Conformations of a highly expressed Z19 α-zein studied with AlphaFold2 and MD simulations.

α-zeins are amphiphilic maize seed storage proteins with material properties suitable for a multitude of applications e.g., in renewable plastics, foods, therapeutics and additive manufacturing (3D-printing). To exploit their full potential, molecular-level insights are essential. The difficulties in experimental atomic-resolution characterization of α-zeins have resulted in a diversity of published molecular models. However, deep-learning α-zein models are largely unexplored. Therefore, this work studies an AlphaFold2 (AF2) model of a highly expressed α-zein using molecular dynamics (MD) simulations. The sequence of the α-zein cZ19C2 gave a loosely packed AF2 model with 7 α-helical segments connected by turns/loops. Compact tertiary structure was limited to a C-terminal bundle of three α-helices, each showing notable agreement with a published consensus sequence. Aiming to chart possible α-zein conformations in practically relevant solvents, rather than the native solid-state, the AF2 model was subjected to MD simulations in water/ethanol mixtures with varying ethanol concentrations. Despite giving structurally diverse endpoints, the simulations showed several patterns: In water and low ethanol concentrations, the model rapidly formed compact globular structures, largely preserving the C-terminal bundle. At ≥ 50 mol% ethanol, extended conformations prevailed, consistent with previous SAXS studies. Tertiary structure was partially stabilized in water and low ethanol concentrations, but was disrupted in ≥ 50 mol% ethanol. Aggregated results indicated minor increases in helicity with ethanol concentration. ß-sheet content was consistently low (∼1%) across all conditions. Beyond structural dynamics, the rapid formation of branched α-zein aggregates in aqueous environments was highlighted. Furthermore, aqueous simulations revealed favorable interactions between the protein and the crosslinking agent glycidyl methacrylate (GMA). The proximity of GMA epoxide carbons and side chain hydroxyl oxygens simultaneously suggested accessible reactive sites in compact α-zein conformations and pre-reaction geometries for methacrylation. The findings may assist in expanding the applications of these technologically significant proteins, e.g., by guiding chemical modifications.

Lung cancer among the Elderly in Denmark - A comprehensive population-based cohort study.

OBJECTIVE: Lung cancer primarily occurs in the elderly with a median age at diagnosis in Denmark of 73 years. However, elderly patients are under-represented in clinical trials as well as in screening studies. In this study, we aim to characterize elderly patients with lung cancer and explore the diagnostic intensity, treatment patterns, and survival. METHOD: Patients diagnosed with lung cancer between 2014 and 2017 according to the Danish Cancer Registry, and with clinical information in the Danish Lung Cancer Registry were included. Patient information was linked by the unique social identification number to information from Statistics Denmark. RESULTS: We included n = 17,835 patients in this study, of whom 2,871 (16.1 %) were 80 years or older. Fewer elderly patients had lung biopsies (47 % vs 53 %) or mediastinal procedures (34 % vs 26 %), compared to the younger patients (p < 0.001). Fewer elderly patients had treatment registration (60 % vs 85 %), and fewer received treatment with curative intent (23 % vs 42 %) compared to patients younger than 80 years (p < 0.001). The elderly patients had 2.1 (CI 95 % 1.9 - 2.2) times higher odds of dying within 12 months after diagnosis than younger patients. CONCLUSION: The diagnostic intensity among lung cancer patients aged eighty years or above is lower compared to younger patients. Being elderly is associated with not undergoing surgical treatment or treatment with curative intent. Across all treatment groups, being older than eighty years of age was associated with an adverse prognosis.

Cell-Free Culture Supernatant of Lactobacillus acidophilus AG01 and Bifidobacterium animalis subsp. lactis AG02 Reduces the Pathogenicity of NetB-Positive Clostridium perfringens in a Chicken Intestinal Epithelial Cell Line.

The worldwide reduction in the use of antibiotics in animal feed is fueling the need for alternatives for the prevention and control of poultry intestinal diseases such as necrotic enteritis (NE), which is caused by Clostridium perfringens. This is the first report on the use of an intestinal epithelial chicken cell line (CHIC-8E11) to study the pathogenic traits of C. perfringens and to investigate the mode of action of cell-free supernatants (CFS) from probiotic Lactobacillus acidophilus AG01 and Bifidobacterium animalis subsp. lactis AG02 in reducing the pathogenicity of C. perfringens. The cell adhesion, permeability and cytotoxicity were assessed under challenge with four C. perfringens strains isolated from broiler NE episodes of differing geographical origin (CP1-UK; CP10-Sweden; 25037-CP01 and CP22-USA). All the C. perfringens strains could adhere to the CHIC-8E11 cells, with varying affinity (0.05-0.48% adhesion across the strains). The CFS from one out of two strains (CP22) increased the cell permeability (+4.5-fold vs. the control, p < 0.01), as measured by the fluorescein isothiocyanate-dextran (FD4) content, with NetB toxin implicated in this effect. The CFS from all the strains was cytotoxic against the CHIC-8E11 cells in a dose- and strain-dependent manner (cytotoxicity 23-62% across the strains when dosed at 50 µL/mL, as assessed by the MTT cell viability assay). Pre-treatment of the cells with CFS from B. animalis subsp. lactis AG02 but not L. acidophilus AG01 reduced the cell adhesion of three out of four C. perfringens strains (by 77-85% vs. the control, p < 0.001) and reduced the negative effect of two NetB-positive strains on the cell permeability. The CFS of both probiotics alleviated the cytotoxicity of all the C. perfringens strains, which was dependent on the dose. The results confirm the suitability of the CHIC-8E11 cell line for the study of host-pathogen cell interactions in the context of NE caused by C. perfringens and reveal a beneficial mode of action of B. animalis subsp. lactis AG02 in reducing C. perfringens cell adhesion and, together with L. acidophilus AG01, in reducing C. perfringens cytotoxicity.

The Danish lung cancer registry: A nationwide validation study.

BACKGROUND: This study evaluates the validity of the information in the Danish Lung Cancer Registry (DLCR). Since 2000, the DLCR has been a tool for monitoring interventions and outcome of all Danish lung cancer patients with the intent to streamline and improve treatment and survival. The DLCR receives information from the Danish Patient Registries in addition to clinical information from the treating physicians. In the year 2022, more than 50 papers have been published using DLCR as a data source. However, the DLCR has not previously been validated. METHODS: A random sample of 1000 patients diagnosed with non-small cell lung cancer from 2014 to 2016 and recorded in the DLCR were included for validation. Medical records were reviewed and were considered as the "gold standard" to which data listed in the DLCR were compared. RESULTS: Information was retrieved from medical charts for all patients. Agreement on stage at diagnosis was 90.1 % (95 % CI 88.0-91.9) and on date of diagnoses was 93.8 (95 % CI 92.1-93.2). Agreement on smoking status in pack years (+/- 10 pack years) was 91.2 % (95 % CI 88.6-93.2). The positive predictive value of treatment intent was 87.4 (95 % CI 85.1-89.6). CONCLUSION: The data in the DLCR are complete, detailed and accurate. The comparison of data from the DLCR with the medical records revealed overall high validity of the data in the registry.

Weak signal extraction enabled by deep neural network denoising of diffraction data.

The removal or cancellation of noise has wide-spread applications in imaging and acoustics. In applications in everyday life, such as image restoration, denoising may even include generative aspects, which are unfaithful to the ground truth. For scientific use, however, denoising must reproduce the ground truth accurately. Denoising scientific data is further challenged by unknown noise profiles. In fact, such data will often include noise from multiple distinct sources, which substantially reduces the applicability of simulation-based approaches. Here we show how scientific data can be denoised by using a deep convolutional neural network such that weak signals appear with quantitative accuracy. In particular, we study X-ray diffraction and resonant X-ray scattering data recorded on crystalline materials. We demonstrate that weak signals stemming from charge ordering, insignificant in the noisy data, become visible and accurate in the denoised data. This success is enabled by supervised training of a deep neural network with pairs of measured low- and high-noise data. We additionally show that using artificial noise does not yield such quantitatively accurate results. Our approach thus illustrates a practical strategy for noise filtering that can be applied to challenging acquisition problems.

Outcome of Incidental Pulmonary Nodules in a Real-World Setting.

OBJECTIVES: Early diagnosis of lung cancer is imperative to improve survival. Incidental pulmonary nodules (IPN) may represent early stages of lung cancer and appropriate follow-up and management of these nodules is important, but also very resource demanding. We aim to describe the results of the CT-based follow-up on a cohort of patients with IPN in terms of detected malignancies, the proportion undergoing invasive procedures, and the subsequent outcome. MATERIALS AND METHODS: Retrospective cohort study of patients in a CT IPN follow-up program who underwent a needle biopsy of the lung from 2018 to 2021 at Aarhus University Hospital. RESULTS: A total of 4181 patients with IPN were followed with CT control scans. Out of these 249 (6%) were diagnosed with lung cancer of which 224 (90%) were diagnosed as a result of the IPN follow-up. Seventy-five percent of the patients were diagnosed in stages I to II and curable treatment was possible in 77.9% of the patients. In the CT IPN follow-up program 449 patients underwent a CT guided needle biopsy. Out of these 190 patients underwent biopsy without the detection of malignancy, corresponding to 4.5% of the entire IPN population. CONCLUSION: The cumulated incidence of lung cancer in our population in the IPN follow-up program was 6%. The probability of malignancy when undergoing an invasive procedure on an IPN was 55.7% of which lung cancer was vastly predominant. The majority of lung cancers were diagnosed in an early and potentially curable stage.

Tuning magnetoelectricity in a mixed-anisotropy antiferromagnet.

Control of magnetization and electric polarization is attractive in relation to tailoring materials for data storage and devices such as sensors or antennae. In magnetoelectric materials, these degrees of freedom are closely coupled, allowing polarization to be controlled by a magnetic field, and magnetization by an electric field, but the magnitude of the effect remains a challenge in the case of single-phase magnetoelectrics for applications. We demonstrate that the magnetoelectric properties of the mixed-anisotropy antiferromagnet LiNi1-xFexPO4 are profoundly affected by partial substitution of Ni2+ ions with Fe2+ on the transition metal site. This introduces random site-dependent single-ion anisotropy energies and causes a lowering of the magnetic symmetry of the system. In turn, magnetoelectric couplings that are symmetry-forbidden in the parent compounds, LiNiPO4 and LiFePO4, are unlocked and the dominant coupling is enhanced by almost two orders of magnitude. Our results demonstrate the potential of mixed-anisotropy magnets for tuning magnetoelectric properties.

A Validated Register-Based Algorithm to Identify Patients Diagnosed with Recurrence of Surgically Treated Stage I Lung Cancer in Denmark.

Introduction: Recurrence of cancer is not routinely registered in Danish national health registers. This study aimed to develop and validate a register-based algorithm to identify patients diagnosed with recurrent lung cancer and to estimate the accuracy of the identified diagnosis date. Material and Methods: Patients with early-stage lung cancer treated with surgery were included in the study. Recurrence indicators were diagnosis and procedure codes recorded in the Danish National Patient Register and pathology results recorded in the Danish National Pathology Register. Information from CT scans and medical records served as the gold standard to assess the accuracy of the algorithm. Results: The final population consisted of 217 patients; 72 (33%) had recurrence according to the gold standard. The median follow-up time since primary lung cancer diagnosis was 29 months (interquartile interval: 18-46). The algorithm for identifying a recurrence reached a sensitivity of 83.3% (95% CI: 72.7-91.1), a specificity of 93.8% (95% CI: 88.5-97.1), and a positive predictive value of 87.0% (95% CI: 76.7-93.9). The algorithm identified 70% of the recurrences within 60 days of the recurrence date registered by the gold standard method. The positive predictive value of the algorithm decreased to 70% when the algorithm was simulated in a population with a recurrence rate of 15%. Conclusion: The proposed algorithm demonstrated good performance in a population with 33% recurrences over a median of 29 months. It can be used to identify patients diagnosed with recurrent lung cancer, and it may be a valuable tool for future research in this field. However, a lower positive predictive value is seen when applying the algorithm in populations with low recurrence rates.

Ca2+-Responsive Glyco-insulin.

Chemical modification of peptides and proteins, such as PEGylation and lipidation, creates conjugates with new properties. However, they are typically not dynamic or stimuli-responsive. Self-assembly controlled by a stimulus will allow adjusting properties directly. Here, we report that conjugates of oligogalacturonic acids (OGAs), isolated from plant-derived pectin, are Ca2+-responsive. We report the conjugation of OGA to human insulin (HI) to create new glyco-insulins. In addition, we coupled OGA to model peptides. We studied their self-assembly by dynamic light scattering, small-angle X-ray scattering, and circular dichroism, which showed that the self-assembly to form nanostructures depended on the length of the OGA sequence and Zn2+ and Ca2+ concentrations. Subcutaneous administration of OGA12-HI with Zn2+ showed a stable decrease in blood glucose over a longer period of time compared to HI, despite the lower receptor binding affinity.

Identification and Characterization of a Novel Species of Genus Akkermansia with Metabolic Health Effects in a Diet-Induced Obesity Mouse Model.

Akkermansia muciniphila is a well-known bacterium with the ability to degrade mucin. This metabolic capability is believed to play an important role in the colonization of this bacterium in the gut. In this study, we report the identification and characterization of a novel Akkermansia sp. DSM 33459 isolated from human feces of a healthy donor. Phylogenetic analysis based on the genome-wide average nucleotide identity indicated that the Akkermansia sp. DSM 33459 has only 87.5% similarity with the type strain A. muciniphila ATCC BAA-835. Akkermansia sp. DSM 33459 showed significant differences in its fatty acid profile and carbon utilization as compared to the type strain. The Akkermansia sp. DSM 33459 strain was tested in a preclinical obesity model to determine its effect on metabolic markers. Akkermansia sp. DSM 33459 showed significant improvement in body weight, total fat weight, and resistin and insulin levels. Interestingly, these effects were more pronounced with the live form as compared to a pasteurized form of the strain. The strain showed production of agmatine, suggesting a potential novel mechanism for supporting metabolic and cognitive health. Based on its phenotypic features and phylogenetic position, it is proposed that this isolate represents a novel species in the genus Akkermansia and a promising therapeutic candidate for the management of metabolic diseases.

In-line Fluorescence Spectroscopy for Quantification of Low Amount of Active Pharmaceutical Ingredient.

The pharmaceutical industry is currently implementing new manufacturing principles and modernizing the related processing solutions. A key element in this development is implementation of process analytical technologies (PAT) for measuring product quality in a real-time mode, ideally for a continuously operating processing line. Near-infrared (NIR) spectroscopy is widely used for this purpose, but has limited use for low concentration formulations, due to its inherent detection limit. Light-induced fluorescence (LIF) spectroscopy is a PAT tool that can be used to quantify low concentrations of active pharmaceutical ingredient, and recent development of instrumentation has made it available for in-line applications. In this study, the content of tryptophan in a dynamic powder flow could be measured as low as 0.10 w/w % with LIF spectroscopy with good accuracy of RMSEP = 0.008 w/w %. Both partial least squares regression and support vector machines (SVM) were investigated, but we found SVM to be the better option due to non-linearities between the calibration test and the in-line measurements. With the use of SVM, LIF spectroscopy is a promising candidate for low concentration applications where NIR is not suitable.

Identifying interactions in omics data for clinical biomarker discovery using symbolic regression.

MOTIVATION: The identification of predictive biomarker signatures from omics and multi-omics data for clinical applications is an active area of research. Recent developments in assay technologies and machine learning (ML) methods have led to significant improvements in predictive performance. However, most high-performing ML methods suffer from complex architectures and lack interpretability. RESULTS: We present the application of a novel symbolic-regression-based algorithm, the QLattice, on a selection of clinical omics datasets. This approach generates parsimonious high-performing models that can both predict disease outcomes and reveal putative disease mechanisms, demonstrating the importance of selecting maximally relevant and minimally redundant features in omics-based machine-learning applications. The simplicity and high-predictive power of these biomarker signatures make them attractive tools for high-stakes applications in areas such as primary care, clinical decision-making and patient stratification. AVAILABILITY AND IMPLEMENTATION: The QLattice is available as part of a python package (feyn), which is available at the Python Package Index (https://pypi.org/project/feyn/) and can be installed via pip. The documentation provides guides, tutorials and the API reference (https://docs.abzu.ai/). All code and data used to generate the models and plots discussed in this work can be found in https://github.com/abzu-ai/QLattice-clinical-omics. SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

Tying Up a Loose End: On the Role of the C-Terminal CCHHRAG Fragment of the Metalloregulator CueR.

The transcriptional regulator CueR is activated by the binding of CuI , AgI , or AuI to two cysteinates in a near-linear fashion. The C-terminal CCHHRAG sequence in Escherichia coli CueR present potential additional metal binding ligands and here we explore the effect of deleting this fragment on the binding of AgI to CueR. CD spectroscopic and ESI-MS data indicate that the high AgI -binding affinity of WT-CueR is significantly reduced in Δ7C-CueR.[111 Ag PAC spectroscopy demonstrates that the WT-CueR metal site structure (AgS2 ) is conserved, but less populated in the truncated variant. Thus, the function of the C-terminal fragment may be to stabilize the two-coordinate metal site for cognate monovalent metal ions. In a broader perspective this is an example of residues beyond the second coordination sphere affecting metal site physicochemical properties while leaving the structure unperturbed.

Magnetic Bloch oscillations and domain wall dynamics in a near-Ising ferromagnetic chain.

When charged particles in periodic lattices are subjected to a constant electric field, they respond by oscillating. Here we demonstrate that the magnetic analogue of these Bloch oscillations are realised in a ferromagnetic easy axis chain. In this case, the "particles" undergoing oscillatory motion in the presence of a magnetic field are domain walls. Inelastic neutron scattering reveals three distinct components of the low energy spin-dynamics including a signature Bloch oscillation mode. Using parameter-free theoretical calculations, we are able to account for all features in the excitation spectrum, thus providing detailed insights into the complex dynamics in spin-anisotropic chains.

[Cocaine-induced asthma exacerbation].

Asthma is one of the most common chronic diseases in children and adults. Cocaine is associated with asthma exacerbations. In Denmark, the prevalence of cocaine use has been increasing in recent years. This is a case report of a 47-year-old male with acute asthma exacerbation after cocaine use. Cocaine use is probably an underestimated reason for acute asthma exacerbations.

[Rational use of systemic corticosteroid in the treatment of obstructive lung disease, asthma, and allergic rhinitis].

The anti-inflammatory effect of systemic corticosteroid (CS) on obstructive lung diseases and seasonal allergic rhinitis is well known. So are the physiological side-effects of CS. A major development in inhalation and biologic treatment as well as hyposensibilisation has taken place in recent years and evidence of personalized use of CS in acute exacerbations increases. We review the side effects of CS and the rationale for use of systemic CS in treatment of obstructive lung diseases as asthma and COPD, as well as seasonal allergic rhinitis.

Chirality transmission in macromolecular domains.

Chiral communications exist in secondary structures of foldamers and copolymers via a network of noncovalent interactions within effective intermolecular force (IMF) range. It is not known whether long-range chiral communication exists between macromolecular tertiary structures such as peptide coiled-coils beyond the IMF distance. Harnessing the high sensitivity of single-molecule force spectroscopy, we investigate the chiral interaction between covalently linked DNA duplexes and peptide coiled-coils by evaluating the binding of a diastereomeric pair of three DNA-peptide conjugates. We find that right-handed DNA triple helices well accommodate peptide triple coiled-coils of the same handedness, but not with the left-handed coiled-coil stereoisomers. This chiral communication is effective in a range (<4.5 nm) far beyond canonical IMF distance. Small-angle X-ray scattering and molecular dynamics simulation indicate that the interdomain linkers are tightly packed via hydrophobic interactions, which likely sustains the chirality transmission between DNA and peptide domains. Our findings establish that long-range chiral transmission occurs in tertiary macromolecular domains, explaining the presence of homochiral pairing of superhelices in proteins.

Polydextrose with and without Bifidobacterium animalis ssp. lactis 420 drives the prevalence of Akkermansia and improves liver health in a multi-compartmental obesogenic mice study.

The past two decades of research have raised gut microbiota composition as a contributing factor to the development of obesity, and higher abundance of certain bacterial species has been linked to the lean phenotype, such as Akkermansia muciniphila. The ability of pre- and probiotics to affect metabolic health could be via microbial community alterations and subsequently changes in metabolite profiles, modulating for example host energy balance via complex signaling pathways. The aim of this mice study was to determine how administration of a prebiotic fiber, polydextrose (PDX) and a probiotic Bifidobacterium animalis ssp. lactis 420 (B420), during high fat diet (HFD; 60 kcal% fat) affects microbiota composition in the gastrointestinal tract and adipose tissue, and metabolite levels in gut and liver. In this study C57Bl/6J mice (N = 200) were split in five treatments and daily gavaged: 1) Normal control (NC); 2) HFD; 3) HFD + PDX; 4) HFD + B420 or 5) HFD + PDX + B420 (HFD+S). At six weeks of treatment intraperitoneal glucose-tolerance test (IPGTT) was performed, and feces were collected at weeks 0, 3, 6 and 9. At end of the intervention, ileum and colon mucosa, adipose tissue and liver samples were collected. The microbiota composition in fecal, ileum, colon and adipose tissue was analyzed using 16S rDNA sequencing, fecal and liver metabolomics were performed by nuclear magnetic resonance (NMR) spectroscopy. It was found that HFD+PDX intervention reduced body weight gain and hepatic fat compared to HFD. Sequencing the mice adipose tissue (MAT) identified Akkermansia and its prevalence was increased in HFD+S group. Furthermore, by the inclusion of PDX, fecal, lleum and colon levels of Akkermansia were increased and liver health was improved as the detoxification capacity and levels of methyl-donors were increased. These new results demonstrate how PDX and B420 can affect the interactions between gut, liver and adipose tissue.

Direct and indirect economic burden of lung cancer in Denmark a nationwide study.

Background: Lung cancer is the leading cause of cancer death worldwide, but the additional economic burden regarding direct and indirect costs is largely unknown. This study provides information on the economic consequences of lung cancer on a national level. Methods: From the Danish National Patient Registry (NPR) and the Danish Civil Registration System (CPR), 53,749 patients with lung cancer were identified and matched with 214,304 controls on age, gender, region of residence and marital status in the period 1998-2010. Direct and indirect costs, health care contacts and frequency, medication and social transfer payments were extracted from national databases. Results: Direct health care cost were higher for lung cancer patients than controls both before and after being diagnosed with lung cancer. At the year of diagnosis, health care cost peaked with cost of €21,497 compared to €2,880 for controls. Average difference in income from employment was €+3,118 in years prior to diagnosis and €+748 after diagnosis in favor of controls. Average difference in total public transfer income was €+1,288 before and €+441 after diagnosis, with higher public transfer income for lung cancer patients. Conclusion: For both genders, lung cancer was associated with significantly higher rates of health-related costs, medication costs, public transfer income, social transfer payments and significantly lower income from employment until retirement (age 65).

Routes to diagnosis and the association with the prognosis in patients with cancer - A nationwide register-based cohort study in Denmark.

BACKGROUND: The prognosis of cancer is related to how the cancer is identified, and where in the healthcare system the patient presents, i.e. routes to diagnosis (RtD). We aimed to describe the RtD for patients diagnosed with cancer in Denmark by using routinely collected register-based data and to investigate the association between RtD and prognosis measured as one-year all-cause mortality. METHODS: We conducted a population-based national cohort study by linking routinely collected Danish registry data. We categorised each patient into one of eight specified RtD based on an algorithm using a stepwise logic decision process. We described the proportions of patients with cancer diagnosed by different RtD. We examined associations between RtD and one-year all-cause mortality using logistic regression models adjusting for sex, age, cancer type, year of diagnosis, region of residence, and comorbidity. RESULTS: We included 144,635 cancers diagnosed in 139,023 patients in 2014-2017. The most common RtD were cancer patient pathway from primary care (45.9 %), cancer patient pathway from secondary care (20.0 %), unplanned hospital admission (15.8 %), and population-based screening (7.5 %). The one-year mortality ranged from 1.4 % in screened patients to 53.0 % in patients diagnosed through unplanned hospital admission. Patients with an unplanned admission were more likely to die within the first year after diagnosis (OR = 3.38 (95 %CI: 3.24-3.52)) compared to patients diagnosed through the cancer patient pathway from primary care. CONCLUSION: The majority of cancer patients were diagnosed through a cancer patient pathway. The RtD were associated with the prognosis, and the prognosis was worst in patients diagnosed through unplanned admission. The study suggests that linking routinely collected registry data could enable a national framework for RtD, which could serve to identify variations across patient-, health-, and system-related and healthcare factors. This information could be used in future research investigating markers for monitoring purposes.