Alien plant species distribution in Romania: a nationwide survey following the implementation of the EU Regulation on Invasive Alien Species.

Background: Biological invasions pose an increasing risk to nature, social security and the economy, being ranked amongst the top five threats to biodiversity. Managing alien and invasive species is a priority for the European Union, as outlined in the EU Biodiversity Strategy for 2030 and the Kunming-Montreal Global Biodiversity Framework. Alien plant species are acknowledged to impact the economy and biodiversity; thus, analysing the distribution of such species provides valuable inputs for the management and decision-making processes. The database presented in the current study is the first consolidated checklist of alien plant species that are present in Romania, both of European Union concern and of national interest. This database complements a prior published distribution, based only on records from literature, bringing new information regarding the occurrence of alien plants in Romania, as revealed by a nationwide field survey. We consider this database a valuable instrument for managing biological invasions at both national and regional levels, as it can be utilised in further research studies and in drafting management and action plans, assisting stakeholders in making informed decisions and implementing management actions. New information: We present the results of the first nationwide survey of alien plant species in Romania, conducted between 2019 and 2022, in the framework of a national project coordinated by the Ministry of Environment, Waters and Forests and the University of Bucharest. The present database complements and updates the database published by Sirbu et. al (2022), which included occurrence records published until 2019. The new database includes 98323 occurrence records for 396 alien plant species in 77 families, with most species belonging to the Asteraceae family. One alien plant species in our database, the black locust Robiniapseudoacacia L., had more than 10,000 occurrence records. The distribution database also includes information on newly-reported invasive alien plant species of European Union concern in Romania (i.e. the floating primrose-willow Ludwigiapeploides (Kunth) P.H.Raven) and documents the presence of plants in 44 additional families compared to Sirbu et al. (2022). Each entry includes information on species taxonomy, location, year, person who recorded and identified the alien plant, geographical coordinates and taxon rank.

Hierarchical Protofilament Intertwining Rules the Formation of Mixed-Curvature Amyloid Polymorphs.

Amyloid polymorphism is a hallmark of almost all amyloid species, yet the mechanisms underlying the formation of amyloid polymorphs and their complex architectures remain elusive. Commonly, two main mesoscopic topologies are found in amyloid polymorphs characterized by non-zero Gaussian and mean curvatures: twisted ribbons and helical fibrils, respectively. Here, a rich heterogeneity of configurations is demonstrated on insulin amyloid fibrils, where protofilament packing can occur, besides the common polymorphs, also in a combined mode forming mixed-curvature polymorphs. Through AFM statistical analysis, an extended array of heterogeneous architectures that are rationalized by mesoscopic theoretical arguments are identified. Notably, an unusual fibrillization pathway is also unraveled toward mixed-curvature polymorphs via the widespread recruitment and intertwining of protofilaments and protofibrils. The results present an original view of amyloid polymorphism and advance the fundamental understanding of the fibrillization mechanism from single protofilaments into mature amyloid fibrils.

Binding Dynamics of a Stapled Peptide Targeting the Transcription Factor NF-Y.

Transcription factors (TFs) play a central role in gene regulation, and their malfunction can result in a plethora of severe diseases. TFs are therefore interesting therapeutic targets, but their involvement in protein-protein interaction networks and the frequent lack of well-defined binding pockets render them challenging targets for classical small molecules. As an alternative, peptide-based scaffolds have proven useful, in particular with an α-helical active conformation. Peptide-based strategies often require extensive structural optimization efforts, which could benefit from a more detailed understanding of the dynamics in inhibitor/protein interactions. In this study, we investigate how truncated stapled α-helical peptides interact with the transcription factor Nuclear Factor-Y (NF-Y). We identified a 13-mer minimal binding core region, for which two crystal structures with an altered C-terminal peptide conformation when bound to NF-Y were obtained. Subsequent molecular dynamics simulations confirmed that the C-terminal part of the stapled peptide is indeed relatively flexible while still showing defined interactions with NF-Y. Our findings highlight the importance of flexibility in the bound state of peptides, which can contribute to overall binding affinity.

Elucidating the role of water in collagen self-assembly by isotopically modulating collagen hydration.

Water is known to play an important role in collagen self-assembly, but it is still largely unclear how water-collagen interactions influence the assembly process and determine the fibril network properties. Here, we use the H[Formula: see text]O/D[Formula: see text]O isotope effect on the hydrogen-bond strength in water to investigate the role of hydration in collagen self-assembly. We dissolve collagen in H[Formula: see text]O and D[Formula: see text]O and compare the growth kinetics and the structure of the collagen assemblies formed in these water isotopomers. Surprisingly, collagen assembly occurs ten times faster in D[Formula: see text]O than in H[Formula: see text]O, and collagen in D[Formula: see text]O self-assembles into much thinner fibrils, that form a more inhomogeneous and softer network, with a fourfold reduction in elastic modulus when compared to H[Formula: see text]O. Combining spectroscopic measurements with atomistic simulations, we show that collagen in D[Formula: see text]O is less hydrated than in H[Formula: see text]O. This partial dehydration lowers the enthalpic penalty for water removal and reorganization at the collagen-water interface, increasing the self-assembly rate and the number of nucleation centers, leading to thinner fibrils and a softer network. Coarse-grained simulations show that the acceleration in the initial nucleation rate can be reproduced by the enhancement of electrostatic interactions. These results show that water acts as a mediator between collagen monomers, by modulating their interactions so as to optimize the assembly process and, thus, the final network properties. We believe that isotopically modulating the hydration of proteins can be a valuable method to investigate the role of water in protein structural dynamics and protein self-assembly.

Inside anticancer therapy resistance and metastasis. Focus on CD36.

Despite recent advances in targeted cancer therapies, drug resistance remains an important setback in tumor control. Understanding the complex mechanisms involved in both innate and acquired drug resistance represents the first step in discovering novel therapeutic agents. Because of its importance in tumorigenesis, progression, and metastasis, lipid metabolism is increasingly garnering attention. CD36 is a membrane receptor at the top of the signaling cascade that transports lipids. Its expression has been repeatedly presented as an unfavorable prognostic factor for various tumor types, raising the question: could CD36 be a critical factor in cancer treatment resistance? In our review, we set out to explore the most prominent studies on the implication of CD36 in resistance to platinum-based drugs and other adjuvant cancer therapies in solid and haematological neoplasia. Moreover, we provide an overview of the latest anti-CD36 cancer therapies, thus opening new perspectives for future personalized medicine.

EEG-based spatiotemporal dynamics of fast ripple networks and hubs in infantile epileptic spasms.

OBJECTIVE: Infantile epileptic spasms (IS) are epileptic seizures that are associated with increased risk for developmental impairments, adult epilepsies, and mortality. Here, we investigated coherence-based network dynamics in scalp EEG of infants with IS to identify frequency-dependent networks associated with spasms. We hypothesized that there is a network of increased fast ripple connectivity during the electrographic onset of clinical spasms, which is distinct from controls. METHODS: We retrospectively analyzed peri-ictal and interictal EEG recordings of 14 IS patients. The data was compared with 9 age-matched controls. Wavelet phase coherence (WPC) was computed between 0.2 and 400 Hz. Frequency- and time-dependent brain networks were constructed using this coherence as the strength of connection between two EEG channels, based on graph theory principles. Connectivity was evaluated through global efficiency (GE) and channel-based closeness centrality (CC), over frequency and time. RESULTS: GE in the fast ripple band (251-400 Hz) was significantly greater following the onset of spasms in all patients (P < 0.05). Fast ripple networks during the first 10s from spasm onset show enhanced anteroposterior gradient in connectivity (posterior > central > anterior, Kruskal-Wallis P < 0.001), with maximum CC over the centroparietal channels in 10/14 patients. Additionally, this anteroposterior gradient in CC connectivity is observed during spasms but not during the interictal awake or asleep states of infants with IS. In controls, anteroposterior gradient in fast ripple CC was noted during arousals and wakefulness but not during sleep. There was also a simultaneous decrease in GE in the 5-8 Hz range after the onset of spasms (P < 0.05), of unclear biological significance. SIGNIFICANCE: We identified an anteroposterior gradient in the CC connectivity of fast ripple hubs during spasms. This anteroposterior gradient observed during spasms is similar to the anteroposterior gradient in the CC connectivity observed in wakefulness or arousals in controls, suggesting that this state change is related to arousal networks.

Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning.

Existing therapies for neurodegenerative diseases like Parkinson's and Alzheimer's address only their symptoms and do not prevent disease onset. Common therapeutic agents, such as small molecules and antibodies struggle with insufficient selectivity, stability and bioavailability, leading to poor performance in clinical trials. Peptide-based therapeutics are emerging as promising candidates, with successful applications for cardiovascular diseases and cancers due to their high bioavailability, good efficacy and specificity. In particular, cyclic peptides have a long in vivo stability, while maintaining a robust antibody-like binding affinity. However, the de novo design of cyclic peptides is challenging due to the lack of long-lived druggable pockets of the target polypeptide, absence of exhaustive conformational distributions of the target and/or the binder, unknown binding site, methodological limitations, associated constraints (failed trials, time, money) and the vast combinatorial sequence space. Hence, efficient alignment and cooperation between disciplines, and synergies between experiments and simulations complemented by popular techniques like machine-learning can significantly speed up the therapeutic cyclic-peptide development for neurodegenerative diseases. We review the latest advancements in cyclic peptide design against amyloidogenic targets from a computational perspective in light of recent advancements and potential of machine learning to optimize the design process. We discuss the difficulties encountered when designing novel peptide-based inhibitors and we propose new strategies incorporating experiments, simulations and machine learning to design cyclic peptides to inhibit the toxic propagation of amyloidogenic polypeptides. Importantly, these strategies extend beyond the mere design of cyclic peptides and serve as template for the de novo generation of (bio)materials with programmable properties.

Training in tools to develop quantitative microbial risk assessment of ready-to-eat food with a comparison between the Romanian and Spanish food supply chains.

The prevention and control of bacterial contamination on ready-to-eat (RTE) fresh produce is an essential task to ensure food safety. Therefore, the development of novel and effective decontamination technologies to ensure microbiological safety of fruits and vegetables has gained considerable attention and new sanitisation methods are needed. The antimicrobial activity of essential oils (EOs) is well documented, but their application in fresh produce remains a challenge due to their hydrophobic nature. Thus, nanoemulsions efficiently contribute to support the use of EOs in foods by enhancing their dispersibility, their contact area and facilitating the introduction into bacterial cells. The combination of these factors ultimately increases their antimicrobial activity. Quantitative microbial risk assessment (QMRA) is gaining more attention as an effective tool to assess and prevent potential risks associated with food-borne pathogens. In this context, the current project aims to study the effectiveness of different washing methods based on nanoemulsified EOs, comparing them against traditional methods, using a QMRA model for Escherichia coli O157:H7 on cherry tomatoes. Different simulations within a stochastic risk assessment model were implemented using the biorisk package for R, aiming to describe microbial behaviour and biological risk along the Romanian and Spanish food supply chains of RTE fresh produce. Nanoemulsions were prepared using oregano and rosemary EOs, each from Romania and Spain. The four nanoemulsions were evaluated as decontamination treatments to control the growth of E. coli O157:H7 on artificially contaminated cherry tomatoes. The decontamination treatments showed encouraging results, comparable to commonly used chlorine solutions. Therefore, oregano and rosemary nanoemulsions are promising and could be a feasible alternative for chlorine solutions in the reduction of microbiological contaminants.

Leukemic conversion involving RAS mutations of type 1 CALR-mutated primary myelofibrosis in a patient treated for HCV cirrhosis: a case report.

Somatic frameshift mutations in exon 9 of calreticulin (CALR) gene are recognized as disease drivers in primary myelofibrosis (PMF), one of the three classical Philadelphia-negative myeloproliferative neoplasms (MPNs). Type 1/type 1-like CALR mutations particularly confer a favorable prognostic and survival advantage in PMF patients. We report an unusual case of PMF incidentally diagnosed in a 68-year-old woman known with hepatitis C virus (HCV) cirrhosis who developed a progressive painful splenomegaly, without anomalies in blood cell counts. While harboring a type 1 CALR mutation, the patient underwent a leukemic transformation in less than 1 year from diagnosis, with a lethal outcome. Analysis of paired DNA samples from chronic and leukemic phases by a targeted next-generation sequencing (NGS) panel and single-nucleotide polymorphism (SNP) microarray revealed that the leukemic clone developed from the CALR-mutated clone through the acquisition of genetic events in the RAS signaling pathway: an increased variant allele frequency of the germline NRAS Y64D mutation present in the chronic phase (via an acquired uniparental disomy of chromosome 1) and gaining NRAS G12D in the blast phase. SNP microarray analysis showed five clinically significant copy number losses at regions 7q22.1, 8q11.1-q11.21, 10p12.1-p11.22, 11p14.1-p11.2, and Xp11.4, revealing a complex karyotype already in the chronic phase. We discuss how additional mutations, detected by NGS, as well as HCV infection and antiviral therapy, might have negatively impacted this type 1 CALR-mutated PMF. We suggest that larger studies are required to determine if more careful monitoring would be needed in MPN patients also carrying HCV and receiving anti-HCV treatment.

The Metabolism of Lufotrelvir, a Prodrug Investigated for the Treatment of SARS-COV2 in Humans Following Intravenous Administration.

The metabolism of lufotrelvir, a novel phosphate prodrug of PF-00835231 for the treatment of COVID-19, was evaluated in healthy human volunteers and clinical trial participants with COVID-19 following intravenous infusion. The prodrug was completely converted to PF-00835231 that was subsequently cleared by hydrolysis, hydroxylation, ketoreduction, epimerization, renal clearance, and secretion into the feces. The main circulating metabolite was a hydrolysis product (M7) that was present at concentrations greater than PF-00835231, and this was consistent between healthy volunteers and participants with COVID-19. On administration of [14C]lufotrelvir, only 63% of the dose was obtained in excreta over 10 days and total drug-related material demonstrated a prolonged terminal phase half-life in plasma. A considerable portion of the labeled material was unextractable from fecal homogenate and plasma. The position of the carbon-14 atom in the labeled material was at a leucine carbonyl, and pronase digestion of the pellet derived from extraction of the fecal homogenate showed that [14C]leucine was released. SIGNIFICANCE STATEMENT: Lufotrelvir is an experimental phosphate prodrug intravenous therapy investigated for the potential treatment of COVID-19 in a hospital setting. The overall metabolism of lufotrelvir was determined in human healthy volunteers and clinical trial participants with COVID-19. Conversion of the phosphate prodrug to the active drug PF-00835231 was complete and the subsequent metabolic clearance of the active drug was largely via amide bond hydrolysis. Substantial drug-related material was not recovered due to loss of the carbon-14 label to endogenous metabolism.

Deep learning based automated delineation of the intraprostatic gross tumour volume in PSMA-PET for patients with primary prostate cancer.

PURPOSE: With the increased use of focal radiation dose escalation for primary prostate cancer (PCa), accurate delineation of gross tumor volume (GTV) in prostate-specific membrane antigen PET (PSMA-PET) becomes crucial. Manual approaches are time-consuming and observer dependent. The purpose of this study was to create a deep learning model for the accurate delineation of the intraprostatic GTV in PSMA-PET. METHODS: A 3D U-Net was trained on 128 different 18F-PSMA-1007 PET images from three different institutions. Testing was done on 52 patients including one independent internal cohort (Freiburg: n = 19) and three independent external cohorts (Dresden: n = 14 18F-PSMA-1007, Boston: Massachusetts General Hospital (MGH): n = 9 18F-DCFPyL-PSMA and Dana-Farber Cancer Institute (DFCI): n = 10 68Ga-PSMA-11). Expert contours were generated in consensus using a validated technique. CNN predictions were compared to expert contours using Dice similarity coefficient (DSC). Co-registered whole-mount histology was used for the internal testing cohort to assess sensitivity/specificity. RESULTS: Median DSCs were Freiburg: 0.82 (IQR: 0.73-0.88), Dresden: 0.71 (IQR: 0.53-0.75), MGH: 0.80 (IQR: 0.64-0.83) and DFCI: 0.80 (IQR: 0.67-0.84), respectively. Median sensitivity for CNN and expert contours were 0.88 (IQR: 0.68-0.97) and 0.85 (IQR: 0.75-0.88) (p = 0.40), respectively. GTV volumes did not differ significantly (p > 0.1 for all comparisons). Median specificity of 0.83 (IQR: 0.57-0.97) and 0.88 (IQR: 0.69-0.98) were observed for CNN and expert contours (p = 0.014), respectively. CNN prediction took 3.81 seconds on average per patient. CONCLUSION: The CNN was trained and tested on internal and external datasets as well as histopathology reference, achieving a fast GTV segmentation for three PSMA-PET tracers with high diagnostic accuracy comparable to manual experts.

Decrypting Integrins by Mixed-Solvent Molecular Dynamics Simulations.

Integrins are a family of α/ß heterodimeric cell surface adhesion receptors which are capable of transmitting signals bidirectionally across membranes. They are known for their therapeutic potential in a wide range of diseases. However, the development of integrin-targeting medications has been impacted by unexpected downstream effects including unwanted agonist-like effects. Allosteric modulation of integrins is a promising approach to potentially overcome these limitations. Applying mixed-solvent molecular dynamics (MD) simulations to integrins, the current study uncovers hitherto unknown allosteric sites within the integrin α I domains of LFA-1 (αLß2; CD11a/CD18), VLA-1 (α1ß1; CD49a/CD29), and Mac-1 (αMß2, CD11b/CD18). We show that these pockets are putatively accessible to small-molecule modulators. The findings reported here may provide opportunities for the design of novel allosteric integrin inhibitors lacking the unwanted agonism observed with earlier as well as current integrin-targeting drugs.

Bridging the gap between mechanistic biological models and machine learning surrogates.

Mechanistic models have been used for centuries to describe complex interconnected processes, including biological ones. As the scope of these models has widened, so have their computational demands. This complexity can limit their suitability when running many simulations or when real-time results are required. Surrogate machine learning (ML) models can be used to approximate the behaviour of complex mechanistic models, and once built, their computational demands are several orders of magnitude lower. This paper provides an overview of the relevant literature, both from an applicability and a theoretical perspective. For the latter, the paper focuses on the design and training of the underlying ML models. Application-wise, we show how ML surrogates have been used to approximate different mechanistic models. We present a perspective on how these approaches can be applied to models representing biological processes with potential industrial applications (e.g., metabolism and whole-cell modelling) and show why surrogate ML models may hold the key to making the simulation of complex biological systems possible using a typical desktop computer.

The Impacts of Working With Victims of Sexual Violence: A Rapid Evidence Assessment.

AIM: Supporting clients who have experienced trauma can lead to trauma symptoms in those working with them; workers in the sexual violence field are at heightened risks of these. This article collated and critically appraised papers, published from 2017 onward, in the area of people assisting victims of sexual violence. It explores the impacts and effects the work has on them, their coping and self-care mechanisms, and organizational support offered to them. DESIGN: A question-based rapid evidence assessment with a triangulated weight of evidence approach was used. Academic and nonacademic databases were searched. Twenty-five papers were included for analysis based on the inclusion/exclusion criteria. RESULTS: Most studies were of medium to high methodological quality. Negative impacts included trauma symptoms, disrupted social relationships, behavioral changes, and emotional and psychological distress. Ability to manage negative impacts was influenced by overall organizational support, availability of training, supervision and guidance, workloads and caseload characteristics, individual characteristics, and their coping and self-care mechanisms. Positive impacts included empowering feelings, improved relationships, compassion satisfaction, and posttraumatic growth. CONCLUSIONS: Impacts are significant. Support at work and in personal life increases staff's ability to cope and find meaning in their role. Implications for research and practice are discussed.

Use of Immune Checkpoint Inhibitors in Elderly Patients With Chronic Kidney Disease and Renal Cell Carcinoma Metastasis of the Parotid Gland: Case Report and Review of the Literature.

Renal cell carcinoma metastasis of the parotid gland is extremely rare, and the present literature review found only 23 cases reported in the last two decades. We present a case of a 75-year-old woman with a colon cancer history who had parotid gland metastasis as the first manifestation of second primary kidney cancer. The presence of multiple comorbidities affected medical decision-making. Therefore the patient was treated primarily with immunotherapy. After four cycles of dual immune checkpoint blockade, this advanced patient still benefited and was changed to nivolumab monotherapy as maintenance therapy.

Ex vivo γH2AX assay for tumor radiosensitivity in primary prostate cancer patients and correlation with clinical parameters.

BACKROUND: Accurate surrogate parameters for radio resistance are warranted for individualized radiotherapy (RT) concepts in prostate cancer (PCa). The purpose of this study was to assess intertumoral heterogeneity in terms of radio resistance using an ex-vivo γH2AX assay after irradiation of prostate biopsy cores and to investigate its correlation with clinical features of respective patients as well as imaging and genomic features of tumor areas. METHODS: Twenty one patients with histologically-proven PCa and pre-therapeutic multiparametric resonance imaging and prostate-specific membrane antigen positron emission tomography were included in the study. Biopsy cores were collected from 26 PCa foci. Residual γH2AX foci were counted 24 h after ex-vivo irradiation (with 0 and 4 Gy) of biopsy specimen and served as a surrogate for radio resistance. Clinical, genomic (next generation sequencing) and imaging features were collected and their association with the radio resistance was studied. RESULTS: In total 18 PCa lesions from 16 patients were included in the final analysis. The median γH2AX foci value per PCa lesion was 3.12. According to this, the patients were divided into two groups (radio sensitive vs. radio resistant) with significant differences in foci number (p < 0.0001). The patients in the radio sensitive group had significantly higher prostate specific antigen serum concentration (p = 0.015), tumor areas in the radio sensitive group had higher SUV (standardized uptake values in PSMA PET)-max and -mean values (p = 0.0037, p = 0.028) and lower ADC (apparent diffusion coefficient-mean values, p = 0.049). All later parameters had significant (p < 0.05) correlations in Pearson's test. One patient in the radio sensitive group displayed a previously not reported loss of function frameshift mutation in the NBN gene (c.654_658delAAAAC) that introduces a premature termination codon and results in a truncated protein. CONCLUSION: In this pilot study, significant differences in intertumoral radio resistance were observed and clinical as well as imaging parameters may be applied for their prediction. After further prospective validation in larger patient cohorts these finding may lead to individual RT dose prescription for PCa patients in the future.

Interactions of Curcumin's Degradation Products with the Aß42 Dimer: A Computational Study.

Amyloid-ß (Aß) dimers are the smallest toxic species along the amyloid-aggregation pathway and among the most populated oligomeric accumulations present in the brain affected by Alzheimer's disease (AD). A proposed therapeutic strategy to avoid the aggregation of Aß into higher-order structures is to develop molecules that inhibit the early stages of aggregation, i.e., dimerization. Under physiological conditions, the Aß dimer is highly dynamic and does not attain a single well-defined structure but is rather characterized by an ensemble of conformations. In a recent study, a highly heterogeneous library of conformers of the Aß dimer was generated by an efficient sampling method with constraints based on ion mobility mass spectrometry data. Here, we make use of the Aß dimer library to study the interaction with two curcumin degradation products, ferulic aldehyde and vanillin, by molecular dynamics (MD) simulations. Ensemble docking and MD simulations are used to provide atomistic detail of the interactions between the curcumin degradation products and the Aß dimer. The simulations show that the aromatic residues of Aß, and in particular 19FF20, interact with ferulic aldehyde and vanillin through π-π stacking. The binding of these small molecules induces significant changes on the 16KLVFF20 region.

Intraindividual Comparison Between [18F] PSMA-1007 PET/CT and Multiparametric MRI for Radiotherapy Planning in Primary Prostate Cancer Patients.

Introduction: Accurate detection and segmentation of the intraprostatic gross tumor volume (GTV) is pivotal for radiotherapy (RT) in primary prostate cancer (PCa) since it influences focal therapy target volumes and the patients' cT stage. The study aimed to compare the performance of multiparametric resonance imaging (mpMRI) with [18F] PSMA-1007 positron emission tomography (PET) for intraprostatic GTV detection as well as delineation and to evaluate their respective influence on RT concepts. Materials and Methods: In total, 93 patients from two German University Hospitals with [18F] PSMA-1007-PET/CT and MRI (Freiburg) or [18F] PSMA-1007-PET/MRI (Dresden) were retrospectively enrolled. Validated contouring techniques were applied for GTV-PET and -MRI segmentation. Absolute tumor volume and cT status were determined for each imaging method. The PCa distribution from histopathological reports based on biopsy cores and surgery specimen was used as reference in terms of laterality (unilateral vs. bilateral). Results: In the Freiburg cohort (n = 84), mpMRI and PET detected in median 2 (range: 1-5) and 3 (range: 1-8) GTVs, respectively (p < 0.01). The median GTV-MRI was significantly smaller than the GTV-PET, measuring 2.05 vs. 3.65 ml (p = 0.0005). PET had a statistically significant higher concordance in laterality with surgery specimen compared to mpMRI (p = 0.04) and biopsy (p < 0.01), respectively. PSMA PET led to more cT2c and cT3b stages, whereas cT3a stage was more pronounced in mpMRI. Based on the cT stage derived from mpMRI and PET information, 21 and 23 as well as 59 and 60 patients, respectively, were intermediate- and high-risk according to the National Comprehensive Cancer Network (NCCN) v1.2022 criteria. In the Dresden cohort (n = 9), similar results were observed. Conclusion: Intraprostatic GTV segmentation based on [18F] PSMA-1007 PET results in more and larger GTVs compared to mpMRI. This influences focal RT target volumes and cT stage definition, but not the NCCN risk group.

Antibody binding increases the flexibility of the prion protein.

Prion diseases are associated with the conversion of the cellular prion protein (PrP) into a pathogenic conformer (PrPSc). A proposed therapeutic approach to avoid the pathogenic transformation is to develop antibodies that bind to PrP and stabilize its structure. POM1 and POM6 are two monoclonal antibodies that bind the globular domain of PrP and have different biological responses, i.e., trigger neurotoxicity mimicking prion infections (POM1) or prevent neurotoxicity (POM6). The crystal structures of PrP in complex with the two antibodies show similar epitopes which seems inconsistent with the opposite phenotypes. Here, we investigate the influence of the POM1 and POM6 antibodies on the flexibility of the mouse PrP by molecular dynamics simulations. The simulations reveal that the POM6/PrP interface is less stable than the POM1/PrP interface, ascribable to localized polar mismatches at the interface, despite the former complex having a larger epitope than the latter. In the presence of any of the two antibodies, the flexibility of the globular domain increases everywhere except for the ß1-α1 loop in the POM1/PrP complex which suggests the involvement of this loop in the pathological conversion. The secondary structure of PrP is preserved whereas the polar interactions involving residues Glu146, Arg156 and Arg208 are modified upon antibody binding.

Development and application of criteria for classification of hydrolysed proteins in the framework of feed safety.

In the view of a circular economy, there is an increasing need for (re-)using animal by-products that have a wide range of applications and sufficient safety. Hydrolysates of animal proteins (HPs) are frequently used as feed ingredients. Nevertheless, clear criteria for legal use and methods for monitoring feed applications are not available. Here, a range of methods have been used and evaluated for characterizing a set of 26 samples of hydrolysed proteins, 'hydrolysed' feather meals and processed animal proteins (PAPs), with verification based on an additional set of eight samples. Methods included determination of ash content, sediment (mineral fraction) content, protein content, species identity, solubility, protein solubility, size exclusion chromatography and polyacrylamide gel electrophoresis (SDS-PAGE). After a comparison of results obtained with water and SDS, water was chosen as the solvent for environmental and occupational reasons. Typical HP samples have a protein content higher than 60%, a solubility exceeding 50% and a virtual absence of a mineral fraction. The first discrimination between HPs and PAPs could be based on the absence or presence, respectively, of a mineral fraction. An approach for HP characterization is designed using a Hydrolysation Index (HI) based on the fraction of peptides smaller than 10 kDa, the solubility of the sample and the fraction of soluble proteins. A simplified version (HIs), exclusively based on the fraction of peptides smaller than 10 kDa and the solubility of the sample, shows a trend among the samples highly comparable to HI. Values for HI and HIs exceeding 60% would characterise HPs. Feather meals, which are heat treated instead of treatment by a chemical process of hydrolysation, range among the PAPs and should not be indicated as "hydrolysed." The HIs can be used as an easy parameter for classifying HPs and for legal enforcement.