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T cell engagers (TCEs) are becoming an integral class of biological therapeutic owing to their highly potent ability to eradicate cancer cells. Nevertheless, the widespread utility of classical CD3-targeted TCEs has been limited by narrow therapeutic index (TI) linked to systemic CD4+ T cell activation and aberrant cytokine release. One attractive approach to circumvent the systemic activation of pan CD3+ T cells and reduce the risk of cytokine release syndrome is to redirect specific subsets of T cells. A promising strategy is the use of peptide-major histocompatibility class I bispecific antibodies (pMHC-IgGs), which have emerged as an intriguing modality of TCE, based on their ability to selectively redirect highly reactive viral-specific effector memory cytotoxic CD8+ T cells to eliminate cancer cells. However, the relatively low frequency of these effector memory cells in human peripheral blood mononuclear cells (PBMCs) may hamper their redirection as effector cells for clinical applications. To mitigate this potential limitation, we report here the generation of a pMHC-IgG derivative known as guided-pMHC-staging (GPS) carrying a covalent fusion of a monovalent interleukin-2 (IL-2) mutein (H16A, F42A). Using an anti-epidermal growth factor receptor (EGFR) arm as a proof-of-concept, tumor-associated antigen paired with a single-chain HLA-A *02:01/CMVpp65 pMHC fusion moiety, we demonstrate in vitro that the IL-2-armored GPS modality robustly expands CMVpp65-specific CD8+ effector memory T cells and induces potent cytotoxic activity against target cancer cells. Similar to GPS, IL-2-armored GPS molecules induce modulated T cell activation and reduced cytokine release profile compared to an analogous CD3-targeted TCE. In vivo we show that IL-2-armored GPS, but not the corresponding GPS, effectively expands grafted CMVpp65 CD8+ T cells from unstimulated human PBMCs in an NSG mouse model. Lastly, we demonstrate that the IL-2-armored GPS modality exhibits a favorable developability profile and monoclonal antibody-like pharmacokinetic properties in human neonatal Fc receptor transgenic mice. Overall, IL-2-armored GPS represents an attractive approach for treating cancer with the potential for inducing vaccine-like antiviral T cell expansion, immune cell redirection as a TCE, and significantly widened TI due to reduced cytokine release.

Optimising antibody properties such as affinity can be detrimental to other key properties. Here the authors use machine learning to simplify the identification of antibodies with co-optimal levels of affinity and specificity for a clinical-stage antibody that displays high levels of on- and off-target binding.

Abstract Monoclonal antibodies that target SARS-CoV-2 with high affinity are valuable for a wide range of biomedical applications involving novel coronavirus disease (COVID-19) diagnosis, treatment, and prophylactic intervention. Strategies for the rapid and reliable isolation of these antibodies, especially potent neutralizing antibodies, are critical toward improved COVID-19 response and informed future response to emergent infectious diseases. In this study, single B cell screening was used to interrogate antibody repertoires of immunized mice and isolate antigen-specific IgG1+ memory B cells. Using these methods, high-affinity, potent neutralizing antibodies were identified that target the receptor-binding domain of SARS-CoV-2. Further engineering of the identified molecules to increase valency resulted in enhanced neutralizing activity. Mechanistic investigation revealed that these antibodies compete with ACE2 for binding to the receptor-binding domain of SARS-CoV-2. These antibodies may warrant further development for urgent COVID-19 applications. Overall, these results highlight the potential of single B cell screening for the rapid and reliable identification of high-affinity, potent neutralizing antibodies for infectious disease applications.

SARS-CoV-2 variants with enhanced transmissibility represent a serious threat to global health. Here we report machine learning models that can predict the impact of receptor-binding domain (RBD) mutations on receptor (ACE2) affinity, which is linked to infectivity, and escape from human serum antibodies, which is linked to viral neutralization. Importantly, the models predict many of the known impacts of RBD mutations in current and former Variants of Concern on receptor affinity and antibody escape as well as novel sets of mutations that strongly modulate both properties. Moreover, these models reveal key opposing impacts of RBD mutations on transmissibility, as many sets of RBD mutations predicted to increase antibody escape are also predicted to reduce receptor affinity and vice versa. These models, when used in concert, capture the complex impacts of SARS-CoV-2 mutations on properties linked to transmissibility and are expected to improve the development of next-generation vaccines and biotherapeutics.

Gas-phase synthesis and detection of boron-doped nitride clusterfullerenes and a large variety of monometallofullerenes have been achieved using a pulsed laser vaporization cluster source. Density functional theory (DFT) calculations show that the electronic structures of boron-doped endohedral metallofullerenes differ from those of the pristine all-carbon cages due to the lack of one electron upon boron substitution. For monometallofullerenes, this is likely the main reason for the somewhat different abundance distribution observed for boron-doped with respect to all-carbon cages. Moreover, the three carbon atoms directly bonded to B show the most negative charges in the cage, and consequently, metal atoms are primarily placed nearby boron.

Cell lineage decisions occur in three-dimensional spatial patterns that are difficult to identify by eye. There is an ongoing effort to replicate such patterns using mathematical modeling. One approach uses long ranging cell-cell communication to replicate common spatial arrangements like checkerboard and engulfing patterns. In this model, the cell-cell communication has been implemented as a signal that disperses throughout the tissue. On the other hand, machine learning models have been developed for pattern recognition and pattern reconstruction tasks. We combined synthetic data generated by the mathematical model with spatial summary statistics and deep learning algorithms to recognize and reconstruct cell fate patterns in organoids of mouse embryonic stem cells. Application of Moran's index and pair correlation functions for in vitro and synthetic data from the model showed local clustering and radial segregation. To assess the patterns as a whole, a graph neural network was developed and trained on synthetic data from the model. Application to in vitro data predicted a low signal dispersion value. To test this result, we implemented a multilayer perceptron for the prediction of a given cell fate based on the fates of the neighboring cells. The results show a 70% accuracy of cell fate imputation based on the nine nearest neighbors of a cell. Overall, our approach combines deep learning with mathematical modeling to link cell fate patterns with potential underlying mechanisms., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Dirk et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Embryos develop in a concerted sequence of spatiotemporal arrangements of cells. In the preimplantation mouse embryo, the distribution of the cells in the inner cell mass evolves from a salt-and-pepper pattern to spatial segregation of two distinct cell types. The exact properties of the salt-and-pepper pattern have not been analyzed so far. We investigate the spatiotemporal distribution of NANOG- and GATA6-expressing cells in the ICM of the mouse blastocysts with quantitative three-dimensional single-cell-based neighborhood analyses. A combination of spatial statistics and agent-based modeling reveals that the cell fate distribution follows a local clustering pattern. Using ordinary differential equations modeling, we show that this pattern can be established by a distance-based signaling mechanism enabling cells to integrate information from the whole inner cell mass into their cell fate decision. Our work highlights the importance of longer-range signaling to ensure coordinated decisions in groups of cells to successfully build embryos., Competing Interests: The authors declare no competing interests., (© 2023 The Authors.)

During development, spatio-temporal patterns ranging from checkerboard to engulfing occur with precise proportions of the respective cell fates. Key developmental regulators are intracellular transcriptional interactions and intercellular signaling. We present an analytically tractable mathematical model based on signaling that reliably generates different cell type patterns with specified proportions. Employing statistical mechanics, We derived a cell fate decision model for two cell types. A detailed steady state analysis on the resulting dynamical system yielded necessary conditions to generate spatially heterogeneous patterns. This allows the cell type proportions to be controlled by a single model parameter. Cell-cell communication is realized by local and global signaling mechanisms. These result in different cell type patterns. A nearest neighbor signal yields checkerboard patterns. Increasing the signal dispersion, cell fate clusters and an engulfing pattern can be generated. Altogether, the presented model allows us to reliably generate heterogeneous cell type patterns of different kinds as well as desired proportions., (© 2023. The Author(s).)

It is common to evaluate pediatric patients with suspected malfunction of intraventricular shunts (VS) with cranial computed tomography (CT) as well as radiographs. Yet, the clinical yield of these studies is not well defined. We conducted a study to determine if radiographs of VS add useful clinical data in the evaluation of shunt malfunctions. A retrospective chart review of children evaluated in the emergency department for potential VS malfunction was conducted. CT scan results were categorized into five distinct categories based on the presence of shunt malfunction and comparison to prior studies. Determination of the presence of VS malfunction was based upon the discharge diagnosis. There were 205 patient encounters identified. The mean age was 5.3 years. Forty-four of the visits involved children younger than 2 years of age. Forty-eight children (23% of total) were taken to surgery for shunt malfunction. Only 8 had radiography demonstrating breakage or discontinuity of the shunt or tubing. Of these, 6 had CT scans demonstrating increased intracranial pressure. The remaining 2 had vomiting and lethargy, with one also having evidence of cerebrospinal fluid extravasation on examination. Overall, CT scans identified 46 of 48 (96%) patients with malfunction of their VS. The 2 remaining children had radiographs demonstrating abnormality of their VS. Both children, however, had a classic clinical presentation of shunt malfunction. In this series, plain radiography in patients with suspected shunt malfunction, looking for breakage or discontinuity of the shunt, may represent unnecessary ionizing radiation exposure and expense.

Oral application of atropine was used to test if a modulation of cholinergic neurotransmission changed motor excitability. Healthy volunteers received either 1 or 2 mg atropine. Paired transcranial magnetic stimulation was used to study intracortical inhibition and intracortical facilitation before, 1 h and 24 h after ingestion of atropine. In addition, the silent period, motor threshold, F wave and motor response amplitudes were measured. The 1 mg dose of atropine induced a loss of intracortical inhibition, the 2 mg dose produced an intracortical disinhibition and enhanced intracortical facilitation. These changes returned to baseline after 24 h. Other electrophysiological parameters remained unchanged. Thus, an antagonist of pre- and postsynaptic muscarinic receptors increased excitability in the human motor cortex in a dose-dependent manner, indicating an influence of the cholinergic system on motor cortex excitation.