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In recent years, convolutional neural networks (CNNs) have demonstrated their effectiveness in predicting bulk parameters, such as effective diffusion, directly from pore-space geometries. CNNs offer significant computational advantages over traditional methods, making them particularly appealing. However, the current literature primarily focuses on fully saturated porous media, while the partially saturated case is also of high interest for various applications. Partially saturated conditions present more complex geometries for diffusive transport, making the prediction task more challenging. Traditional CNNs tend to lose robustness and accuracy with lower saturation rates. In this paper, we overcome this limitation by introducing a CNN, which conveniently fuses diffusion prediction and a well-established morphological model that describes phase distributions in partially saturated porous media. We demonstrate the ability of our CNN to perform accurate predictions of relative diffusion directly from full pore-space geometries. Finally, we compare our predictions with well-established relations such as the one by Millington–Quirk.

IntroductionBecause adult-onset leukoencephalopathy with axonal spheroids and pigmented glia (ALSP) is a rare, rapidly progressive, debilitating, and ultimately fatal neurodegenerative disease, a rapid and accurate diagnosis is critical. This analysis examined the frequency of initial misdiagnosis of ALSP via comprehensive review of peer-reviewed published cases.MethodsData were extracted from a MEDLINE search via PubMed (January 1, 1980, through March 22, 2022) from eligible published case reports/series for patients with an ALSP diagnosis that had been confirmed by testing for the colony-stimulating factor-1 receptor gene (CSF1R) mutation. Patient demographics, clinical symptoms, brain imaging, and initial diagnosis data were summarized descriptively. Categorical data for patient demographics, symptoms, and brain imaging were stratified by initial diagnosis category to test for differences in initial diagnosis based on each variable.ResultsData were extracted from a cohort of 291 patients with ALSP from 93 published case reports and case series. Mean (standard deviation) age of symptom onset was 43.2 (11.6) years. A family history of ALSP was observed in 59.1% of patients. Cognitive impairment (47.1%) and behavioral and psychiatric abnormalities (26.8%) were the most frequently reported initial symptoms. Of 291 total cases, an accurate initial diagnosis of ALSP was made in 72 cases (24.7%) and the most frequent initial misdiagnosis categories were frontotemporal dementia (28 [9.6%]) and multiple sclerosis (21 [7.2%]). Of the 219 cases (75.3%) that were initially mis- or undiagnosed, 206 cases (94.1%) were later confirmed as ALSP by immunohistology, imaging, and/or genetic testing; for the remaining 13 cases, no final diagnosis was reported. Initial diagnosis category varied based on age, family history, geographic region, mode of inheritance, and presenting symptoms of pyramidal or extrapyramidal motor dysfunction, behavioral and psychiatric abnormalities, cognitive impairment, and speech difficulty. Brain imaging abnormalities were common, and initial diagnosis category was significantly associated with white matter hyperintensities, white matter calcifications, and ventricular enlargement.DiscussionIn this literature analysis, ALSP was frequently misdiagnosed. Improving awareness of this condition and distinguishing it from other conditions with overlapping presenting symptoms is important for timely management of a rapidly progressive disease such as ALSP.

The second variant of the electron cyclotron heating and current drive system in DEMO considers the deployment of 2 MW power Gaussian microwave beams to the plasma by frequency steering. Broadband optical grade chemical vapor deposition diamond windows are thus required. The Brewster-angle window represents the primary choice. However, in the case of showstoppers, the double-disk window is the backup solution. This window concept was used at ASDEX Upgrade for injection of up to 1 MW at four frequencies between 105 and 140 GHz. This paper shows computational fluid dynamics conjugated heat transfer and structural analyses of such a circumferentially water-cooled window design aiming to check whether it might be used for DEMO microwave beam scenarios. This design was then characterized with respect to different parameters. Temperature and thermal stress results showed that it is a feasible window solution for DEMO, but safety margins against limits shall be increased by introducing design features able to make the fluid more turbulent. A first design change is proposed, showing that, in combination with a higher inlet flow rate, the maximum temperature in the disks can be reduced from 238 to 186 °C, leading, therefore, to lower thermal gradients and stresses in the window.

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both individual risk stratification and quality of care assessment is scarce. We aimed to develop reliable models for mortality prediction in SARI patients utilizing ML algorithms and compare its performances with a classic regression analysis approach. Methods Administrative data (dataset randomly split 75%/25% for model training/testing) from years 2016–2019 of 86 German Helios hospitals was retrospectively analyzed. Inpatient SARI cases were defined by ICD-codes J09-J22. Three ML algorithms were evaluated and its performance compared to generalized linear models (GLM) by computing receiver operating characteristic area under the curve (AUC) and area under the precision-recall curve (AUPRC). Results The dataset contained 241,988 inpatient SARI cases (75 years or older: 49%; male 56.2%). In-hospital mortality was 11.6%. AUC and AUPRC in the testing dataset were 0.83 and 0.372 for GLM, 0.831 and 0.384 for random forest (RF), 0.834 and 0.382 for single layer neural network (NNET) and 0.834 and 0.389 for extreme gradient boosting (XGBoost). Statistical comparison of ROC AUCs revealed a better performance of NNET and XGBoost as compared to GLM. Conclusion ML algorithms for predicting in-hospital mortality were trained and tested on a large real-world administrative dataset of SARI patients and showed good discriminatory performances. Broad application of our models in clinical routine practice can contribute to patients’ risk assessment and quality management.

Abstract Background The aim of our study was to assess the impact the impact of gender and age on reactogenicity to three COVID-19 vaccine products: Biontech/Pfizer (BNT162b2), Moderna (mRNA-1273) and AstraZeneca (ChAdOx). Additional analyses focused on the reduction in working capacity after vaccination and the influence of the time of day when vaccines were administered. Methods We conducted a survey on COVID-19 vaccinations and eventual reactions among 73,000 employees of 89 hospitals of the Helios Group. On May 19th, 2021 all employees received an email, inviting all employees who received at least 1 dose of a COVID-19 to participate using an attached link. Additionally, the invitation was posted in the group’s intranet page. Participation was voluntary and non-traceable. The survey was closed on June 21st, 2021. Results 8375 participants reported on 16,727 vaccinations. Reactogenicity was reported after 74.6% of COVID-19 vaccinations. After 23.0% vaccinations the capacity to work was affected. ChAdOx induced impairing reactogenicity mainly after the prime vaccination (70.5%), while mRNA-1273 led to more pronounced reactions after the second dose (71.6%). Heterologous prime-booster vaccinations with ChAdOx followed by either mRNA-1273 or BNT162b2 were associated with the highest risk for impairment (81.4%). Multivariable analyses identified the factors older age, male gender and vaccine BNT162b as independently associated with lower odds ratio for both, impairing reactogenicity and incapacity to work. In the comparison of vaccine schedules, the heterologous combination ChAdOx + BNT162b or mRNA-1273 was associated with the highest and the homologue prime-booster vaccination with BNT162b with the lowest odds ratios. The time of vaccination had no significant influence. Conclusions Around 75% of the COVID-19 vaccinations led to reactogenicity and nearly 25% of them led to one or more days of work loss. Major risk factors were female gender, younger age and the administration of a vaccine other than BNT162b2. When vaccinating a large part of a workforce against COVID-19, especially in professions with a higher proportion of young and women such as health care, employers and employees must be prepared for a noticeable amount of absenteeism. Assuming vaccine effectiveness to be equivalent across the vaccine combinations, to minimize reactogenicity, employees at risk should receive a homologous prime-booster immunisation with BNT162b2. Trial registration: The study was approved by the Ethic Committee of the Aerztekammer Berlin on May 27th, 2021 (Eth-37/21) and registered in the German Clinical Trials Register (DRKS 00025745). The study was supported by the Helios research grant HCRI-ID 2021-0272.

Abstract Aims Models predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in‐hospital mortality rates in HF cohorts on a population level based on administrative data comparing regression analysis with different machine learning (ML) models. Methods and results Inpatient cases with primary International Statistical Classification of Diseases and Related Health Problems (ICD‐10) encoded discharge diagnosis of HF non‐electively admitted to 86 German Helios hospitals between 1 January 2016 and 31 December 2018 were identified. The dataset was randomly split 75%/25% for model development and testing. Highly unbalanced variables were removed. Four ML algorithms were applied, and all algorithms were tuned using a grid search with multiple repetitions. Model performance was evaluated by computing receiver operating characteristic areas under the curve. In total, 59 125 cases (69.8% aged 75 years or older, 51.9% female) were investigated, and in‐hospital mortality was 6.20%. Areas under the curve of all ML algorithms outperformed regression analysis in the testing dataset with values of 0.829 [95% confidence interval (CI) 0.814–0.843] for logistic regression, 0.875 (95% CI 0.863–0.886) for random forest, 0.882 (95% CI 0.871–0.893) for gradient boosting machine, 0.866 (95% CI 0.854–0.878) for single‐layer neural networks, and 0.882 (95% CI 0.872–0.893) for extreme gradient boosting. Brier scores demonstrated a good calibration especially of the latter three models. Conclusions We introduced reliable models to calculate expected in‐hospital mortality based only on administrative routine data using ML algorithms. A broad application could supplement quality measurement programs and therefore improve future HF patient care.

Abstract Aims The Covid‐19 pandemic affects care for cardiovascular conditions, but data on heart failure (HF) are scarce. This study aims to analyse HF care and in‐hospital outcomes during the pandemic in Germany. Methods and results A total of 9452 HF admissions were studied using claims data of 65 Helios hospitals; 1979 in the study period (13 March 30 April 2020) and 4691 and 2782 in two control periods (13 March to 30 April 2019 and 1 January to 12 March 2020). HF admissions declined compared with both control periods by 29–38%. Cardiac resynchronization therapy was implanted in 0.55% during the study period, 0.32% [odds ratio (OR) 1.66, 95% confidence interval (CI) 0.68–4.04, P = 0.27] in the previous year and 0.43% (OR 1.35, 95% CI 0.64–2.84, P = 0.43) in the same year control. Intensive care treatment was 6.22% during the study period, 4.49% in the previous year (OR 1.46, 95% CI 1.13–1.89, P

Abstract Background Pseudomonas aeruginosa infections are a serious threat in intensive care units (ICUs). The aim of this confirmatory, randomized, multicenter, placebo-controlled, double-blind, phase 2/3 study was to assess the efficacy, immunogenicity, and safety of IC43 recombinant Pseudomonas aeruginosa vaccine in non-surgical ICU patients. Methods Eight hundred patients aged 18 to 80 years admitted to the ICU with expected need for mechanical ventilation for ≥ 48 h were randomized 1:1 to either IC43 100 μg or saline placebo, given in two vaccinations 7 days apart. The primary efficacy endpoint was all-cause mortality in patients 28 days after the first vaccination. Immunogenicity and safety were also evaluated. Findings All-cause mortality rates at day 28 were 29.2% vs 27.7% in the IC43 and placebo groups, respectively (P = .67). Overall survival (Kaplan-Meier survival estimates, P = .46) and proportion of patients with ≥ one confirmed P. aeruginosa invasive infection or respiratory tract infection also did not differ significantly between both groups. The geometric mean fold increase in OprF/I titers was 1.5 after the first vaccination, 20 at day 28, after the second vaccination, and 2.9 at day 180. Significantly more patients in the placebo group (96.5%) had ≥ one adverse event (AE) versus the IC43 100 μg group (93.1%) (P = .04). The most frequently reported severe AEs in the IC43 and placebo groups were respiratory failure (6.9% vs 5.7%, respectively), septic shock (4.1% vs 6.5%), cardiac arrest (4.3% vs 5.7%), multiorgan failure (4.6% vs 5.5%), and sepsis (4.6% vs 4.2%). No related serious AEs were reported in the IC43 group. Interpretation The IC43 100 μg vaccine was well tolerated in this large population of medically ill, mechanically ventilated patients. The vaccine achieved high immunogenicity but provided no clinical benefit over placebo in terms of overall mortality. Trial registration https://clinicaltrials.gov (NCT01563263). Registration was sent to ClinicalTrials.gov on March 14, 2012, but posted by ClinicalTrials.gov on March 26, 2012. The first subject was included in the trial on March 22, 2012.

Background: After the first COVID-19 infection wave, a constant increase of pulmonary embolism (PE) hospitalizations not linked with active PCR-confirmed COVID-19 was observed, but potential contributors to this observation are unclear. Therefore, we analyzed associations between changes in PE hospitalizations and (1) the incidence of non-COVID-19 pneumonia, (2) the use of computed tomography pulmonary angiography (CTPA), (3) volume depletion, and (4) preceding COVID-19 infection numbers in Germany.Methods: Claims data of Helios hospitals in Germany were used, and consecutive cases with a hospital admission between May 6 and December 15, 2020 (PE surplus period), were analyzed and compared to corresponding periods covering the same weeks in 2016–2019 (control period). We analyzed the number of PE cases in the target period with multivariable Poisson general linear mixed models (GLMM) including (a) cohorts of 2020 versus 2016–2019, (b) the number of cases with pneumonia, (c) CTPA, and (d) volume depletion and adjusted for age and sex. In order to associate the daily number of PE cases in 2020 with the number of preceding SARS-CoV-2 infections in Germany, we calculated the average number of daily infections (divided by 10,000) occurring between 14 up to 90 days with increasing window sizes before PE cases and modeled the data with Poisson regression.Results: There were 2,404 PE hospitalizations between May 6 and December 15, 2020, as opposed to 2,112–2,236 (total 8,717) in the corresponding 2016–2019 control periods (crude rate ratio [CRR] 1.10, 95% CI 1.05–1.15, P < 0.01). With the use of multivariable Poisson GLMM adjusted for age, sex, and volume depletion, PE cases were significantly associated with the number of cases with pneumonia (CRR 1.09, 95% CI 1.07–1.10, P < 0.01) and with CTPA (CRR 1.10, 95% CI 1.09–1.10, P < 0.01). The increase of PE cases in 2020 compared with the control period remained significant (CRR 1.07, 95% CI 1.02–1.12, P < 0.01) when controlling for those factors. In the 2020 cohort, the number of preceding average daily COVID-19 infections was associated with increased PE case incidence in all investigated windows, i.e., including preceding infections from 14 to 90 days. The best model (log likelihood −576) was with a window size of 4 days, i.e., average COVID-19 infections 14–17 days before PE hospitalization had a risk of 1.20 (95% CI 1.12–1.29, P < 0.01).Conclusions: There is an increase in PE cases since early May 2020 compared to corresponding periods in 2016–2019. This surplus was significant even when controlling for changes in potential modulators such as demographics, volume depletion, non-COVID-19 pneumonia, CTPA use, and preceding COVID-19 infections. Future studies are needed (1) to investigate a potential causal link for increased risk of delayed PE with preceding SARS-CoV-2 infection and (2) to define optimal screening for SARS-CoV-2 in patients presenting with pneumonia and PE.

Purpose The Mid-German Sepsis Cohort (MSC) aims to investigate mid-term and long-term functional disabilities in sepsis survivors from intensive care unit (ICU) discharge until 1 year after. Secondary, post-acute mortality and morbidity, health-related quality of life and healthcare utilisation will be investigated.Participants The MSC comprises adult (aged ≥18 years) patients who were treated for (severe) sepsis or septic shock on ICU. The participants were recruited between 15 April 2016 and 30 November 2018 from five German centres. Three thousand two hundred and ten patients with sepsis were identified, of which 1968 survived their ICU stay and were eligible for enrolment in the follow-up cohort. Informed consent for follow-up assessment was provided by 907 patients (46.1% of eligible patients).Findings to date The recruitment of the participants for follow-up assessments and the baseline data collection is completed. Incidence of sepsis was 116.7 patients per 1000 ICU patients. In this cohort profile, we provide an overview of the demographics and the clinical characteristics of both the overall sepsis cohort and the ICU survivors who provided informed consent for follow-up assessment (907 out of 1968 ICU survivors (46.1%)).Future plans The follow-ups are conducted 3, 6 and 12 months after ICU discharge. Another yearly follow-up up to 5 years after ICU discharge is pursued. Several cooperation and satellite projects were initiated. This prospective cohort offers a unique resource for research on long-term sequelae of sepsis survivors.Trial registration number German Clinical Trials Registry (DRKS00010050).

BackgroundDuring the early phase of the Covid-19 pandemic, reductions of hospital admissions with a focus on emergencies have been observed for several medical and surgical conditions, while trend data during later stages of the pandemic are scarce. Consequently, this study aims to provide up-to-date hospitalization trends for several conditions including cardiovascular, psychiatry, oncology and surgery cases in both the in- and outpatient setting.Methods and findingsUsing claims data of 86 Helios hospitals in Germany, consecutive cases with an in- or outpatient hospital admission between March 13, 2020 (the begin of the "protection" stage of the German pandemic plan) and December 10, 2020 (end of study period) were analyzed and compared to a corresponding period covering the same weeks in 2019. Cause-specific hospitalizations were defined based on the primary discharge diagnosis according to International Statistical Classification of Diseases and Related Health Problems (ICD-10) or German procedure classification codes for cardiovascular, oncology, psychiatry and surgery cases. Cumulative hospitalization deficit was computed as the difference between the expected and observed cumulative admission number for every week in the study period, expressed as a percentage of the cumulative expected number. The expected admission number was defined as the weekly average during the control period. A total of 1,493,915 hospital admissions (723,364 during the study and 770,551 during the control period) were included. At the end of the study period, total cumulative hospitalization deficit was -10% [95% confidence interval -10; -10] for cardiovascular and -9% [-10; -9] for surgical cases, higher than -4% [-4; -3] in psychiatry and 4% [4; 4] in oncology cases. The utilization of inpatient care and subsequent hospitalization deficit was similar in trend with some variation in magnitude between cardiovascular (-12% [-13; -12]), psychiatry (-18% [-19; -17]), oncology (-7% [-8; -7]) and surgery cases (-11% [-11; -11]). Similarly, cardiovascular and surgical outpatient cases had a deficit of -5% [-6; -5] and -3% [-4; -3], respectively. This was in contrast to psychiatry (2% [1; 2]) and oncology cases (21% [20; 21]) that had a surplus in the outpatient sector. While in-hospital mortality, was higher during the Covid-19 pandemic in cardiovascular (3.9 vs. 3.5%, OR 1.10 [95% CI 1.06-1.15], PConclusionsThere have been varying changes in care pathways and in-hospital mortality in different disciplines during the Covid-19 pandemic in Germany. Despite all the inherent and well-known limitations of claims data use, this data may be used for health care surveillance as the pandemic continues worldwide. While this study provides an up-to-date analysis of utilization of hospital care in the largest German hospital network, short- and long-term consequences are unknown and deserve further studies.

Soil functions are closely related to the structure of soil microaggregates. Yet, the mechanisms controlling the establishment of soil structure are diverse and partly unknown. Hence, the understanding of soil processes and functions requires the connection of the concepts on the formation and consolidation of soil structural elements across scales that are hard to observe experimentally. At the bottom level, the dynamics of microaggregate development and restructuring build the basis for transport phenomena at the continuum scale. By modeling the interactions of specific minerals and/or organic matter, we aim to identify the mechanisms that control the evolution of structure and establishment of stationary aggregate properties. We present a mechanistic framework based on a cellular automaton model to simulate the interplay between the prototypic building units of soil microaggregates quartz, goethite, and illite subject to attractive and repulsive electrostatic interaction forces. The resulting structures are quantified by morphological measures. We investigated shielding effects due to charge neutralization and the aggregate growth rate in response to the net system charge. We found that the fraction as well as the size of the interacting oppositely charged constituents control the size, shape, and amount of occurring aggregates. Furthermore, the concentration in terms of the liquid solid ratio has been shown to increase the aggregation rate. We further adopt the model for an assessment of the temporal evolution of aggregate formation due to successive formation of particle dimers at early stages in comparison to higher order aggregates at later stages. With that we show the effect of composition, charge, size ratio, time, and concentration on microaggregate formation by the application of a mechanistic model which also provides predictions for soil aggregation behavior in case an observation is inhibited by experimental limitations.

Based on a survey, the following study investigates opinions and also usage patterns relating to the ResearchGate social networking site for scientists and researchers. The survey consisted of 19 questions and was conducted online with 695 scientists from the disciplines of physics, biology, medicine, and neuroscience. Amongst other issues, the research questions concerned how much time and effort the interviewees expended on ResearchGate, what added value they perceived in using the site, the extent to which social aspects influence use, how participants planned to use the platform in future, and what role ResearchGate's own metric, the RG score, played for the scientists. In addition, we discuss which of the factors of age, sex, origin, and scientific discipline have a decisive influence on the responses of the interviewees and which are of no statistical significance The results clearly show that the origin of the participants is frequently decisive, but that the remaining factors also have a considerable influence on the responses for more than 25% of the questions.

[This corrects the article DOI: 10.1371/journal.pone.0167214.].

We report on the effect of hemoadsorption therapy to reduce cytokines in septic patients with respiratory failure.This was a randomized, controlled, open-label, multicenter trial. Mechanically ventilated patients with severe sepsis or septic shock and acute lung injury or acute respiratory distress syndrome were eligible for study inclusion. Patients were randomly assigned to either therapy with CytoSorb hemoperfusion for 6 hours per day for up to 7 consecutive days (treatment), or no hemoperfusion (control). Primary outcome was change in normalized IL-6-serum concentrations during study day 1 and 7.97 of the 100 randomized patients were analyzed. We were not able to detect differences in systemic plasma IL-6 levels between the two groups (n = 75; p = 0.15). Significant IL-6 elimination, averaging between 5 and 18% per blood pass throughout the entire treatment period was recorded. In the unadjusted analysis, 60-day-mortality was significantly higher in the treatment group (44.7%) compared to the control group (26.0%; p = 0.039). The proportion of patients receiving renal replacement therapy at the time of enrollment was higher in the treatment group (31.9%) when compared to the control group (16.3%). After adjustment for patient morbidity and baseline imbalances, no association of hemoperfusion with mortality was found (p = 0.19).In this patient population with predominantly septic shock and multiple organ failure, hemoadsorption removed IL-6 but this did not lead to lower plasma IL-6-levels. We did not detect statistically significant differences in the secondary outcomes multiple organ dysfunction score, ventilation time and time course of oxygenation.

To evaluate the performance of low contrast media (CM) dose dual-energy computed tomography pulmonary angiography (CTPA) with advanced monoenergetic reconstructions in patients with suspected pulmonary embolism (PE).The study had institutional review board approval; all patients gave written informed consent. Forty-one patients (25 men, 16 women, mean age 62.9±14.7 years) undergoing low CM dose (15ml, 6g iodine) dual-energy CTPA with advanced monoenergetic reconstructions were matched via propensity-scoring based on logistic regression analysis with a comparison group of 41 patients (24 men, 17 women, mean age 62.7±13.9 years) undergoing standard CM dose single-energy CTPA (80ml, 24g iodine). Subjective (noise, artifacts) and objective (attenuation, noise, contrast-to-noise ratio (CNR)) image quality was assessed by two blinded, independent readers. All patients underwent clinical follow-up after three months for evaluation of adverse events.Interrater agreement for subjective image quality in both groups ranged from fair to excellent (ICC: 0.46-0.84); agreement for objective image quality was excellent (ICC: 0.83-0.93). There was no significant difference regarding subjective noise (p = 0.15-0.72) and artifacts (p = 0.16-1) between the low and the standard CM dose group. There was no significant difference regarding CNR between the CM dose groups (p = 0.11-0.87). Seven of the 41 (17%) patients in the low and 5/41 (12%) in the standard CM dose group were diagnosed with PE (p = 0.32). No patient suffered from subsequent PE or PE-associated death during the follow-up period.Dual-energy CTPA with advanced monoenergetic reconstruction is feasible with 6g iodine and allows for the diagnosis and safe exclusion of central, lobar, and segmental PE.