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Protein–ligand interactions are increasingly profiled at high throughput using affinity selection and massively parallel sequencing. However, these assays do not provide the biophysical parameters that most rigorously quantify molecular interactions. Here we describe a flexible machine learning method, called ProBound, that accurately defines sequence recognition in terms of equilibrium binding constants or kinetic rates. This is achieved using a multi-layered maximum-likelihood framework that models both the molecular interactions and the data generation process. We show that ProBound quantifies transcription factor (TF) behavior with models that predict binding affinity over a range exceeding that of previous resources; captures the impact of DNA modifications and conformational flexibility of multi-TF complexes; and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with an assay called KD-seq, it determines the absolute affinity of protein–ligand interactions. We also apply ProBound to profile the kinetics of kinase–substrate interactions. ProBound opens new avenues for decoding biological networks and rationally engineering protein–ligand interactions.

Botulinum neurotoxin (BoNT) is used for the treatment of a number of ailments. The activity of the toxin that is isolated from bacterial cultures is frequently tested in the mouse lethality assay. Apart from the ethical concerns inherent to this assay, species-specific differences in the affinity for different BoNT serotypes give rise to activity results that differ from the activity in humans. Thus, BoNT/B is more active in mice than in humans. The current study shows that the stimulus-dependent release of a luciferase from a differentiated human neuroblastoma–based reporter cell line (SIMA-hPOMC1-26-Gluc) was inhibited by clostridial and recombinant BoNT/A to the same extent, whereas both clostridial and recombinant BoNT/B inhibited the release to a lesser extent and only at much higher concentrations, reflecting the low activity of BoNT/B in humans. By contrast, the genetically modified BoNT/B-MY, which has increased affinity for human synaptotagmin, and the BoNT/B protein receptor inhibited luciferase release effectively and with an EC50 comparable to recombinant BoNT/A. This was due to an enhanced uptake into the reporter cells of BoNT/B-MY in comparison to the recombinant wild-type toxin. Thus, the SIMA-hPOMC1-26-Gluc cell assay is a versatile tool to determine the activity of different BoNT serotypes providing human-relevant dose-response data., Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe; 1257

Monitoring the treatment outcome of canine cystic endometrial hyperplasia-pyometra complex (CEH-P) is essential to identify nonresponding patients who might require a rapid intervention to avoid life-threatening conditions. Uterine artery Doppler characterization may contribute to monitoring medically treated CEH-P, but published studies are currently lacking. Therefore, the aim of this longitudinal prospective observational study was to evaluate uterine artery resistance changes in the medical treatment of female dogs with CEH-P. Twelve diestrous female dogs suffering from CEH-P were treated with a combined protocol of cabergoline, cloprostenol, and antibiotics. The animals were clinically and ultrasonographically evaluated before the beginning of treatment (day 0) and on days 3, 7, 14, 21, and 28. The widest transverse diameter and luminal diameter of uterine horns were measured, as well as the peak systolic velocity (PSV) and end diastolic velocity (EDV) of uterine arteries. The resistance index (RI), pulsatility index (PI), and notch deep index (NDI) were calculated. On day 3, nine of 12 animals showed clinical improvement. In all these female dogs, the widest transverse sectional diameter (P 0.01), luminal diameter (P 0.01), PSV (P 0.01), and EDV (P 0.01) progressively decreased, while RI (P 0.01), PI (P 0.01), and NDI (P 0.01) increased up to day 21. In nonresponding dogs (3/12), Doppler parameters remained unchanged. Although comparisons of PSV, EDV, and NDI were significantly different, these results should be cautiously interpreted due to the low statistical power. female dogs that responded to this treatment showed an increase in uterine artery resistance, along with clinical and ultrasonographic improvement.

The concept of the digital twin as the representation of a physical object is currently under development and is delivering promising first results. At the same time, the goals and the definition of digital twins differ, sometimes significantly, depending on the area of application and use case. Therefore, the descriptions and concepts of digital twins in a specific application cannot simply be transferred to new fields of application. Meanwhile, battery cell manufacturing is a key of the energy and mobility transition that is still characterized by high costs as well as scrap rates and will benefit enormously from the use of digital twins. To provide a basis for the development of digital twins in battery cell manufacturing, this white paper presents a unified definition for the digital twin in battery cell manufacturing, based on existing work. For this purpose, three forms of the digital twin are described: the building twin, the machine twin, and the product twin. Each of these forms must be examined in detail so that components of the respective forms can be identified, exemplary use cases can be shown, and concrete goals as well as challenges can be defined. Based on the concepts described in this white paper, the digital twin will be used in battery cell production to track, optimize, and control products and processes in the future. In perspective, this can significantly improve energy, raw material, and cost efficiency.

Additional file 3. Review history.

Additional file 2: Table S1. Positive mutations identified in the LbCas12a saturation screen. Table S2. T-DNA vectors used in this study. Table S3. Oligos used in this study.

Additional file 1: Figure S1. Double mutations on LbCas12atransferred from AsCas12a Ultra reduced editing efficiency in HEK293 cells. Figure S2. Editing efficiency of 24 novel LbCas12a mutant proteins in HEK293 cells using the T7EI assay. Figure S3. Targeted mutagenesis by LbCas12a variants in rice and tomato protoplasts using low-concentration RNP delivery. A, single crRNA was delivered using 0.001 µM RNP in rice protoplast; B, multiplex 6 crRNAs were delivered using 0.006 µM RNP in tomato protoplast. Figure S4. Genotypes of T0 plants at 5 target sites of LbCas12a variants. Figure S5. Off-target analysis of LbCas12 variants in T0 rice plants.As per journal requirements, every additional file must have a corresponding caption. In this regard, please be informed that the caption was taken from the additional e-file itself. Please advise if the action taken is appropriate and amend if necessary.The captions look good!

Implementations of potentially transformative eHealth technologies are currently underway internationally, often with significant impact on national expenditure. Such large-scale efforts and expenditures have been justified on the grounds that picture archiving and communication systems (PACS), electronic prescribing (ePrescribing) and associated computerized provider (or physician) order entry systems (CPOE), and computerized decision support systems (CDSS) are supposed to help to address the problems of variable quality and safety in modern health care. However, the scientific basis of such claims, which are repeatedly made, remains to be firmly established. This paper has the objective to contribute to the scientific discourse on the relationship between the digitalization of hospital care and quality and safety of such care by exploring the experience in the Netherlands. The central question of this thesis is: What is the relation between the maturity of hospital EMR systems and the quality of care. The three sub-studies showed little or no association between maturity and quality of care. We found that implementing clinical documentation, especially nursing documentation, ‘Closed Loop Medication Administration’, and intelligent pathways including CDSS, present as a challenge. The interviewed medical specialists prefer digital over the old paper records. The fact that involved health professionals can access the patient data at any time they need it, is considered important. However, in practice, potential quality improvement lags behind as long as decision support cannot be applied by lack of a fully coded patient record. We believe that Dutch hospitals are only at the beginning of a digital transformation. Moreover, a number of preconditions must also be met, such as the active involvement of professionals and management. It is not just a technical transformation but mainly an organizational one.

The COVID-19 pandemic has led to face-to-face activities being developed in a virtual format that often offers a poor experience in areas such as education. Virtual Learning Environments have improved in recent years thanks to new technologies such as Virtual Reality or Chatbots. However, creating Virtual Learning Environments requires advanced programming knowledge, so this work is aimed to enable teachers to create these new environments easily. This work presents a set of extensions for App Inventor that facilitate the authoring of mobile learning apps that use Chatbots in a Virtual Reality environment, while simultaneously monitoring of student activity. This proposal is based on integrating block-based languages and Business Process Model and Notation diagrams. The developed extensions were successfully implemented in an educational app called Let’s date!. A quantitative analysis of the use of these extensions in App Inventor was also carried out, resulting in a significant reduction in the number of blocks required. The proposed contribution has demonstrated its validity in creating virtual learning environments through visual programming and modelling, reducing development complexity.