, we designed a compound (EG-2184) with greater potency in blocking Panx1. Treatment with EG-2184 significantly reduced both the physical signs and conditioned place aversion caused by opioid withdrawal in mice, as well as suppressed cue-induced reinstatement of opioid seeking in rats. Together, these findings demonstrate that microglial Panx1 channels modulate LC noradrenergic circuitry during opioid withdrawal and reinstatement. Blocking Panx1 to dampen LC hyperexcitability may therefore provide a therapeutic strategy for alleviating the physical and aversive components of opioid withdrawal.

Abstract The healthy lifestyle index (HLI), defined as the unweighted sum of individual lifestyle components, was used to investigate the combined role of lifestyle factors on health-related outcomes. We introduced weighted outcome-specific versions of the HLI, where individual lifestyle components were weighted according to their associations with disease outcomes. Within the European Prospective Investigation into Cancer and Nutrition (EPIC), we examined the association between the standard and the outcome-specific HLIs and the risk of T2D, CVD, cancer, and all-cause premature mortality. Estimates of the hazard ratios (HRs), the Harrell’s C-index and the population attributable fractions (PAFs) were compared. For T2D, the HR for 1-SD increase of the standard and T2D-specific HLI were 0.66 (95% CI: 0.64, 0.67) and 0.43 (0.42, 0.44), respectively, and the C-index were 0.63 (0.62, 0.64) and 0.72 (0.72, 0.73). Similar, yet less pronounced differences in HR and C-index were observed for standard and outcome-specific estimates for cancer, CVD and all-cause mortality. PAF estimates for mortality before age 80 were 57% (55%, 58%) and 33% (32%, 34%) for standard and mortality-specific HLI, respectively. The use of outcome-specific HLI could improve the assessment of the role of lifestyle factors on disease outcomes, thus enhancing the definition of public health recommendations.

Abstract There is growing awareness of the unique etiology, biology, and clinical presentation of invasive lobular breast cancer (ILC), but additional research is needed to ensure translation of findings into management and treatment guidelines. We conducted a survey with input from breast cancer physicians, laboratory-based researchers, and patients to analyze the current understanding of ILC, and identify consensus research questions. 1774 participants from 66 countries respondents self-identified as clinicians (N = 413), researchers (N = 376), and breast cancer patients and advocates (N = 1120), with some belonging to more than one category. The majority of physicians reported being very/extremely (41%) to moderately (42%) confident in describing the differences between ILC and invasive breast cancer of no special type (NST). Knowledge of histology was seen as important (73%) and as affecting treatment decisions (51%), and most agreed that refining treatment guidelines would be valuable (76%). 85% of clinicians have never powered a clinical trial to allow subset analysis for histological subtypes, but the majority would consider it, and would participate in an ILC clinical trials consortium. The majority of laboratory researchers, reported being and very/extremely (48%) to moderately (29%) confident in describing differences between ILC and NST. They reported that ILCs are inadequately presented in large genomic data sets, and that ILC models are insufficient. The majority have adequate access to tissue or blood from patients with ILC. The majority of patients and advocates (52%) thought that their health care providers did not sufficiently explain the unique features of ILC. They identified improvement of ILC screening/early detection, and identification of better imaging tools as top research priorities. In contrast, both researchers and clinicians identified understanding of endocrine resistance and identifying novel drugs that can be tested in clinical trials as top research priority. In summary, we have gathered information from an international community of physicians, researchers, and patients/advocates that we expect will lay the foundation for a community-informed collaborative research agenda, with the goal of improving management and personalizing treatment for patients with ILC.

The generation of photogrammetric point clouds from satellite images is often based on image correlation techniques. Correlation errors can arise for a wide variety of reasons: transient objects, homogeneous areas, shadows, and surface discontinuities. Therefore, a simple 3D Gaussian distribution at the point cloud level is not an appropriate model. In this paper, we propose a new point cloud denoising method integrated into the Multiview Stereo Pipeline CARS, dedicated to satellite imagery. Building upon bilateral filtering principles, our approach introduces a novel utilization of color information, confidence estimation and geometric constraints alongside point positions and normals. While the use of point color increases the level of detail, the addition of geometric constraints and confidence awareness guides processing towards a realistic solution. We propose an ablation study and compare our solution against a previously established bilateral filter with LiDAR data as ground truth.

Abstract Background Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions. Results As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes. Conclusions This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools. Graphical Abstract

Abstract Dense and aligned Collagen I fibers are associated with collective cancer invasion led by protrusive tumor cells, leader cells. In some breast tumors, a population of cancer cells (basal-like cells) maintain several epithelial characteristics and express the myoepithelial/basal cell marker Keratin 14 (K14). Emergence of leader cells and K14 expression are regarded as interconnected events triggered by Collagen I, however the underlying mechanisms remain unknown. Using breast carcinoma organoids, we show that Collagen I drives a force-dependent loop, specifically in basal-like cancer cells. The feed-forward loop is centered around the mechanotransducer Yap and independent of K14 expression. Yap promotes a transcriptional program that enhances Collagen I alignment and tension, which further activates Yap. Active Yap is detected in invading breast cancer cells in patients and required for collective invasion in 3D Collagen I and in the mammary fat pad of mice. Our work uncovers an essential function for Yap in leader cell selection during collective cancer invasion.

Interdisciplinary project teams are increasingly vital in organizations that are focused on providing successful technical solutions that include a positive user experience. In response to the need for experience in this area, some higher education institutions have created interdisciplinary project-based experiential learning opportunities. In this research, we examine an interdisciplinary computing capstone course and present results from a qualitative study of student participants. We investigate how teams in an interdisciplinary capstone course self-organize, what convictions drive these decisions, and how they assess and value the expected contributions from disciplines other than their own. We analyze students' attitudes, beliefs, and motivations as gleaned from interviews and offer suggested improvement strategies for future interdisciplinary capstone courses.

BackgroundEpilepsy management during pregnancy is crucial for both the mother and fetus. The use of antiseizure medications (ASMs) during pregnancy requires careful consideration due to their potential effects on maternal and fetal health.MethodsThis study analyzed trends in ASMs use among pregnant people in four Canadian provinces over 20 years (Manitoba, Saskatchewan, Alberta, and Quebec). Descriptive statistics were utilized to examine the characteristics of the population, with the frequency and patterns of ASM use estimated throughout each trimester. Linear regression models were developed to analyze yearly patterns of ASM utilization for the overall study population, as well as for people with and without epilepsy.ResultsAmong 1,317,141 pregnant individuals across four provinces, 0.7% had epilepsy. Of the total pregnancies, 1.7% (n = 22,783) were exposed to ASMs, comprising 4,392 from pregnant people with epilepsy (PPWE) and 18,391 from those without epilepsy (PPWOE). Results demonstrated varying trends in ASM usage between provinces, with an overall increase in usage among people without epilepsy in Manitoba, Saskatchewan, and Alberta. ASM use among PPWOE surged significantly in Manitoba (24.2–149.1 per 10,000 pregnant people), Saskatchewan (29.4–107.0 per 10,000), and Alberta (65.7–241.7 per 10,000) (p < 0.05). In Alberta, PPWE’s ASM exposure also rose, from 23.6 in 2008 to 43.0 per 10,000 pregnant people in 2021, while Quebec witnessed a decrease from 59.2 in 1998 to 45.5 per 10,000 pregnancies in 2015. Analysis of ASM use by trimester illustrated a substantial decline among PPWOE from 365 days pre-pregnancy to the third trimester in all provinces. ASM utilization by drug class showcased significant shifts, with second-generation ASMs experiencing a notable rise. Carbamazepine, once prominent, declined, making way for lamotrigine. Regional variations underscore diverse preferences, such as clonazepam’s sustained popularity in Manitoba and Quebec.ConclusionThe study identified increasing trends in ASM use, particularly the increased use of second-generation ASMs, and differences in prescription patterns for pregnant individuals with and without epilepsy. These findings reveal changing ASM use patterns, including increased second-generation ASM use and regional disparities, providing valuable insights into real-world prescription practices.

Abstract Background Healthy lifestyles are inversely associated with the risk of noncommunicable diseases, which are leading causes of death. However, few studies have used longitudinal data to assess the impact of changing lifestyle behaviours on all-cause and cancer mortality. Methods Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, lifestyle profiles of 308,497 cancer-free adults (71% female) aged 35–70 years at recruitment across nine countries were assessed with baseline and follow-up questionnaires administered on average of 7 years apart. A healthy lifestyle index (HLI), assessed at two time points, combined information on smoking status, alcohol intake, body mass index, and physical activity, and ranged from 0 to 16 units. A change score was calculated as the difference between HLI at baseline and follow-up. Associations between HLI change and all-cause and cancer mortality were modelled with Cox regression, and the impact of changing HLI on accelerating mortality rate was estimated by rate advancement periods (RAP, in years). Results After the follow-up questionnaire, participants were followed for an average of 9.9 years, with 21,696 deaths (8407 cancer deaths) documented. Compared to participants whose HLIs remained stable (within one unit), improving HLI by more than one unit was inversely associated with all-cause and cancer mortality (hazard ratio [HR]: 0.84; 95% confidence interval [CI]: 0.81, 0.88; and HR: 0.87; 95% CI: 0.82, 0.92; respectively), while worsening HLI by more than one unit was associated with an increase in mortality (all-cause mortality HR: 1.26; 95% CI: 1.20, 1.33; cancer mortality HR: 1.19; 95% CI: 1.09, 1.29). Participants who worsened HLI by more than one advanced their risk of death by 1.62 (1.44, 1.96) years, while participants who improved HLI by the same amount delayed their risk of death by 1.19 (0.65, 2.32) years, compared to those with stable HLI. Conclusions Making healthier lifestyle changes during adulthood was inversely associated with all-cause and cancer mortality and delayed risk of death. Conversely, making unhealthier lifestyle changes was positively associated with mortality and an accelerated risk of death.

Abstract Background With roughly 45,000 adult patients each year, distal radius fractures are one of the most common fractures in the emergency department. Approximately 60% of all these fractures are displaced and require surgery. The current guidelines advise to perform closed reduction of these fractures awaiting surgery, as it may lead to post-reduction pain relief and release tension of the surrounding neurovascular structures. Recent studies have shown that successful reduction does not warrant conservative treatment, while patients find it painful or even traumatizing. The aim of this study is to determine whether closed reduction can be safely abandoned in these patients. Methods In this multicenter randomized clinical trial, we will randomize between closed reduction followed by plaster casting and only plaster casting. Patients aged 18 to 75 years, presenting at the emergency department with a displaced distal radial fracture and requiring surgery according to the attending surgeon, are eligible for inclusion. Primary outcome is pain assessed with daily VAS scores from the visit to the emergency department until surgery. Secondary outcomes are function assessed by PRWHE, length of stay at the emergency department, length of surgery, return to work, patient satisfaction, and complications. A total of 134 patients will be included in this study with follow-up of 1 year. Discussion If our study shows that patients who did not receive closed reduction experience no significant drawbacks, we might be able to reorganize the initial care for distal radial fractures in the emergency department. If surgery is warranted, the patient can be sent home with a plaster cast to await the call for admission, decreasing the time spend in the emergency room drastically. Trial registration This trial was registered on January 27, 2023.

Dieses White Paper empfiehlt gezielte Maßnahmen zur Verbesserung der medizinischen Versorgung Long-Covid-Betroffener und basiert auf den Ergebnissen der ASAP-Studie, die von der Dr. Becker Klinikgruppe (DBKG), Dr. Becker Kiliani-Klinik und der Constructor University Bremen durchgeführt wurde. Diese Maßnahmen bestehen aus den folgenden fünf Kernaspekten: 1. Nutzung eines niedrigschwelligen selbst auszufüllenden Screenings auf Post-/Long-Covid (PACS). 2. Interdisziplinäre Erfassung und Bewertung des Gesundheitszustandes (Assessment). 3. Einsatz von digitalen Therapieangeboten zur Unterstützung der medizinischen Versorgung. 4. Einsatz von persönlichen Lots:innen zur Begleitung während des Versorgungsprozesses. 5. Etablierung eines umfassenden Behandlungspfades. Die Befunde aus der ASAP-Studie liefern Evidenz für diese Maßnahmen.

Abstract Research on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per patient from its first 20 patients. In a dedicated experiment, we show the mild impact of increasing time after death on RNA quality, transcriptional profiles and immunohistochemical staining in tumor tissue samples. We show that this impact can be counteracted by organ cooling. We successfully generated ex vivo models from tissue and liquid biopsies from distinct histological subtypes of breast cancer. We anticipate these and future findings of UPTIDER to elucidate mechanisms of disease progression and treatment resistance and to provide tools for the exploration of precision medicine strategies in the metastatic setting.

Abstract Invasive lobular breast cancer (ILC) differs from invasive breast cancer of no special type in many ways. Evidence on treatment efficacy for ILC is, however, lacking. We studied the degree of documentation and representation of ILC in phase III/IV clinical trials for novel breast cancer treatments. Trials were identified on Pubmed and clinicaltrials.gov. Inclusion/exclusion criteria were reviewed for requirements on histological subtype and tumor measurability. Documentation of ILC was assessed and ILC inclusion rate, central pathology and subgroup analyses were evaluated. Inclusion restrictions concerning tumor measurability were found in 39/93 manuscripts. Inclusion rates for ILC were documented in 13/93 manuscripts and varied between 2.0 and 26.0%. No central pathology for ILC was reported and 3/13 manuscripts had ILC sub-analyses. ILC is largely disregarded in most trials with poor representation and documentation. The current inclusion criteria using RECIST v1.1, fall short in recognizing the unique non-measurable metastatic infiltration of ILC.