Structural Elucidation of Ubiquitin via Gas-Phase Ion/Ion Cross-Linking Reactions Using Sodium-Cationized Reagents Coupled with Infrared Multiphoton Dissociation.

Accurate structural determination of proteins is critical to understanding their biological functions and the impact of structural disruption on disease progression. Gas-phase cross-linking mass spectrometry (XL-MS) via ion/ion reactions between multiply charged protein cations and singly charged cross-linker anions has previously been developed to obtain low-resolution structural information on proteins. This method significantly shortens experimental time relative to conventional solution-phase XL-MS but has several technical limitations: (1) the singly deprotonated N-hydroxysulfosuccinimide (sulfo-NHS)-based cross-linker anions are restricted to attachment at neutral amine groups of basic amino acid residues and (2) analyzing terminal cross-linked fragment ions is insufficient to unambiguously localize sites of linker attachment. Herein, we demonstrate enhanced structural information for alcohol-denatured A-state ubiquitin obtained from an alternative gas-phase XL-MS approach. Briefly, singly sodiated ethylene glycol bis(sulfosuccinimidyl succinate) (sulfo-EGS) cross-linker anions enable covalent cross-linking at both ammonium and amine groups. Additionally, covalently modified internal fragment ions, along with terminal b-/y-type counterparts, improve the determination of linker attachment sites. Molecular dynamics simulations validate experimentally obtained gas-phase conformations of denatured ubiquitin. This method has identified four cross-linking sites across 8+ ubiquitin, including two new sites in the N-terminal region of the protein that were originally inaccessible in prior gas-phase XL approaches. The two N-terminal cross-linking sites suggest that the N-terminal half of ubiquitin is more compact in gas-phase conformations. By comparison, the two C-terminal linker sites indicate the signature transformation of this region of the protein from a native to a denatured conformation. Overall, the results suggest that the solution-phase secondary structures of the A-state ubiquitin are conserved in the gas phase. This method also provides sufficient sensitivity to differentiate between two gas-phase conformers of the same charge state with subtle structural variations.

Etiological diagnosis of recurrent acute pancreatitis.

Acute pancreatitis is the leading cause of inpatient care among gastrointestinal conditions. Despite early intervention, one-third of patients experience recurrent acute pancreatitis (RAP). A comprehensive diagnostic approach is warranted to identify and treat underlying factors in order to prevent recurrence. RAP is most frequent among men aged 30-40, smokers, and in those with excessive alcohol consumption. To identify the etiology is paramount to stratify patients according to their individual risk of RAP and for predicting an eventual evolution to chronic pancreatitis. Although the initial management of acute pancreatitis is widely homogeneous according to established guidelines, there are no defined protocols to investigate RAP. In the present editorial article we propose a structured algorithm with precise recommendations to investigate the etiology RAP as part of routine clinical practice. Although there are relevant knowledge gaps in this disease, we believe that our guidance would contribute for a more homogenous diagnostic approach of RAP in clinical practice.

A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners but often include false positives. Furthermore, they provide no information about what the binding region is (e.g., the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competitive Binding Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment and the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies of AF and AF-CBA to help users identify scenarios where the approach will be most useful. Given the method's speed and accuracy, we anticipate its broad applicability to identify binding epitope regions among potential partners, setting the stage for experimental verification.

Revolutionizing Peptide-Based Drug Discovery: Advances in the Post-AlphaFold Era.

Peptide-based drugs offer high specificity, potency, and selectivity. However, their inherent flexibility and differences in conformational preferences between their free and bound states create unique challenges that have hindered progress in effective drug discovery pipelines. The emergence of AlphaFold (AF) and Artificial Intelligence (AI) presents new opportunities for enhancing peptide-based drug discovery. We explore recent advancements that facilitate a successful peptide drug discovery pipeline, considering peptides' attractive therapeutic properties and strategies to enhance their stability and bioavailability. AF enables efficient and accurate prediction of peptide-protein structures, addressing a critical requirement in computational drug discovery pipelines. In the post-AF era, we are witnessing rapid progress with the potential to revolutionize peptide-based drug discovery such as the ability to rank peptide binders or classify them as binders/non-binders and the ability to design novel peptide sequences. However, AI-based methods are struggling due to the lack of well-curated datasets, for example to accommodate modified amino acids or unconventional cyclization. Thus, physics-based methods, such as docking or molecular dynamics simulations, continue to hold a complementary role in peptide drug discovery pipelines. Moreover, MD-based tools offer valuable insights into binding mechanisms, as well as the thermodynamic and kinetic properties of complexes. As we navigate this evolving landscape, a synergistic integration of AI and physics-based methods holds the promise of reshaping the landscape of peptide-based drug discovery.

Loop diuretic down-titration at discharge in patients hospitalized for acute heart failure.

AIMS: The current literature provides limited guidance on the best diuretic strategy post-hospitalization for acute heart failure (AHF). It is postulated that the efficacy and safety of the outpatient diuretic regimen may be significantly influenced by the degree of fluid overload (FO) encountered during hospitalization. We hypothesize that in patients with more pronounced FO, reducing their regular oral diuretic dosage might be associated with an elevated risk of unfavourable clinical outcomes. METHODS AND RESULTS: It was a retrospective observational study of 410 patients hospitalized for AHF in which the dose of furosemide at admission and discharge was collected. Patients were categorized across diuretic dose status into two groups: (i) the down-titration group and (ii) the stable/up-titration group. FO status was evaluated by a clinical congestion score and circulating biomarkers. The endpoint of interest was the composite of time to all-cause death and/or heart failure readmission. A multivariable Cox proportional hazard regression model was constructed to analyse the endpoints. The median age was 86 (78-92) years, 256 (62%) were women, and 80% had heart failure with preserved ejection fraction. After multivariate adjustment, the down-titration furosemide equivalent dose remained not associated with the risk of the combined endpoint in the whole sample (hazard ratio 1.34, 95% confidence interval 0.86-2.06, P = 0.184). The risk of the combination of death and/or worsening heart failure associated with the diuretic strategy at discharge was significantly influenced by FO status, including clinical congestion scores and circulating proxies of FO like BNP and cancer antigen 125. CONCLUSIONS: In patients hospitalized for AHF, furosemide down-titration does not imply an increased risk of mortality and/or heart failure readmission. However, FO status modifies the effect of down-titration on the outcome. In patients with severe congestion or residual congestion at discharge, down-titration was associated with an increased risk of mortality and/or heart failure readmission.

An overload of missense variants in the OTOG gene may drive a higher prevalence of familial Meniere disease in the European population.

Meniere disease is a complex inner ear disorder with significant familial aggregation. A differential prevalence of familial MD (FMD) has been reported, being 9-10% in Europeans compared to 6% in East Asians. A broad genetic heterogeneity in FMD has been described, OTOG being the most common mutated gene, with a compound heterozygous recessive inheritance. We hypothesize that an OTOG-related founder effect may explain the higher prevalence of FMD in the European population. Therefore, the present study aimed to compare the allele frequency (AF) and distribution of OTOG rare variants across different populations. For this purpose, the coding regions with high constraint (low density of rare variants) were retrieved in the OTOG coding sequence in Non-Finnish European (NFE).. Missense variants (AF < 0.01) were selected from a 100 FMD patient cohort, and their population AF was annotated using gnomAD v2.1. A linkage analysis was performed, and odds ratios were calculated to compare AF between NFE and other populations. Thirteen rare missense variants were observed in 13 FMD patients, with 2 variants (rs61978648 and rs61736002) shared by 5 individuals and another variant (rs117315845) shared by two individuals. The results confirm the observed enrichment of OTOG rare missense variants in FMD. Furthermore, eight variants were enriched in the NFE population, and six of them were in constrained regions. Structural modeling predicts five missense variants that could alter the otogelin stability. We conclude that several variants reported in FMD are in constraint regions, and they may have a founder effect and explain the burden of FMD in the European population.

Diversity and prevalence of zoonotic infections at the animal-human interface of primate trafficking in Peru.

Wildlife trafficking creates favorable scenarios for intra- and inter-specific interactions that can lead to parasite spread and disease emergence. Among the fauna affected by this activity, primates are relevant due to their potential to acquire and share zoonoses - infections caused by parasites that can spread between humans and other animals. Though it is known that most primate parasites can affect multiple hosts and that many are zoonotic, comparative studies across different contexts for animal-human interactions are scarce. We conducted a multi-parasite screening targeting the detection of zoonotic infections in wild-caught monkeys in nine Peruvian cities across three contexts: captivity (zoos and rescue centers, n = 187); pet (households, n = 69); and trade (trafficked or recently confiscated, n = 132). We detected 32 parasite taxa including mycobacteria, simian foamyvirus, bacteria, helminths, and protozoa. Monkeys in the trade context had the highest prevalence of hemoparasites (including Plasmodium malariae/brasilianum, Trypanosoma cruzi, and microfilaria) and enteric helminths and protozoa were less common in pet monkeys. However, parasite communities showed overall low variation between the three contexts. Parasite richness (PR) was best explained by host genus and the city where the animal was sampled. Squirrel (genus Saimiri) and wooly (genus Lagothrix) monkeys had the highest PR, which was ~2.2 times the PR found in tufted capuchins (genus Sapajus) and tamarins (genus Saguinus/Leontocebus) in a multivariable model adjusted for context, sex, and age. Our findings illustrate that the threats of wildlife trafficking to One Health encompass exposure to multiple zoonotic parasites well-known to cause disease in humans, monkeys, and other species. We demonstrate these threats continue beyond the markets where wildlife is initially sold; monkeys trafficked for the pet market remain a reservoir for and contribute to the translocation of zoonotic parasites to households and other captive facilities where contact with humans is frequent. Our results have practical applications for the healthcare of rescued monkeys and call for urgent action against wildlife trafficking and ownership of monkeys as pets.

Fully automated CT imaging biomarkers for opportunistic prediction of future hip fractures.

OBJECTIVE: Assess automated CT imaging biomarkers in patients who went on to hip fracture, compared with controls. METHODS: In this retrospective case-control study, 6926 total patients underwent initial abdominal CT over a 20-year interval at one institution. A total of 1308 patients (mean age at initial CT, 70.5 ± 12.0 years; 64.4% female) went on to hip fracture (mean time to fracture, 5.2 years); 5618 were controls (mean age 70.3 ± 12.0 years; 61.2% female; mean follow-up interval 7.6 years). Validated fully automated quantitative CT algorithms for trabecular bone attenuation (at L1), skeletal muscle attenuation (at L3), and subcutaneous adipose tissue area (SAT) (at L3) were applied to all scans. Hazard ratios (HRs) comparing highest to lowest risk quartiles and receiver operating characteristic (ROC) curve analysis including area under the curve (AUC) were derived. RESULTS: Hip fracture HRs (95% CI) were 3.18 (2.69-3.76) for low trabecular bone HU, 1.50 (1.28-1.75) for low muscle HU, and 2.18 (1.86-2.56) for low SAT. 10-year ROC AUC values for predicting hip fracture were 0.702, 0.603, and 0.603 for these CT-based biomarkers, respectively. Multivariate combinations of these biomarkers further improved predictive value; the 10-year ROC AUC combining bone/muscle/SAT was 0.733, while combining muscle/SAT was 0.686. CONCLUSION: Opportunistic use of automated CT bone, muscle, and fat measures can identify patients at higher risk for future hip fracture, regardless of the indication for CT imaging. ADVANCES IN KNOWLEDGE: CT data can be leveraged opportunistically for further patient evaluation, with early intervention as needed. These novel AI tools analyse CT data to determine a patient's future hip fracture risk.

Advancing Molecular Dynamics: Toward Standardization, Integration, and Data Accessibility in Structural Biology.

Molecular dynamics (MD) simulations have become a valuable tool in structural biology, offering insights into complex biological systems that are difficult to obtain through experimental techniques alone. The lack of available data sets and structures in most published computational work has limited other researchers' use of these models. In recent years, the emergence of online sharing platforms and MD database initiatives favor the deposition of ensembles and structures to accompany publications, favoring reuse of the data sets. However, the lack of uniform metadata collection, formats, and what data are deposited limits the impact and its use by different communities that are not necessarily experts in MD. This Perspective highlights the need for standardization and better resource sharing for processing and interpreting MD simulation results, akin to efforts in other areas of structural biology. As the field moves forward, we will see an increase in popularity and benefits of MD-based integrative approaches combining experimental data and simulations through probabilistic reasoning, but these too are limited by uniformity in experimental data availability and choices on how the data are modeled that are not trivial to decipher from papers. Other fields have addressed similar challenges comprehensively by establishing task forces with different degrees of success. The large scope and number of communities to represent the breadth of types of MD simulations complicates a parallel approach that would fit all. Thus, each group typically decides what data and which format to upload on servers like Zenodo. Uploading data with FAIR (findable, accessible, interoperable, reusable) principles in mind including optimal metadata collection will make the data more accessible and actionable by the community. Such a wealth of simulation data will foster method development and infrastructure advancements, thus propelling the field forward.

Sifting Through the Noise: A Computational Pipeline for Accurate Prioritization of Protein-Protein Binding Candidates in High-Throughput Protein Libraries.

Identifying the interactome for a protein of interest is challenging due to the large number of possible binders. High-throughput experimental approaches narrow down possible binding partners, but often include false positives. Furthermore, they provide no information about what the binding region is (e.g. the binding epitope). We introduce a novel computational pipeline based on an AlphaFold2 (AF) Competition Assay (AF-CBA) to identify proteins that bind a target of interest from a pull-down experiment, along with the binding epitope. Our focus is on proteins that bind the Extraterminal (ET) domain of Bromo and Extraterminal domain (BET) proteins, but we also introduce nine additional systems to show transferability to other peptide-protein systems. We describe a series of limitations to the methodology based on intrinsic deficiencies to AF and AF-CBA, to help users identify scenarios where the approach will be most useful. Given the speed and accuracy of the methodology, we expect it to be generally applicable to facilitate target selection for experimental verification starting from high-throughput protein libraries.

Molecular Modeling of Self-Assembling Peptides.

Peptide epitopes mediate as many as 40% of protein-protein interactions and fulfill signaling, inhibition, and activation roles within the cell. Beyond protein recognition, some peptides can self- or coassemble into stable hydrogels, making them a readily available source of biomaterials. While these 3D assemblies are routinely characterized at the fiber level, there are missing atomistic details about the assembly scaffold. Such atomistic detail can be useful in the rational design of more stable scaffold structures and with improved accessibility to functional motifs. Computational approaches can in principle reduce the experimental cost of such an endeavor by predicting the assembly scaffold and identifying novel sequences that adopt said structure. Yet, inaccuracies in physical models and inefficient sampling have limited atomistic studies to short (two or three amino acid) peptides. Given recent developments in machine learning and advances in sampling strategies, we revisit the suitability of physical models for this task. We use the MELD (Modeling Employing Limited Data) approach to drive self-assembly in combination with generic data in cases where conventional MD is unsuccessful. Finally, despite recent developments in machine learning algorithms for protein structure and sequence predictions, we find the algorithms are not yet suited for studying the assembly of short peptides.

Bilateral Digitally Aided Tooth Autotransplantation: A 2-Year Case Report.

Tooth autotransplantation is an effective treatment to replace missing teeth. Digital planning can facilitate successful autotransplantation. Guiding templates are highly recommended when performing cases in healed ridges in the posterior area to reduce excessive bone loss and increase the chances of fitting the donor tooth in the new socket. This case report highlights the use of 3D planning tools and fully guided drilling templates for successful tooth autotransplantation in the posterior area. Two tooth autotransplantations were performed in a 51-year-old patient using mandibular third molars to replace hopeless mandibular first and second molars. Root canal treatments were carried out before the surgeries, and different alveoloplasty techniques were used in each recipient area. The prosthetic phase was carried out after 9 months. Both teeth were asymptomatic, functional, and exhibited no signs of resorption or apical radiolucency and showed complete regeneration of the periodontal apparatus at the 2-year follow-up.

Elementos clínicos para el diagnóstico de apendicitis aguda en la atención primaria de salud

La apendicitis aguda se manifiesta, en ocasiones, con una variada e inespecífica presentación clínica, lo que dificulta su diagnóstico oportuno y favorece el riesgo de complicaciones. El objetivo es actualizar la información relacionada con las características clínicas de la apendicitis aguda, para lo que se realizó una revisión no sistemática de la literatura hasta abril del año 2022. Se revisaron artículos, libros especializados y citas bibliográficas de estudios elegidos, 20 de los cuales fueron seleccionados para la revisión. Mediante esta investigación se concluye que la primera y principal manifestación clínica es el dolor abdominal. El paciente debe someterse a una cuidadosa exploración física, incluyendo un examen rectal si lo precisa, y en las mujeres a un examen ginecológico si existiera duda diagnóstica.

Acute appendicitis is manifested, sometimes, with a varied and unspecific clinical presentation, which makes difficult its timely diagnosis and favors the complication risk. The objective is to update the information related to the clinical characteristics of acute appendicitis, for which a non-systematic review of the literature was carried out until April 2022. Articles, specialized books and bibliographic citations of selected studies were reviewed, 20 of which were chosen for the review. Through this research it is concluded that the first and main manifestation is abdominal pain. The patient should undergo a rigorous physical examination, including a rectal examination if necessary, and in the case of women, a gynecological examination if there is diagnostic doubt.

Mes de la Ciencia: estrategia para el conocimiento y la investigación

El Mes de la Ciencia surge como idea para socializar y divulgar las investigaciones y el nivel de actualización sobre los principales problemas de salud que afectan a la población matancera. Expone el nivel científico de las diferentes especialidades que ofrecen servicio en las instituciones de salud; permite la interdisciplinariedad entre ellas; motiva a los estudiantes del pregrado y resulta una fuente de gestión del conocimiento para el educando del posgrado; ofrece soluciones para los desafíos de la vida cotidiana y el manejo de las principales entidades que son atendidas en las instituciones, y permite el crecimiento profesional y el intercambio entre profesionales del país y del extranjero. Los autores se proponen mostrar los primeros resultados que ha tenido el Mes de la Ciencia a partir de su implementación. Estos están relacionados con el número considerable de conferencias magistrales y talleres impartidos, del incremento de participantes por mes y del nivel de satisfacción por eventos recogido por los principales actores. Aún más, se ha transformado de evento interhospitalario a uno con carácter provincial, con participación nacional e internacional y con alta aceptación por la comunidad científica, lo que le ha merecido el reconocimiento de los directivos provinciales y del ministro de Salud Pública.

Science month arises as an idea to socialize and disseminate research and the level of updating on the main health problems affecting the population of Matanzas. It exposes the scientific level of the different specialties that offer services in health institutions; it enables interdisciplinarity between them; motivates undergraduate students and is a source of knowledge management for postgraduate students; it offers solutions for the challenges of daily life and the management of the main entities that are served in the institutions, and allows the professional growth and interchange between professional in the country and abroad. The authors intend to show the first results the Science Month has had since its implementation. These are related to the considerable number of keynote conferences and workshops given, the increase in participants per month and the level of satisfaction per events collected by the main actors. Even more, it has been transformed from an inter-hospital event to one of a provincial character, with national and international participation, and with high acceptance by the scientific community, which has earned it the recognition of the provincial management staff and the minister of Public Health.

Comparing fully automated AI body composition measures derived from thin and thick slice CT image data.

PURPOSE: To compare fully automated artificial intelligence body composition measures derived from thin (1.25 mm) and thick (5 mm) slice abdominal CT data. METHODS: In this retrospective study, fully automated CT-based body composition algorithms for quantifying bone attenuation, muscle attenuation, muscle area, liver attenuation, liver volume, spleen volume, visceral-to-subcutaneous fat ratio (VSR) and aortic calcium were applied to both thin (1.25 × 0.625 mm) and thick (5 × 3 mm) abdominal CT series from two patient cohorts: unenhanced scans in asymptomatic adults undergoing colorectal cancer screening, and post-contrast scans in patients with colorectal cancer. Body composition measures derived from thin and thick slice data were compared, including correlation coefficients and Bland-Altman analysis. RESULTS: A total of 9882 CT scans (mean age, 57.0 years; 4527 women, 5355 men) were evaluated, including 8947 non-contrast and 935 contrast-enhanced CT exams. Very strong positive correlation was observed for all soft tissue measures: muscle attenuation (r2 = 0.97), muscle area (r2 = 0.98), liver attenuation (r2 = 0.99), liver volume (r2 = 0.98) and spleen volume (r2 = 0.99), VSR (r2 = 0.98), and aortic calcium (r2 = 0.92); (p < 0.001 for all). Moderate positive correlation was observed for bone attenuation (r2 = 0.35). Bland-Altman analysis showed strong agreement for muscle attenuation, muscle area, liver attenuation, liver volume and spleen volume. Mean percentage differences amongst body composition measures were less than 5% for VSR (4.6%), muscle area (- 0.5%), liver attenuation (0.4%) and liver volume (2.7%) and less than 10% for muscle attenuation (- 5.5%) and spleen volume (5.1%). For aortic calcium, thick slice overestimated for Agatston scores between 0 and 100 and > 400 burden in 3.1% and 0.3% relative to thin slice, respectively, but underestimated scores between 100 and 400. CONCLUSION: Automated body composition measures derived from thin and thick abdominal CT data are strongly correlated and show agreement, particularly for soft tissue applications, making it feasible to use either series for these CT-based body composition algorithms.

Association of Polymorphisms of the IL-17A and IL-17F Genes with Increased Risk of Hypertension and Obesity in Mexican Patients with COVID-19.

Coronavirus disease 2019 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2). COVID-19 can cause a cytokine release syndrome in which cytokines, including interleukin 17 (IL-17), are massively secreted in response to a specific stimulus. This can contribute to mortality and severe forms of COVID-19. The study aimed to determine the association of SARS-CoV2 infection with the IL-17A rs2275913 and IL-17F rs763780 variants, as well as with the associated comorbidities in COVID-19-positive Mexican patients. The study included 178 patients positive to COVID-19 and 177 COVID-19 negative subjects. For genotyping, the samples were amplified with a TaqMan® probe. There was no association between the AA genotype and A allele of IL-17A variant or the IL-17F C allele with the presence of COVID-19. In regard to comorbidities, a statistically significant association was found between IL-17A rs2275913 AA genotype and hypertension, as well as with the presence of obesity (P = 0.003, OR 23, 95% CI: 2.97-178.092 and P = 0.025, OR 28, 95% CI: 1.52-178.029, respectively) in patients with COVID-19. In conclusion, rs2275913 IL-17A polymorphism in COVID-19 patients seems to confer a higher susceptibility to the presence of hypertension and obesity, increasing the risk of premature cardiovascular disease in this population. However, more studies should be conducted for a better understanding of their relation.

Plasmodium vivax apical membrane antigen 1I-II from Nicaragua (2012-2013): genetic and antigenic polymorphism.

OBJECTIVE: Genetic and antigenic polymorphism of P. vivax apical membrane antigen-1 (pvama1I-II) from Nicaragua was examined. MATERIALS AND METHODS: Infected blood samples from patients were obtained during 2012-2013. A gene fragment comprising domains I-II was amplified and sequenced, and the genetic parameters, haplotype relationships, genetic structure, and amino acid variation in predicted B cell epitopes were analyzed. RESULTS: 65 sequences of pvama1III had 19 nonsynonymous and five synonymous nucleotide changes. Nicaraguan parasites had low diversity, high linkage disequilibrium, and few recombination events. Neutrality tests indicate a positive and divergent selection, and three genetic clusters with loss of haplotypes were demonstrated. Amino acid variation predominated in predicted B cell epitopes and was closely related to that in Latin American parasites. CONCLUSIONS: Nicaraguan P. vivax is a moderately differentiated population under contraction and focalization processes, and the antigenic diversity resembles that of Latin American parasites. This information is relevant for vaccine development and epidemiological surveillance.

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.

When MELD Meets GaMD: Accelerating Biomolecular Landscape Exploration.

We introduce Gaussian accelerated MELD (GaMELD) as a new method for exploring the energy landscape of biomolecules. GaMELD combines the strengths of Gaussian accelerated molecular dynamics (GaMD) and modeling employing limited data (MELD) to navigate complex energy landscapes. MELD uses replica-exchange molecular simulations to integrate limited and uncertain data into simulations via Bayesian inference. MELD has been successfully applied to problems of structure prediction like protein folding and complex structure prediction. However, the computational cost for MELD simulations has limited its broader applicability. The synergy of GaMD and MELD surmounts this limitation efficiently sampling the energy landscape at a lower computational cost (reducing the computational cost by a factor of 2 to six). Effectively, GaMD is used to shift energy distributions along replicas to increase the overlap in energy distributions across replicas, facilitating a random walk in replica space. We tested GaMELD on a benchmark set of 12 small proteins that have been previously studied through MELD and conventional MD. GaMELD consistently achieves accurate predictions with fewer replicas. By increasing the efficacy of replica exchange, GaMELD effectively accelerates convergence in the conformational space, enabling improved sampling across a diverse set of systems.