[Current regulations in the Animal Welfare Act and the significance for animal research]. / Aktuelle Regelungen im Tierschutzgesetz und Bedeutung für die tierexperimentelle Forschung.

Due to the legal implantation of the 3R principle, the number of laboratory animals decreased significantly over the past 10 years. In this article, the historical development of animal experiments over the last decade will be presented in the context of the current regulations of the Animal Welfare Act. It points out bureaucratic obstacles to the approval of animal experiments, which jeopardize Germany as a research location for both academia and industry. The article presents constructive proposals for solutions. This should be done in accordance with the DFG recommendation to ensure efficient biomedical research while maintaining the highest animal welfare standards.

Absolute structure determination of Berkecoumarin by X-ray and electron diffraction.

X-ray and electron diffraction methods independently identify the S-enantiomer of Berkecoumarin [systematic name: (S)-8-hydroxy-3-(2-hydroxypropyl)-6-methoxy-2H-chromen-2-one]. Isolated from Berkeley Pit Lake Penicillium sp., Berkecoumarin is a natural product with a light-atom composition (C13H14O5) that challenges in-house absolute structure determination by anomalous scattering. This study further demonstrates the utility of dynamical refinement of electron-diffraction data for absolute structure determination.

Comparative study of the gut microbial communities collected by scraping and swabbing in a fish model: a comprehensive guide to promote non-lethal procedures for gut microbial studies.

In the present study, we propose the use of swabs in non-lethal sampling procedures to collect the mucosa-adhered gut microbiota from the posterior intestine of fish, and therefore, we compare the bacterial communities collected by conventional scraping and by swabbing methods. For this purpose, samples of the posterior intestine of rainbow trout (Oncorhynchus mykiss) were collected first using the swabbing approach, and after fish euthanasia, by mucosa scraping. Finally, bacterial communities were compared by 16S rRNA gene Illumina sequencing. Results from the current study revealed that similar values of bacterial richness and diversity were found for both sampling procedures. Similarly, there were no differences between procedures when using qualitative metrics (Jaccard and unweighted UniFrac) for estimating inter-individual diversity, but the quantitative metrics (Bray-Curtis and weighted UniFrac) showed a higher dispersion when samples were obtained by swabbing compared to scraping. In terms of bacterial composition, there were differences in abundance for the phyla Firmicutes and Proteobacteria. The cause of these differential abundances may be the inability of the swab to access to certain areas, such as the basal region of the intestinal villi. Moreover, swabbing allowed a higher representation of low abundant taxa, which may also have an important role in host microbiome regardless of their low abundance. Overall, our results demonstrate that the sampling method is a factor to be considered in experimental design when studying gut bacterial communities to avoid potential biases in the interpretation or comparison of results from different studies. In addition, the advantages and disadvantages of each procedure (swabbing vs scraping) are discussed in detail, concluding that swabbing can be implemented as a reliable and non-lethal procedure for posterior gut microbiota studies, which is of particular interest for animal welfare and the 3Rs principle, and may offer a wide range of novel applications.

Reference Data Set for Circular Dichroism Spectroscopy Comprised of Validated Intrinsically Disordered Protein Models.

Circular dichroism (CD) spectroscopy is an analytical technique that measures the wavelength-dependent differential absorbance of circularly polarized light and is applicable to most biologically important macromolecules, such as proteins, nucleic acids, and carbohydrates. It serves to characterize the secondary structure composition of proteins, including intrinsically disordered proteins, by analyzing their recorded spectra. Several computational tools have been developed to interpret protein CD spectra. These methods have been calibrated and tested mostly on globular proteins with well-defined structures, mainly due to the lack of reliable reference structures for disordered proteins. It is therefore still largely unclear how accurately these computational methods can determine the secondary structure composition of disordered proteins. Here, we provide such a required reference data set consisting of model structural ensembles and matching CD spectra for eight intrinsically disordered proteins. Using this set of data, we have assessed the accuracy of several published CD prediction and secondary structure estimation tools, including our own CD analysis package, SESCA. Our results show that for most of the tested methods, their accuracy for disordered proteins is generally lower than for globular proteins. In contrast, SESCA, which was developed using globular reference proteins, but was designed to be applicable to disordered proteins as well, performs similarly well for both classes of proteins. The new reference data set for disordered proteins should allow for further improvement of all published methods.

Understanding the Effects of Adding Metal Oxides to Polylactic Acid and Polylactic Acid Blends on Mechanical and Rheological Behaviour, Wettability, and Photo-Oxidation Resistance.

Biopolymers are of growing interest, but to improve some of their poor properties and performance, the formulation of bio-based blends and/or adding of nanoparticles is required. For this purpose, in this work, two different metal oxides, namely zinc oxide (ZnO) and titanium dioxide (TiO2), at different concentrations (0.5, 1, and 2%wt.) were added in polylactic acid (PLA) and polylactic acid/polyamide 11 (PLA/PA11) blends to establish their effects on solid-state properties, morphology, melt behaviour, and photo-oxidation resistance. It seems that the addition of ZnO in PLA leads to a significant reduction in its rigidity, probably due to an inefficient dispersion in the melt state, while the addition of TiO2 does not penalize PLA rigidity. Interestingly, the addition of both ZnO and TiO2 in the PLA/PA11 blend has a positive effect on the rigidity because of blend morphology refinement and leads to a slight increase in film hydrophobicity. The photo-oxidation resistance of the neat PLA and PLA/PA11 blend is significantly reduced due to the presence of both metal oxides, and this must be considered when designing potential applications. The last results suggest that both metal oxides could be considered photo-sensitive degradant agents for biopolymer and biopolymer blends.

Synthesis and Thermal Decomposition of High-Entropy Layered Rare Earth Hydroxychlorides.

The synthesis of multicomponent and high-entropy compounds has become a rapidly developing field in advanced inorganic chemistry, making it possible to combine the properties of multiple elements in a single phase. This paper reports on the synthesis of a series of novel high-entropy layered rare earth hydroxychlorides, namely, (Sm,Eu,Gd,Y,Er)2(OH)5Cl, (Eu,Gd,Tb,Y,Er)2(OH)5Cl, (Eu,Gd,Dy,Y,Er)2(OH)5Cl, and (Eu,Gd,Y,Er,Yb)2(OH)5Cl, using a homogeneous hydrolysis technique under hydrothermal conditions. Elemental mapping proved the even distribution of rare earth elements, while luminescence spectroscopy confirmed efficient energy transfer between europium and other rare earth cations, thus providing additional evidence of the homogeneous distribution of rare earth elements within the crystal lattice. The average rare earth cation radii correlated linearly with the unit cell parameters (0.868 < R2 < 0.982) of the high-entropy layered rare earth hydroxychlorides. The thermal stability of the high-entropy layered rare earth hydroxychlorides was similar to that of individual hydroxychlorides and their binary solid solutions.

Automated detection of myocardial infarction based on an improved state refinement module for LSTM/GRU.

Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary arteries. The visual inspection of electrocardiogram (ECG) is the main diagnosis pattern, while it is taxing and time-consuming. Motivated from state refinement module for long short term memory (SRM-LSTM), we proposed two improved state refinement frameworks based on LSTM and gated recurrent unit (GRU) called ISRM-LSTM and ISRM-GRU. Both are capable of adaptively refining current states of sample points in ECG with a message passing mechanism than existing LSTM. To evaluate the validity, both are installed into convolutional network architecture and standard LSTM, GRU and Residual networks are employed as control groups across the Physikalisch-Technische Bundesanstalt database. Empirical results confirm noticeable performance improvements than control groups and several existing algorithms with an accuracy of 99.1%. To our knowledge, both modules are the first attempt to consider the interaction characteristics into deep network and improve interpretability exhibiting considerable potentials on lightweight devices thanks to only utilization of three channel ECGs.

Composition templating for heterogeneous nucleation of intermetallic compounds.

Refinement of intermetallic compounds (IMCs) through enhancing heterogeneous nucleation during casting process is an important approach to improve the properties of aluminium alloys, which greatly increases the economy value of recycled Al-alloys. However, heterogeneous nucleation of IMCs is inherently more difficult than that of a pure metal or a solid solution. It requires not only creation of a crystal structure but also the positioning of 2 or more different types of atoms in the lattice with specific composition close to that of the nucleated IMCs. Previous understanding on heterogeneous nucleation is based on structural templating, usually considering the small lattice misfit at the interface between the nucleating solid and substrate. In this work, we proposed a hypothesis and demonstrated that composition templating plays a critical role in heterogeneous nucleation of IMCs. The experimental results revealed that segregation of Fe atoms on the AlB2 surface, i.e., the Fe modified AlB2 particle, provides the required composition templating and hence enhances heterogeneous nucleation of α-Al15(Fe, Mn)3Si2, resulting in a significant refinement of the α-Al15(Fe, Mn)3Si2 particles in an Al-5 Mg-2Si-1.0Mn-1.2Fe alloy.

Predictability of Orthodontic Space Closure Using Invisalign Clear Aligners: A Retrospective Study.

Introduction Clear aligners have demonstrated success in achieving complex tooth movements. However, orthodontists have faced challenges related to the predictability of clear aligners. This retrospective study aimed to assess the predictability of ClinCheck® accuracy in space closure before and after Invisalign® treatment and to identify factors associated with the need for refinement. Methods Patient records from one private clinic in Makkah, Saudi Arabia, were analyzed, and a sample of 55 adult patients who had spacing and underwent Invisalign treatment were included. Data on demographic and orthodontic variables were collected, and a chi-square test was conducted to examine the association between the requirement for refinement and demographic as well as clinical/orthodontic factors. Furthermore, the initial and final space measurements were compared using paired t-tests across various demographic and clinical/orthodontic variables. Results After completing the treatment, 70.9% (N=39) of the cases did not require any orthodontic refinement. The mean final space measurement was higher for males compared to females (0.7 mm and 0.4 mm, respectively), individuals who received treatment in the upper compared to lower arch (0.5 and 0.4 mm, respectively), those with moderate compared to mild spacing (0.5 and 0.1 mm, respectively), and those with class III compared to class I Angle classification (0.9 and 0.3 mm, respectively). Additionally, patients with severe spacing had a significantly higher probability of requiring refinement compared to patients with mild spacing (adjusted odds ratio = 20.9; p < 0.05). Conclusion The study emphasizes the significance of careful patient selection and treatment planning, suggesting that orthodontists should consider overcorrecting in space closure when using clear aligners, especially in cases with more significant spacing.

The Phenix-AlphaFold webservice: Enabling AlphaFold predictions for use in Phenix.

Advances in machine learning have enabled sufficiently accurate predictions of protein structure to be used in macromolecular structure determination with crystallography and cryo-electron microscopy data. The Phenix software suite has AlphaFold predictions integrated into an automated pipeline that can start with an amino acid sequence and data, and automatically perform model-building and refinement to return a protein model fitted into the data. Due to the steep technical requirements of running AlphaFold efficiently, we have implemented a Phenix-AlphaFold webservice that enables all Phenix users to run AlphaFold predictions remotely from the Phenix GUI starting with the official 1.21 release. This webservice will be improved based on how it is used by the research community and the future research directions for Phenix.

Determining Protein Structures Using X-Ray Crystallography.

X-ray crystallography is a robust and widely used technique that facilitates the three-dimensional structure determination of proteins at an atomic scale. This methodology entails the growth of protein crystals under controlled conditions followed by their exposure to X-ray beams and the subsequent analysis of the resulting diffraction patterns via computational tools to determine the three-dimensional architecture of the protein. However, achieving high-resolution structures through X-ray crystallography can be quite challenging due to complexities associated with protein purity, crystallization efficiency, and crystal quality.In this chapter, we provide a detailed overview of the gene to structure determination pipeline used in X-ray crystallography, a crucial tool for understanding protein structures. The chapter covers the steps in protein crystallization, along with the processes of data collection, processing, structure determination, and refinement. The most commonly faced challenges throughout this procedure are also addressed. Finally, the importance of standardized protocols for reproducibility and accuracy is emphasized, as they are crucial for advancing the understanding of protein structure and function.

Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the majority of the experimental maps in the database lack atomic resolution features, making it challenging for machine learning-based methods to precisely determine protein structures from cryogenic electron microscopy density maps. On the other hand, protein structure prediction methods, such as AlphaFold2, leverage evolutionary information from protein sequences and have recently achieved groundbreaking accuracy. However, these methods often require manual refinement, which is labor intensive and time consuming. In this study, we present DeepTracer-Refine, an automated method that refines AlphaFold predicted structures by aligning them to DeepTracers modeled structure. Our method was evaluated on 39 multi-domain proteins and we improved the average residue coverage from 78.2 to 90.0% and average local Distance Difference Test score from 0.67 to 0.71. We also compared DeepTracer-Refine with Phenixs AlphaFold refinement and demonstrated that our method not only performs better when the initial AlphaFold model is less precise but also surpasses Phenix in run-time performance.

Information-based group sequential design for post-market safety monitoring of medical products using real world data.

Real world healthcare data are commonly used in post-market safety monitoring studies to address potential safety issues related to newly approved medical products. Such studies typically involve repeated evaluations of accumulating safety data with respect to pre-defined hypotheses, for which the group sequential design provides a rigorous and flexible statistical framework. A major challenge in designing a group sequential safety monitoring study is the uncertainty associated with product uptake, which makes it difficult to specify the final sample size or maximum duration of the study. To deal with this challenge, we propose an information-based group sequential design which specifies a target amount of information that would produce adequate power for detecting a clinically significant effect size. At each interim analysis, the variance estimate for the treatment effect of interest is used to compute the current information time, and a pre-specified alpha spending function is used to determine the stopping boundary. The proposed design can be applied to regression models that adjust for potential confounders and/or heterogeneous treatment exposure. Simulation results demonstrate that the proposed design performs reasonably well in realistic settings.

Dynamical refinement with multipolar electron scattering factors.

Dynamical refinement is a well established method for refining crystal structures against 3D electron diffraction (ED) data and its benefits have been discussed in the literature [Palatinus, Petrícek & Corrêa, (2015). Acta Cryst. A71, 235-244; Palatinus, Corrêa et al. (2015). Acta Cryst. B71, 740-751]. However, until now, dynamical refinements have only been conducted using the independent atom model (IAM). Recent research has shown that a more accurate description can be achieved by applying the transferable aspherical atom model (TAAM), but this has been limited only to kinematical refinements [Gruza et al. (2020). Acta Cryst. A76, 92-109; Jha et al. (2021). J. Appl. Cryst. 54, 1234-1243]. In this study, we combine dynamical refinement with TAAM for the crystal structure of 1-methyluracil, using data from precession ED. Our results show that this approach improves the residual Fourier electrostatic potential and refinement figures of merit. Furthermore, it leads to systematic changes in the atomic displacement parameters of all atoms and the positions of hydrogen atoms. We found that the refinement results are sensitive to the parameters used in the TAAM modelling process. Though our results show that TAAM offers superior performance compared with IAM in all cases, they also show that TAAM parameters obtained by periodic DFT calculations on the refined structure are superior to the TAAM parameters from the UBDB/MATTS database. It appears that multipolar parameters transferred from the database may not be sufficiently accurate to provide a satisfactory description of all details of the electrostatic potential probed by the 3D ED experiment.

Stimulus-dependent synaptic plasticity underlies neuronal circuitry refinement in the mouse primary visual cortex.

Perceptual learning improves our ability to interpret sensory stimuli present in our environment through experience. Despite its importance, the underlying mechanisms that enable perceptual learning in our sensory cortices are still not fully understood. In this study, we used in vivo two-photon imaging to investigate the functional and structural changes induced by visual stimulation in the mouse primary visual cortex (V1). Our results demonstrate that repeated stimulation leads to a refinement of V1 circuitry by decreasing the number of responsive neurons while potentiating their response. At the synaptic level, we observe a reduction in the number of dendritic spines and an overall increase in spine AMPA receptor levels in the same subset of neurons. In addition, visual stimulation induces synaptic potentiation in neighboring spines within individual dendrites. These findings provide insights into the mechanisms of synaptic plasticity underlying information processing in the neocortex.

3R-Refinement principles: elevating rodent well-being and research quality.

This review article delves into the details of the 3R-Refinement principles as a vital framework for ethically sound rodent research laboratory. It highlights the core objective of the refinement protocol, namely, to enhance the well-being of laboratory animals while simultaneously improving the scientific validity of research outcomes. Through an exploration of key components of the refinement principles, the article outlines how these ethics should be implemented at various stages of animal experiments. It emphasizes the significance of enriched housing environments that reduce stress and encourage natural behaviors, non-restraint methods in handling and training, refined dosing and sampling techniques that prioritize animal comfort, the critical role of optimal pain management and the importance of regular animal welfare assessment in maintaining the rodents well-being. Additionally, the advantages of collaboration with animal care and ethics committees are also mentioned. The other half of the article explains the extensive benefits of the 3R-Refinement protocol such as heightened animal welfare, enhanced research quality, reduced variability, and positive feedback from researchers and animal care staff. Furthermore, it addresses avenues for promoting the adoption of the protocol, such as disseminating best practices, conducting training programs, and engaging with regulatory bodies. Overall, this article highlights the significance of 3R-Refinement protocol in aligning scientific advancement with ethical considerations along with shaping a more compassionate and responsible future for animal research.

Appetitively motivated tasks in the IntelliCage reveal a higher motivational cost of spatial learning in male than female mice.

The IntelliCage (IC) permits the assessment of the behavior and learning abilities of mice in a social home cage context. To overcome water deprivation as an aversive driver of learning, we developed protocols in which spatial learning is motivated appetitively by the preference of mice for sweetened over plain water. While plain water is available at all times, only correct task responses give access to sweetened water rewards. Under these conditions, C57BL/6J mice successfully mastered a corner preference task with the reversal and also learned a more difficult time-place task with reversal. However, the rate of responding to sweetened water decreased strongly with increasing task difficulty, indicating that learning challenges and reduced success in obtaining rewards decreased the motivation of the animals to seek sweetened water. While C57BL/6J mice of both sexes showed similar initial taste preferences and learned similarly well in simple learning tasks, the rate of responding to sweetened water and performance dropped more rapidly in male than in female mice in response to increasing learning challenges. Taken together, our data indicate that male mice can have a disadvantage relative to females in mastering difficult, appetitively motivated learning tasks, likely due to sex differences in value-based decision-making.

Development of a novel primate welfare assessment tool for research macaques.

Primates are important species for biomedical research and ensuring their good welfare is critical for research translatability and ethical responsibility. Systematic animal welfare assessments can support continuous programme improvements and build institutional awareness of areas requiring more attention. A multi-facility, collaborative project aimed to develop and implement a novel primate welfare assessment tool (PWAT) for use with research macaques. PWAT development involved: establishing an internal focus group of primate subject matter experts, identifying animal welfare categories and descriptors based on literature review, developing a preliminary tool, beta-testing the tool to ensure practicality and final consensus on descriptors, finalising the tool in a database with semi-automated data analysis, and delivering the tool to 13 sites across four countries. The tool uses input- and outcome-based measures from six categories: physical, behavioural, training, environmental, procedural, and culture of care. The final tool has 133 descriptors weighted based upon welfare impact, and is split into three forms for ease of use (room level, site level, and personnel interviews). The PWAT was trialled across facilities in March and September 2022 for benchmarking current macaque behavioural management programmes. The tool successfully distinguished strengths and challenges at the facility level and across sites. Following this benchmarking, the tool is being applied semi-annually to assess and monitor progress in behavioural management programmes. The development process of the PWAT demonstrates that evidence-based assessment tools can be developed through collaboration and consensus building, which are important for uptake and applicability, and ultimately for promoting global improvements in research macaque welfare.

Omadacycline dihydrate, C29H40N4O7·2H2O, from X-ray powder diffraction data.

The crystal structure of the title compound {systematic name: (4S,4aS,5aR,12aR)-4,7-bis-(di-methyl-amino)-9-[(2,2-di-methyl-propyl-amino)-meth-yl]-1,10,11,12a-tetra-hydroxy-3,12-dioxo-4a,5,5a,6-tetra-hydro-4H-tetra-cene-2-carb-oxamide dihydrate, C29H40N4O7·2H2O} has been solved and refined using synchrotron X-ray powder diffraction data: it crystallizes in space group R3 with a = 24.34430 (7), c = 14.55212 (4) Å, V = 7468.81 (2) Å3 and Z = 9. Most of the hydrogen bonds are intra-molecular, but two classical N-H⋯O inter-molecular hydrogen bonds (along with probable weak C-H⋯O and C-H⋯N hydrogen bonds) link the mol-ecules into a three-dimensional framework. The framework contains voids, which contain disordered water mol-ecules. Keto-enol tautomerism is apparently important in this mol-ecule, and the exact mol-ecular structure is ambiguous.

A study on disinfection and adhesion behaviour between bacteria and photocatalytic nanostructures by extended DLVO.

Recently, there has been a growing concern regarding the increased contamination of water by bacteria. As a result, more attention has been paid to the potential benefits of utilizing nano adsorbents and photocatalysis for water purification. In order to better manipulate the physicochemical properties, it is crucial to gain a comprehensive understanding of the molecular behaviour between nanoparticles and pathogens. This article investigates the various interactions that can occur between Fe3O4-SiO2-TiO2 (FST) nanoparticles and bacterial cells. Moreover, it explores the impact of the SiO2 mid-layer and the governing interaction in the adhesion and degradation processes. In this regard, FST nanoparticles were prepared, and their adhesion behaviour to E. coli bacterial cells was evaluated using extended DLVO (Derjaguin-Landau-Verwey-Overbeek) theory. The following results revealed that the presence of silica transformed FST into a more hydrophobic material with a positively charged surface, thereby enhancing its affinity for bacterial adsorption. Additionally, SiO2 prevented electron/hole recombination. Amongst the various interactions, Lewis acid-base interactions had the greatest influence on the total energy and lacking energy barriers led to irreversible adhesion. Moreover, the presence of an increased number of ·OH groups on the surface resulted in enhanced bactericidal properties of FST, leading to severe damage of E. coli cells through the formation of a greater number of hydrogen bonds on the bacterial surface, which is the basis of the proposed mechanism for destruction of the bacterial structure.