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Abstract Background Optimal balance between macro- and microcirculation in critically ill patients is crucial for ensuring optimal organ perfusion. Nitric oxide (NO) is a regulator of vascular hemostasis and tone. The availability of NO is controlled by asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), and the availability of the NO substrates arginine and homoarginine. We investigated the changes in plasma concentrations of ADMA, SDMA, arginine, and homoarginine days 1–5 of intensive care unit (ICU) admission and the association between the change in concentration days 1–3 and 30-day all-cause mortality. Methods Single-center cohort study of adult critically ill patients from the ICU at Copenhagen University Hospital – North Zealand. ADMA, SDMA, arginine, and homoarginine (NO-biomarkers) were measured on days 1–5. Initially, we determined the changes in NO-biomarkers days 1–5 with linear mixed models, and subsequently how the changes in NO-biomarkers days 1–3 were associated with 30-day all-cause mortality. Post-hoc we analyzed the association between plasma concentration at admission and 30-day all-cause mortality. Results In total 567 out of 577 patients had plasma samples from days 1–5. Plasma concentrations of ADMA and arginine increased from days 1–5. SDMA concentrations increased from days 1–2, followed by a decrease from days 2–5. Concentrations of homoarginine did not change from days 1–3 but slightly increased from days 3–5. In total 512 patients were alive 3 days after ICU admission. Among these patients, a daily twofold increase in ADMA concentration from days 1–3 was associated with decreased mortality in multivariate analysis (HR 0.45; 95% CI 0.21–0.98; p = 0.046). An increase in SDMA, arginine, or homoarginine was not associated with mortality. Post-hoc we found that a twofold increase in ADMA or SDMA concentrations at admission was associated with mortality (HR 1.78; 95% CI 1.24–2.57; p = 0.0025, and HR 1.41; 95% CI 1.05–1.90; p = 0.024, respectively). Conclusions Increasing ADMA concentrations on days 1–3 are inversely associated with mortality, however not with the same strength as high ADMA or SDMA concentrations at admission. We suggest that admission concentrations are the focus of future research on ADMA and SDMA as predictors of mortality or potential therapeutical targets in ICU patients.

Abstract Phase separation and percolation contribute to phase transitions of multivalent macromolecules. Contributions of percolation are evident through the viscoelasticity of condensates and through the formation of heterogeneous distributions of nano- and mesoscale pre-percolation clusters in sub-saturated solutions. Here, we show that clusters formed in sub-saturated solutions of FET (FUS-EWSR1-TAF15) proteins are affected differently by glutamate versus chloride. These differences on the nanoscale, gleaned using a suite of methods deployed across a wide range of protein concentrations, are prevalent and can be unmasked even though the driving forces for phase separation remain unchanged in glutamate versus chloride. Strikingly, differences in anion-mediated interactions that drive clustering saturate on the micron-scale. Beyond this length scale the system separates into coexisting phases. Overall, we find that sequence-encoded interactions, mediated by solution components, make synergistic and distinct contributions to the formation of pre-percolation clusters in sub-saturated solutions, and to the driving forces for phase separation.

The Formalist tradition in late-scholastic philosophy has gone unnoticed in standard historiography. This article’s overall objective is to add the Formalist tradition to what we know about Renaissance philosophy. I first show how the Formalist tradition was born out of some innovative considerations of hierarchies of distinctions in the wake of the Franciscan John Duns Scotus’s teaching on the formal distinction in the beginning of the fourteenth century (especially Francis of Meyronnes’s model of four distinctions and Petrus Thomae’s more elaborate doctrine of seven kinds of distinctions). I then trace how Formalist literature developed from being an exclusively Franciscan affair to becoming a much more widespread phenomenon. Thus, from the decades up to 1500 and onwards, authors from various late-scholastic schools (Thomism, Lullism, Averroism, and others) produced Formalist literature, i.e., treatises on multiple kinds of distinctions. I highlight particularly how one Franciscan philosopher of the sixteenth century, Jean Du Douet, proposed to view the Formalist preoccupation with distinctions as a discipline in its own right, a proper scientia formalitatum. I finally argue that while this proposal met with dismissive reactions, Du Douet’s idea does in fact reflect the role Formalism played in the scholastic curriculum in the late sixteenth century, at least in Franciscan milieus.

Continuous medical and safety monitoring of subject data during a clinical trial is a critical part of evaluating the safety of trial participants and as such is governed by protocol procedures and regulatory guidelines to meet the trial's intended objectives. We present an open-source validated graphical tool (clinDataReview R package) which provides access to the trial data with drill-down to individual patient profiles. The tool incorporates functionalities that facilitate detection of error and data inconsistencies requiring follow-up. It supports regular medical monitoring and oversight as well as safety monitoring committees with interactive tables and listings alongside graphical visualizations of the primary safety data in reports. An implementation example is given where the tool is used to deliver validated outputs following FDA/EMA guidelines. As such, this tool enables a more efficient, interactive, and reproducible review of safety data collected during an ongoing clinical trial.

The integration of agricultural robots in precision farming plays a pivotal role in tackling the pressing demands of minimizing energy usage, enhancing productivity, and maximizing crop yield to meet the needs of an expanding global population and depleting non-renewable resources. Evaluating the energy expenditure is vital when assessing agricultural machinery systems. Through the reduction of fuel consumption, operational costs can be curtailed while simultaneously minimizing the overall environmental footprint left by these machines. Accurately calculating fuel usage empowers farmers to make well-informed decisions about their farming operations, resulting in more sustainable and productive methods. In this study, the ASABE model was applied to predict the fuel consumption of the studied robot. Results show that the ASABE model can predict the fuel consumption of the robot with an average error equal to 27.5%. Moreover, different machine-learning techniques were applied to develop an effective and novel model for estimating the fuel consumption of an agricultural robot. The proposed GPR model (gaussian process regression) considers four operational features of the studied robot: total operational time, total traveled distance, automatic working distance, and automatic turning distance. The GPR model with four features, considering hyperparameter optimization, showed the best performance (R-squared validation = 0.93, R-squared test = 1.00) among other models. Furthermore, three different ML methods (gradient boosting, random forest, and XGBoost) were considered in this study and compared with the developed GPR model. The results show that the GPR model outperformed the mentioned models. Moreover, the one-way ANOVA test results revealed that the predicted values from the GPR model and observation do not have significantly different means. The results of the sensitivity analysis show that the traveled distance and the total time have a significant correlation with the fuel consumption of the studied robot.

Abstract Many single-molecule investigations are performed in fluidic environments, for example, to avoid unwanted consequences of contact with surfaces. Diffusion of molecules in this arrangement limits the observation time and the number of collected photons, thus, compromising studies of processes with fast or slow dynamics. Here, we introduce a planar optofluidic antenna (OFA), which enhances the fluorescence signal from molecules by about 5 times per passage, leads to about 7-fold more frequent returns to the observation volume, and significantly lengthens the diffusion time within one passage. We use single-molecule multi-parameter fluorescence detection (sm-MFD), fluorescence correlation spectroscopy (FCS) and Förster resonance energy transfer (FRET) measurements to characterize our OFAs. The antenna advantages are showcased by examining both the slow (ms) and fast (50 μs) dynamics of DNA four-way (Holliday) junctions with real-time resolution. The FRET trajectories provide evidence for the absence of an intermediate conformational state and introduce an upper bound for its lifetime. The ease of implementation and compatibility with various microscopy modalities make OFAs broadly applicable to a diverse range of studies.

Abstract Background Robotic-assisted complete mesocolic excision is an advanced procedure mainly because of the great variability in anatomy. Phantoms can be used for simulation-based training and assessment of competency when learning new surgical procedures. However, no phantoms for robotic complete mesocolic excision have previously been described. This study aimed to develop an anatomically true-to-life phantom, which can be used for training with a robotic system situated in the clinical setting and can be used for the assessment of surgical competency. Methods Established pathology and surgical assessment tools for complete mesocolic excision and specimens were used for the phantom development. Each assessment item was translated into an engineering development task and evaluated for relevance. Anatomical realism was obtained by extracting relevant organs from preoperative patient scans and 3D printing casting moulds for each organ. Each element of the phantom was evaluated by two experienced complete mesocolic excision surgeons without influencing each other’s answers and their feedback was used in an iterative process of prototype development and testing. Results It was possible to integrate 35 out of 48 procedure-specific items from the surgical assessment tool and all elements from the pathological evaluation tool. By adding fluorophores to the mesocolic tissue, we developed an easy way to assess the integrity of the mesocolon using ultraviolet light. The phantom was built using silicone, is easy to store, and can be used in robotic systems designated for patient procedures as it does not contain animal-derived parts. Conclusions The newly developed phantom could be used for training and competency assessment for robotic-assisted complete mesocolic excision surgery in a simulated setting.

Introduction Inflammatory bowel disease (IBD), including ulcerative colitis and Crohn’s disease, can be challenging to diagnose, and treatment outcomes are difficult to predict. In the NORDTREAT cohort study, a Nordic prospective multicentre study, we aim to identify novel molecular biomarkers of diagnostic value by assessing the diagnostic test accuracy (cross-sectionally), as well as the prognostic utility when used as prognostic markers in the long-term (cohort study). In the diagnostic test accuracy study, the primary outcome is a successful diagnosis using one or more novel index tests at baseline compared with the ECCO criteria as the reference standard. The composite outcome of the prognostic utility study is ‘severe IBD’ within 52 weeks from inclusion, defined as one or more of the following three events: IBD-related surgery, IBD-related hospitalisation or IBD-related death.Methods and analysis We aim to recruit 800 patients referred on suspicion of IBD to this longitudinal observational study, a collaboration between 11 inclusion sites in Denmark, Iceland, Norway and Sweden. Inclusion will occur from February 2022 until December 2023 with screening and baseline visits for all participants and three outcome visits at weeks 12, 26 and 52 after baseline for IBD-diagnosed patients. Biological material (blood, faeces, biopsies, urine and hair), clinical data and lifestyle information will be collected during these scheduled visits.Ethics and dissemination This study will explore novel biomarkers to improve diagnostic accuracy and prediction of disease progression, thereby improving medical therapy and the quality of life for patients with IBD.The study is approved by the Ethics Committee (DK: S-20200051, v1.4, 16.10.2021; IS: VSNb2021070006/03.01, NO: 193064; SE: DNR 2021-05090) and the Danish Data Protecting Agency (20/54594). Results will be disseminated through peer-reviewed journals, patient associations and presentations at international conferences.Clinical trial registration number NCT05414578; Pre-results.

Introduction: Patients with failure after primary radiotherapy (RT) for head and neck squamous cell carcinoma (HNSCC) have a poor prognosis. This study investigates pattern of failure after primary curatively intended IMRT in a randomized controlled trial in relation to HPV/p16 status. Material and methods: Patients with HNSCC of the oral cavity, oropharynx (OPSCC), hypopharynx or larynx were treated with primary curative IMRT (+/-cisplatin) and concomitant nimorazole between 2007 and 12. Of 608 patients, 151 had loco-regional failure within five years, from whom 130 pairs of scans (planning-CT and diagnostic failure scan) were collected and deformably co-registered. Point of origin-based pattern of failure analysis was conducted, including distance to CTV1 and GTV, and estimated dose coverage of the point of origin. Results: Of 130 patients with pairs of scans, 104 (80 %) had at least one local or regional failure site covered by 95 % of prescribed dose and 87 (67 %) of the failures had point of origin within the high-dose CTV (CTV1). Of failures from primary p16 + OPSCC, the majority of both mucosal (84 %) and nodal (61 %) failures were covered by curative doses. For p16− tumors (oral cavity, OPSCC p16neg, hypopharynx and larynx), 75 % of mucosal and 66 % of nodal failures were high-dose failures. Conclusion: Radioresistance is the primary cause of failure after RT for HNSCC irrespective of HPV/p16 status. Thus, focus on predictors for the response to RT is warranted to identify patients with higher risk of high-dose failure that might benefit from intensified treatment regimens.

AbstractRecurrent respiratory papillomatosis (RRP) is a human papilloma virus (HPV) 6/11 related, predominantly histologically benign neoplasm of the upper and lower airway affecting both younger and older patients. Though potentially declining due to HPV vaccination RRP is still challenging in management and a significant cause of affected quality of life. Systemic bevacizumab has shown efficacy for aggressive disease in other case series in juvenile-onset RRP (JORRP) as in adult-onset RRP (AORRP). We present five consecutive patients with AORRP treated with systemic bevacizumab for aggressive laryngeal and tracheal papillomatosis. Adding to the findings of previous reports we show that systemic bevacizumab treatment could have positive influence on aggressive AORRP without pulmonary spread with manageable side effects.

Mycobacterium avium subspecies paratuberculosis (MAP) is a global concern in modern livestock production worldwide. The available vaccines against paratuberculosis do not offer optimal protection and interfere with the diagnosis of bovine tuberculosis. The aim of this study was to identify immunogenic MAP-specific peptides that do not interfere with the diagnosis of bovine tuberculosis. Initially, 119 peptides were selected by either (1) identifying unique MAP peptides that were predicted to bind to bovine major histocompatibility complex class II (MHC-predicted peptides) or (2) selecting hydrophobic peptides unique to MAP within proteins previously shown to be immunogenic (hydrophobic peptides). Subsequent testing of peptide-specific CD4+ T-cell lines from MAP-infected, adult goats vaccinated with peptides in cationic liposome adjuvant pointed to 23 peptides as being most immunogenic. These peptides were included in a second vaccine trial where three groups of eight healthy goat kids were vaccinated with 14 MHC-predicted peptides, nine hydrophobic peptides, or no peptides in o/w emulsion adjuvant. The majority of the MHC-predicted (93%) and hydrophobic peptides (67%) induced interferon-gamma (IFN-γ) responses in at least one animal. Similarly, 86% of the MHC-predicted and 89% of the hydrophobic peptides induced antibody responses in at least one goat. The immunization of eight healthy heifers with all 119 peptides formulated in emulsion adjuvant identified more peptides as immunogenic, as peptide specific IFN-γ and antibody responses in at least one heifer was found toward 84% and 24% of the peptides, respectively. No peptide-induced reactivity was found with commercial ELISAs for detecting antibodies against Mycobacterium bovis or MAP or when performing tuberculin skin testing for bovine tuberculosis. The vaccinated animals experienced adverse reactions at the injection site; thus, it is recommend that future studies make improvements to the vaccine formulation. In conclusion, immunogenic MAP-specific peptides that appeared promising for use in a vaccine against paratuberculosis without interfering with surveillance and trade tests for bovine tuberculosis were identified by in silico analysis and ex vivo generation of CD4+ T-cell lines and validated by the immunization of goats and cattle. Future studies should test different peptide combinations in challenge trials to determine their protective effect and identify the most MHC-promiscuous vaccine candidates.

Abstract To assess if SARS-CoV-2 (COVID-19) systemic disease can be determined by available nucleoprotein assays, we compared the performance of three commercial SARS-CoV-2 nucleoprotein (N) assays in plasma. A total of 272 plasma samples collected in the period November–December 2021 were analyzed by the methods Simoa SARS CoV‐2 N Protein Advantage Kit [Quanterix Simoa], Solsten SARS-CoV-2 Antigen enzyme immunosorbent assay (ELISA) [Solsten ELISA], and Elecsys SARS‐CoV‐2 Antigen electrochemiluminescence immunoassay [Elecsys ECLIA]. Additionally, a dilution series of inactivated virus culture was analyzed by the three assays. The SARS CoV-2 PCR-status was not known for the patients. Linear correlation in the pairwise correlation between assays as well as linearity of dilution series of inactivated virus culture was estimated by Spearman score. Sensitivity and specificity were estimated by pairwise comparison. The three assays showed poor agreement on patient samples with regards to concentration. Performance on virus culture was excellent but with different level of detection (LOD). Positive vs negative results show comparable sensitivity and specificity of Quanterix Simoa and Solsten ELISA, with a higher LOD in Elecsys ECLIA and thus lower sensitivity and high specificity. N by all tested assays can be used as a marker for systemic COVID-19 disease.

The area of interest is future business model innovation in Society 5.0. This is important as the transition from Society 4.0 to Society 5.0 is happening at an exponential pace driven by the Metaverse. Thus, the research question is: how should companies think and do business model innovation in the Society 5.0 / Metaverse space? The method is conceptual, where the business model characteristics of Society 1.0 to 4.0 are empirically stated for inductive arguments for equivalent characteristics of Society 5.0. This is framed with Society 5.0 theory, Metaverse theory, and Osterwalder and Pigneur’s nine business model building blocks from their iconic Business Model Canvas (BMC). The contribution is a framework cross-tabulating Society 1.0 to Society 5.0 with the nine BMC elements. Finally, a discussion is provided with findings and implications for managers regarding business model innovation, new businesses, outcome logic, ecospheres, and currencies.

The development of robotic-based agricultural machinery systems has significantly increased in recent years. Many autonomous systems have not yet been measured based on sustainability and economic performances, even though automation is regarded as an opportunity to increase safety, dependability, productivity, and efficiency. The operational aspect, economic viability, and environmental impact of replacing conventional machinery with robotized alternatives are the primary focus of this study. The robot considered in this research is designed for extensive fieldwork, where PTO and external hydraulics are required. This robot is equipped with two 75 (hp) Kubota diesel engines with a total engine gross power of up to 144 (hp). Both robotic system and conventional machinery were described, and different scenarios were used to examine various operational and environmental indicators, as well as individual cost elements, considering various field sizes and working widths of implements used in seeding and weeding operations. The findings demonstrate that the robotic system outperforms conventional machinery in terms of operational efficiency by as much as 9%. However, the effective field capacity comparison reveals that the conventional system has a field capacity that is up to 3.6 times greater than that of the robotic system. Additionally, the total cost per hour of the robotic system is up to 57% lower than that of the conventional system. The robotic system can save up to 63.3% of fuel during operation, resulting in the same percentage reduction in CO2 emissions as the conventional system, according to a comparison of fuel consumption.

Abstract Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

Guanylate binding proteins (GBPs) are soluble dynamin-like proteins that undergo a conformational transition for GTP-controlled oligomerization and disrupt membranes of intracellular parasites to exert their function as part of the innate immune system of mammalian cells. We apply neutron spin echo, X-ray scattering, fluorescence, and EPR spectroscopy as techniques for integrative dynamic structural biology to study the structural basis and mechanism of conformational transitions in the human GBP1 (hGBP1). We mapped hGBP1’s essential dynamics from nanoseconds to milliseconds by motional spectra of sub-domains. We find a GTP-independent flexibility of the C-terminal effector domain in the µs-regime and resolve structures of two distinct conformers essential for an opening of hGBP1 like a pocket knife and for oligomerization. Our results on hGBP1’s conformational heterogeneity and dynamics (intrinsic flexibility) deepen our molecular understanding relevant for its reversible oligomerization, GTP-triggered association of the GTPase-domains and assembly-dependent GTP-hydrolysis.

This research investigates the ways in which mathematical modelling as a design feature support or constrain students’ understandings and explanations of a complex natural phenomenon and how students experience the relevance of mathematical modelling in a model-based inquiry (MBI) unit. To support lower secondary students in using mathematical modelling, we developed an MBI unit based on a complex natural phenomenon, a cloudburst event, in which mathematical modelling was essential to understanding and explaining the phenomenon. The research took place in two Danish schools and the unit comprised 12 lessons over a period of one week. The sample group consisted of 40 students in the 14–16 years age group. For the analysis of the students’ mathematical modelling, the research used an adaptation of the modelling cycle proposed by Blum and Leiß (2005) to interpret the students’ artefacts. A subset of participants (n = 7) was also interviewed about their models to gain insights into how students experience the relevance of mathematical modelling in the MBI unit. Results show that the majority of the students – 37 out of 40 – were able to understand the mathematical problem from the anchoring phenomenon and model the phenomenon from a mathematical perspective, but we also see that a small number of students have problems in completing all the facets of the mathematical modelling cycle and are not able to validate the solution of the mathematical problem in relation to the anchoring phenomenon. Students expressed that their own modelling process along with the mathematical modelling helped them better understand the various elements of the anchoring phenomenon.

Patients with multiple sclerosis (MS) and spinal cord injury (SCI) commonly sustain central neuropathic pain (NP) and spasticity. Despite a lack of consistent evidence, cannabis-based medicine (CBM) has been suggested as a supplement treatment. We aimed to investigate the effect of CBM on NP and spasticity in patients with MS or SCI. We performed a randomized, double-blinded, placebo-controlled trial in Denmark. Patients aged ≥18 years with NP (intensity >3, ≤9 on a numerical rating scale (NRS0-10) and/or spasticity (>3 on NRS0-10) were randomized to treatment consisting of either delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), a combination of THC&CBD in maximum doses of 22.5 mg, 45 mg and 22.5/45 mg per day, respectively, or placebo. A baseline registration was performed before randomization. Treatment duration was six weeks followed by a one-week phaseout. Primary endpoints were the intensity of patient-reported NP and/or spasticity. Between February 2019 and December 2021, 134 patients were randomized (MS n = 119, SCI n = 15), where 32 were assigned to THC, 31 to CBD, 31 to THC&CBD, and 40 to placebo. No significant difference was found for: mean pain intensity (THC 0.42 (−0.54–1.38), CBD 0.45 (−0.47–1.38) and THC&CBD 0.16 (−0.75–1.08)), mean spasticity intensity (THC 0.24 (−0.67–1.45), CBD 0.46 (−0.74–1.65), and THC&CBD 0.10 (−1.18–1.39), secondary outcomes (patient global impression of change and quality of life), or any tertiary outcomes. We aimed to include 448 patients in the trial; however, due to COVID-19 and recruitment challenges, fewer were included. Nevertheless, in this four-arm parallel trial, no effect was found between placebo and active treatment with THC or CBD alone or in combination on NP or spasticity in patients with either MS or SCI. The trial was registered with the EU Clinical Trials Register EudraCT (2018-002315-98).

Tuberculosis (TB) subunit vaccines have been investigated as boosters for BCG-induced immunity. Here, the authors design a TB subunit vaccine that doesn't share antigens with BCG and show that co-administration of the two vaccines broadens the T cell response to TB and increases protection.

The scaffold protein PSD-95 links postsynaptic receptors to sites of presynaptic neurotransmitter release. Flexible linkers between folded domains in PSD-95 enable a dynamic supertertiary structure. Interdomain interactions within the PSG supramodule, formed by PDZ3, SH3, and Guanylate Kinase domains, regulate PSD-95 activity. Here we combined discrete molecular dynamics and single molecule Förster resonance energy transfer (FRET) to characterize the PSG supramodule, with time resolution spanning picoseconds to seconds. We used a FRET network to measure distances in full-length PSD-95 and model the conformational ensemble. We found that PDZ3 samples two conformational basins, which we confirmed with disulfide mapping. To understand effects on activity, we measured binding of the synaptic adhesion protein neuroligin. We found that PSD-95 bound neuroligin well at physiological pH while truncated PDZ3 bound poorly. Our hybrid structural models reveal how the supertertiary context of PDZ3 enables recognition of this critical synaptic ligand.

The flavin derivatives 10-methyl-isoalloxazine (MIA) and 6-fluoro-10-methyl-isoalloxazine (6F-MIA) were incorporated in two alternative metal-organic frameworks, (MOFs) MIL-53(Al) and MOF-5. We used a post-synthetic, diffusion-based incorporation into microcrystalline MIL-53 powders with one-dimensional (1D) pores and an in-situ approach during the synthesis of MOF-5 with its 3D channel network. The maximum amount of flavin dye incorporation is 3.9 wt% for MIA@MIL-53(Al) and 1.5 wt% for 6F-MIA@MIL-53(Al), 0.85 wt% for MIA@MOF-5 and 5.2 wt% for 6F-MIA@MOF-5. For the high incorporation yields the probability to have more than one dye molecule in a pore volume is significant. As compared to the flavins in solution, the fluorescence spectrum of these flavin@MOF composites is broadened at the bathocromic side especially for MIA. Time-resolved spectroscopy showed that multi-exponential fluorescence lifetimes were needed to describe the decays. The fluorescence-weighted lifetime of flavin@MOF of 4 ± 1 ns also corresponds to those in solution but is significantly prolonged compared to the solid flavin dyes with less than 1 ns, thereby confirming the concept of “solid solutions” for dye@MOF composites. The fluorescence quantum yield (ΦF) of the flavin@MOF composites is about half of the solution but is significantly higher compared to the solid flavin dyes. Both the fluorescence lifetime and quantum yield of flavin@MOF decrease with the flavin loading in MIL-53 due to the formation of various J-aggregates. Theoretical calculations using plane-wave and QM/MM methods are in good correspondence with the experimental results and explain the electronic structures as well as the photophysical properties of crystalline MIA and the flavin@MOF composites. In the solid flavins, π-stacking interactions of the molecules lead to a charge transfer state with low oscillator strength resulting in aggregation-caused quenching (ACQ) with low lifetimes and quantum yields. In the MOF pores, single flavin molecules represent a major population and the computed MIA@MOF structures do not find π-stacking interactions with the pore walls but only weak van-der-Waals contacts which reasons the enhanced fluorescence lifetime and quantum yield of the flavins in the composites compared to their neat solid state. To analyze the orientation of flavins in MOFs, we measured fluorescence anisotropy images of single flavin@MOF-5 crystals and a static ensemble flavin@MIL53 microcrystals, respectively. Based on image information, anisotropy distributions and overall curve of the time-resolved anisotropy curves combined with theoretical calculations, we can prove that all fluorescent flavins species have a defined and rather homogeneous orientation in the MOF framework. In MIL-53, the transition dipole moments of flavins are orientated along the 1D channel axis, whereas in MOF-5 we resolved an average orientation that is tilted with respect to the cubic crystal lattice. Notably, the more hydrophobic 6F-MIA exhibits a higher degree order than MIA. The flexible MOF MIL-53(Al) was optimized essentially to the experimental large-pore form in the guest-free state with QuantumEspresso (QE) and with MIA molecules in the pores the structure contracted to close to the experimental narrow-pore form which was also confirmed by PXRD. In summary, the incorporation of flavins in MOFs yields solid-state materials with enhanced rigidity, stabilized conformation, defined orientation and reduced aggregations of the flavins, leading to increased fluorescence lifetime and quantum yield as controllable photo-luminescent and photo-physical properties.

Background: Consumer wearables allow objective health data monitoring, e.g., of physical activity and heart rate, which might change over a cancer treatment course. Patients with head and neck cancer (HNC) receiving radiotherapy (RT) with curative intent typically experience side effects such as pain, decreased appetite, and dehydration, which may lead to hospitalizations. Therefore, health data monitoring could be important to understand a patient’s condition outside the hospital. The OncoWatch 1.0 study investigated the feasibility of using smartwatches for patients with HNC receiving RT. Methods: This study was a prospective, single-cohort feasibility study. The inclusion criteria were patients ≥ 18 years of age who planned to receive curatively intended radiotherapy for HNC. Consenting patients were asked to wear a smartwatch during RT and until two weeks after the end of RT. The primary endpoint was adherence. The secondary endpoints were data acquisition and variations in heart rate and physical activity. Results: Ten patients were included, with a median age of 62 years and eight males. The adherence rate for wearing the watch >12 h/d over the study period was 31%. The data acquisition rate was 61%. Conclusions: Although the primary endpoint was not reached, new knowledge has been established, including the secure data setup and key points that need to be addressed in future studies.

To overcome the limitation of FRET data being too sparse to cover all structural details, FRET experiments need to be carefully designed and complemented with simulations. Here the authors present a toolkit for automated design of FRET experiments, which determines how many and which FRET pairs should be used to maximize the accuracy, and for FRET-assisted structural modeling and refinement at the atomistic level.

Ketamine is a non-competitive N-Methyl-D-aspartate receptor (NMDAR) antagonist used in the clinic to initiate and maintain anaesthesia; it induces dissociative states and has emerged as a breakthrough therapy for major depressive disorder. Using local field potential recordings in freely moving rats, we studied resting state EEG profiles induced by co-administering ketamine with either: clozapine, a highly efficacious antipsychotic; or naltrexone, an opioid receptor antagonist reported to block the acute antidepressant effects of ketamine. As human electroencephalography (EEG) is predominantly recorded in a passive state, head-mounted accelerometers were used with rats to determine active and passive states at a high temporal resolution to offer the highest translatability. In general, pharmacological effects for the three drugs were more pronounced in (or restricted to) the passive state. Specifically, during inactive periods clozapine induced increases in delta (0.1–4 Hz), gamma (30–60 Hz) and higher frequencies (>100 Hz). Importantly, it reversed the ketamine-induced reduction in low beta power (10–20 Hz) and potentiated ketamine-induced increases in gamma and high frequency oscillations (130–160 Hz). Naltrexone inhibited frequencies above 50 Hz and significantly reduced the ketamine-induced increase in high frequency oscillations. However, some frequency band changes, such as clozapine-induced decreases in delta power, were only seen in locomoting rats. These results emphasise the potential in differentiating between activity states to capture drug effects and translate to human resting state EEG. Furthermore, the differential reversal of ketamine-induced EEG effects by clozapine and naltrexone may have implications for the understanding of psychotomimetic as well as rapid antidepressant effects of ketamine.

Seismic History Matching (SHM) is a key problem in the geosciences community, requiring optimal parameters of a subsurface model that match the observed data from multiple in-situ measurements. Therefore, the SHM problems are usually solved with Multi-Objective Evolutionary Algorithms (MOEAs). This group of algorithms optimize multiple objectives simultaneously, considering the trade-off between objectives. However, SHM requires the solutions that are good on all objectives rather than a trade-off. In this study, we propose a Differential Evolution algorithm using Lexicase Selection to solve the SHM problems. Unlike the MOEAs, this selection method pushes the solutions to perform well on all objectives. We compared this method with two MOEAs, namely Non-dominated Sorting Genetic Algorithm II and Reference Vector-guided Evolutionary Algorithm, on two SHM problems. The results show that this method generates more solutions near the ground truth.

BACKGROUND: Motor function is critical for childrens health, yet remains an understudied neurodevelopmental domain. Exposure to metals has been linked with motor function, but no study has examined the joint effects of metal mixtures. METHODS: We evaluated cross-sectional associations between a metal mixture and motor function among 569 adolescents (10-14 years old) living near the ferroalloy industry. Concentrations of blood lead, hair manganese, hair copper, and hair chromium were quantified using inductively coupled plasma mass spectrometry. Neuropsychologists administered multiple fine motor function assessments: pursuit aiming, finger tapping, visual reaction time (VRT), and subtests from the Luria Nebraska battery. We estimated associations between motor function and the metal mixture using quantile-based g-computation and multivariable linear regression, adjusting for child age, sex, and socioeconomic status. We explored sex-specific associations in stratified models. RESULTS: Associations between the metal mixture and motor function were mostly null but were modified by sex. We observed a beneficial association among females: a quartile increase in all metals in the mixture was associated with a 2.6% faster average response time on the VRT (95% confidence interval [CI] = -4.7%, -0.5%), driven by Cu and Cr. In contrast, this association was adverse among males (ß = 1.5% slower response time [95% CI = -0.7%, 3.9%]), driven by Cu and Mn. CONCLUSIONS: Results suggest that males may be more susceptible to the adverse effects of metal exposure on motor function during adolescence than females. Future studies, particularly prospective study designs, are warranted to further understand the associations of metal mixtures with motor function.

Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.