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Machine Learning for the Prediction of Size and Encapsulation Efficiency of mRNA-Loaded Lipid Nanoparticles Following a Postencapsulation Approach

Abstract

Lipid nanoparticles (LNPs) have gained significant attention thanks to their ability to encapsulate and deliver mRNA. Exploring a variety of lipid compositions and different preparation processes is essential for a better understanding of the mRNA encapsulation and the LNPs assembly. In this study, we investigated the development of mRNA-LNPs through microfluidic PFVs production followed by a postencapsulation approach. A library of preformed vesicles (PFVs) was produced by microfluidics using a full factorial design by varying 4 formulation and process parameters: main lipid type, sterol type, flow rate ratio, and chip design. The Size and polydispersity index (PDI) of PFVs were measured and compiled into a data set. A subset of formulations was subsequently postencapsulated with mRNA, after which the size, PDI, and EE% of the resulting mRNA-LNPs were quantified to generate a labeled data set. The results showed the effects of chip design and lipid composition on the size and PDI of PFVs, with smaller PFVs obtained with the chip design that provides a higher mixing efficiency. Postencapsulated formulations showed consistent increases in nanoparticle size and decreases in PDI values, compared to the corresponding PFVs. An XGBoost model was trained and validated on the labeled data set for predicting size and EE%, and was further optimized through semisupervised learning by incorporating pseudolabeled data derived from the PFVs data set. The model demonstrated an ability to predict the size and the EE% of LNPs based on the composition, the process parameters, and the physicochemical properties of PFVs. The use of microfluidics and machine learning allowed the obtaining of relevant information with limited resources and time. Integrating machine learning and advanced data analysis in nanomedicine research could unveil its full potential and accelerate the development of innovative formulation strategies.

Chemogenetic activation of oxytocinergic neurons rescues neural correlates of encephalopathy of prematurity in mice

Abstract

Every year, 15 million babies are born preterm, putting them at increased risk of encephalopathy of prematurity (EoP). EoP is characterized by microglia-induced neuroinflammation, which can aggravate injury mechanisms leading to neuronal disorders, myelination delay, and subsequent functional consequences. While effective neuroprotective strategies in the preterm brain remain elusive, interventions such as skin-to-skin, developmental care, and music therapy have a positive impact on newborn brain development, potentially related to the oxytocinergic system. Endogenous oxytocin is recognized as a regulator of maternal-child social bonding, but its neuroprotective effect in the injured brain remains to be elucidated. Here, we investigated the effects of chemogenetic activation of oxytocinergic neurons on the neural correlates of EoP. Using a well-established mouse model of systemic interleukin-1β to induce EoP, we showed that neonatal chemogenetic activation of oxytocinergic neurons has anti-inflammatory effects in microglia, improving microstructural development of the corpus callosum and motor cortex, and rescuing typical social behavior. These neuroprotective effects were more pronounced in females, who showed a greater reduction in microgliosis and improved social behavior compared to males. This study provides a biological explanation for how developmental care and early interventions, linked to the oxytocinergic system, may induce neuroprotection in the developing brain.

Cot-side functional imaging in neonates for early neurodevelopment monitoring using functional ultrasound (fUS) connectivity imaging and the combination of fUS with diffuse optical tomography (fUS-DOT): A feasibility study

Abstract

The newborn infant, particularly those born preterm, is vulnerable to brain injury resulting in lifelong neurodevelopmental sequalae. Conventional structural brain imaging correlates poorly with later individual neurodevelopmental trajectories. Therefore, assessing brain integrity with functional (particularly functional connectivity (FC)) neuroimaging, would be beneficial, as studies showed correlation between early FC assessment and later neurodevelopmental outcomes. However, these tools are absent of neonatal clinical settings, probably either due to lack of portability or restricted access to the deep structures. In this proof of concept (poc) work, we show that functional ultrasound imaging (fUS) has key characteristics for this challenge: including portability, sensitivity and spatiotemporal resolution. fUS can monitor fine grain brain activity in deep cerebral nuclei, detect changes in FC dynamics at different developmental stages, with capabilities for 3D imaging. Furthermore, we present a multimodal poc combining fUS with high-density diffuse optical tomography (HD-DOT). The results demonstrate correlation between fUS and HD-DOT signals in spatially overlapping areas of the brain. The complementary fields of view of fUS (in depth) and HD-DOT (shallow cortex) could enable for the first time cot-side whole brain assessment of FC. In the future, a system combining fUS and HD-DOT could be developed as a clinical tool to monitor the developing brain in high-risk infants.

Biosimilarity and advanced structural characterization of monoclonal antibodies charge variants using capillary zone electrophoresis and mass spectrometry

Abstract

Monoclonal antibodies (mAbs) structural complexity arises from their macromolecular nature and their propensity to undergo post-translational modifications (PTM), potentially leading to the formation of charge variants. Capillary zone electrophoresis (CZE) showed to be particularly relevant for their analysis, however the selectivity provided by CZE separation is not completely elucidated. In this work, CZE-UV analysis was used to characterize charge variants for biosimilars products corresponding to infliximab. Results demonstrated the possibility to identify faint variations between the different products showing its applicability to contribute to mAbs biosimilarity assessment. Enzymatic treatment allowed to attribute the origin of infliximab charge variants. CZE-UV analysis of pembrolizumab showed that none of the five charge variants separated were originating from C-terminal lysine residues and/or N-glycans. To enable further identification, an analytical strategy was developed to achieve CZE-UV fraction collection and enrichment of mAb charge variants followed by systematic offline characterization in CE coupled to tandem mass spectrometry (MS/MS). CE-MS/MS experiments allowed the identification of different types of PTMs such as N-terminal pyroglutamic acid formation and asparagine deamidation for charge variant fractions correlated with decreased mobility. In addition, for the first time succinimide intermediate formation could be successfully characterized using CE-MS/MS data, which could be correlated to increased mobility. Thus, the CZE-UV separation resulted from the synergistic effect of several simultaneous PTMs affecting the apparent mobilities of the charge variants. As a consequence, experiments illustrated the relevance and potential of intact mAbs analysis using CZE-UV to provide an overview of the structural diversity of therapeutic mAbs.

Reassessing Cognitive Trends in Very Preterm Children-Reply

No abstract available

A systematic scoring system to optimise the testing of neurotherapeutics in models of perinatal brain injury, with an applied case study of human umbilical-cord MSC

Abstract

The preclinical stages of therapeutic agent development cost hundreds of millions of dollars, stymying innovation and slowing the development of products to improve human health. There is a striking unmet need for therapies that protect or repair the brain damage associated with preterm birth, i.e., delivery before 37 weeks of gestation. Of the more than 15 million babies born preterm every year, up to 60% will go on to develop a neurological disorder, with the earliest-born infants the most impacted. We have limited options with limited efficacy for preventing or treating these changes. Combining accurate knowledge of pathophysiology with high-throughput sequencing and computational biology approaches is a logical step towards an optimised screening pipeline. In this study, we conducted comprehensive testing of dose, timing, and route of administration, integrating multimodal data from preclinical models of brain injury common in preterm-born infants to validate the most effective therapeutic option for the cord-derived mesenchymal stem cell product (HuMSC). In this study, HuMSC serves as a working example, but the scoring system is therapy-agnostic. We developed a scoring protocol based on microglia transcriptome analyses and myelin protein expression to evaluate the efficacy of the HuMSC product in a rat model of inflammation-associated preterm infant brain injury. We identified the superiority of treatment delivered in the tertiary phase of injury over treatments in the acute or subacute stages, as well as the superiority of intranasal over intravenous delivery of HuMSCs. The optimal time, dose, and route of administration options for HuMSC were confirmed in a second model relevant to preterm infants, but with a different pathophysiology, namely germinal matrix haemorrhage. In conclusion, we have established a scoring protocol that expedites the collection of comprehensive dose, time and route of administration data critical for establishing large animal and clinical trials with the greatest chance of success

Commensal Clostridia in the preterm gut as reservoirs of antimicrobial resistance: susceptibility profiles, and resistance genes

Abstract

The gut microbiome of preterm infants is highly vulnerable to perturbations. Members of the class Clostridia are among the first anaerobes colonizing the preterm gut, yet their ecological roles and antimicrobial resistance (AMR) properties remain poorly understood. We characterized 98 Clostridia isolates from fecal samples of preterm infants, spanning 17 species and 11 genera. Isolates were identified by MALDI-TOF and 16S rRNA sequencing, colonization levels were quantified, and antimicrobial susceptibility was assessed by disk diffusion and E-test. Resistance determinants were screened by PCR and sequenced. We focused on Clostridia that were present at low colonization levels (mean 5.3 log10 CFU g-1 of feces). While most isolates were susceptible to amoxicillin-clavulanic acid, imipenem, and metronidazole, resistance to tetracycline (12%), clindamycin (35%), and cefotaxime (35%) was observed. Distinct species-specific resistance included linezolid (Clostridium argentinense), chloramphenicol (Clostridium innocuum), and tigecycline (Paeniclostridium sordellii), and one Robinsonella peoriensis isolate displayed vancomycin resistance. The detection of tet and erm genes corresponded with phenotypic resistance, while β-lactamase activity was uncommon. Although colonizing at low levels, these findings highlight the ecological significance of rarely studied commensal Clostridia and their contribution to the neonatal resistome, acting as underappreciated reservoirs of AMR genes during a critical window of microbiome assembly.

Predicting neonatal infection in PPROM with vaginal microbiology and metagenomics: a prospective cohort study

Abstract

Objective: Early-onset neonatal sepsis (EONS) due to ascending infection is a potentially preventable complication of preterm premature rupture of membranes (PPROM). Our objective was to determine whether the analysis of bacteria from vaginal swab samples is predictive of the risk of EONS in PPROM.

Study design: In a prospective 3-center observational cohort, patients with PPROM were enrolled between 22 and 36 weeks’ gestation (WG) + 6 days. Vaginal swab samples at delivery were analyzed using two different approaches, classical bacterial cultures and shotgun metagenomic sequencing analysis. A metagenomics score was constructed combining the characterization of the vaginal microbiome and the presence of pathogens and the optimal cut-off to predict EONS was tested on a receiver operating curve.

Results: 563 PPROM cases were enrolled, with 646 liveborn neonates. PPROM occurred < 32 WG in 41.9% and deliveries were < 34 WG in 41.0%. The incidence of EONS was 29/646 (4.5%). When considering all central and peripheral microbiological samples available for 26 neonates, the main pathogens isolated were Escherichia coli in 14 cases (53.8 %), other gram-negatives in 5 (19.2%), strict anaerobes in 3 (11.5%); there was a single case (3.8%) each with Group B Streptococcus (GBS), Streptococcus anginosus, Staphylococcus aureus and Ureaplasma urealyticum. We studied the prediction of EONS among 272 mothers and their 310 neonates (20 EONS, 6.4%) with both culture and metagenomic data available. A culture positive for a major or intermediate pathogen in the vaginal sample at delivery had a sensitivity of 80.0 % (95% CI=56.3-94.3) and a specificity of 37.9% (95% CI=32.3-43.8), adjusted odds ratio (aOR) of 1.6 (95 % CI [0.5-5.0]) to predict EONS. The presence of E. coli was associated with an EONS risk of 10.6% vs 4.9%, in the absence of E. coli (p=0.07). The metagenomics score was highly associated with EONS, with an area under the receiver operating curve of 0.75 (95% CI, 0.61-0.90). At the optimal cutoff value, sensitivity was 70% (95% CI, 64-95%), specificity was 85% (95% CI, 81-89%). A metagenomics score greater than 40 was associated with a significantly increased risk of EONS with an aOR of 8.9 (95 % CI [3.5; 22.3]) in multivariate analysis adjusted for latency period and gestational age, p<0.001.

Conclusion: In PPROM, conventional microbial culture of maternal vaginal samples was associated with EONS, but its predictive values remain insufficient to guide perinatal care. Metagenomic microbial signatures improved predictive values. This opens the perspective for a rapid point-of-care test.

Correction: Stimulating the motor development of very premature infants: effects of early crawling training on a mini-skateboard

Abstract

[This corrects the article DOI: 10.3389/fped.2023.1198016.]

Post-encapsulation methods for the preparation of mRNA-LNPs

Abstract

Microfluidics mixing is the current lab-scale method used for producing mRNA-loaded lipid nanoparticles (mRNA-LNPs) thanks to reproducibility and robustness of microfluidic mixing. Despite these advantages, the production of small LNP volumes is associated with significant material waste. Given the high cost of synthetic mRNA, this waste can be a major limitation, particularly for early-stage screening of formulations. This study proposes alternative methods for mRNA-LNP formulation aiming to improve their stability for both formulation and mRNA screening, while reducing material waste on a research scale. Specifically, we investigated post-encapsulation of mRNA into pre-formed vesicles (PFVs) obtained by microfluidic mixing. These PFVs were complexed with mRNA by: (1) a microfluidic or (2) a manual pipetting method. The resulting mRNA-LNPs produced using these two post-encapsulation methods exhibit similar physicochemical properties and morphologies to those obtained by conventional microfluidic protocol. These mRNA-LNPs were assessed on in vitro and in vivo expression. mRNA-LNPs prepared by our alternative methods showed a similar transfection level compared to the conventional formulation taken as a control. The suitability of post-encapsulation methods to other lipids, mRNAs and microfluidic systems was also confirmed. This work offers robust, simple and economic alternative methods for preparing small volumes of mRNA-LNPs. The versatility of post-encapsulation methods allows to screen mRNA formulations in a wide range of laboratories. These methods could be applied to encapsulate tailored doses of mRNA and various mRNA constructs to achieve an optimal and personalized therapy.