Newborn Screening for Severe T and B Cell Lymphopenia Using TREC/KREC Detection: A Large-Scale Pilot Study of 202,908 Newborns.

Newborn screening (NBS) for severe inborn errors of immunity (IEI), affecting T lymphocytes, and implementing measurements of T cell receptor excision circles (TREC) has been shown to be effective in early diagnosis and improved prognosis of patients with these genetic disorders. Few studies conducted on smaller groups of newborns report results of NBS that also include measurement of kappa-deleting recombination excision circles (KREC) for IEI affecting B lymphocytes. A pilot NBS study utilizing TREC/KREC detection was conducted on 202,908 infants born in 8 regions of Russia over a 14-month period. One hundred thirty-four newborns (0.66‰) were NBS positive after the first test and subsequent retest, 41% of whom were born preterm. After lymphocyte subsets were assessed via flow cytometry, samples of 18 infants (0.09‰) were sent for whole exome sequencing. Confirmed genetic defects were consistent with autosomal recessive agammaglobulinemia in 1/18, severe combined immunodeficiency - in 7/18, 22q11.2DS syndrome - in 4/18, combined immunodeficiency - in 1/18 and trisomy 21 syndrome - in 1/18. Two patients in whom no genetic defect was found met criteria of (severe) combined immunodeficiency with syndromic features. Three patients appeared to have transient lymphopenia. Our findings demonstrate the value of implementing combined TREC/KREC NBS screening and inform the development of policies and guidelines for its integration into routine newborn screening programs.

Size matters: asphaltenes with enlarged aromatic cores promote heat transfer in organic phase-change materials.

Recent experiments and atomistic computer simulations have shown that asphaltene byproducts of oil refineries can serve as thermal conductivity enhancers for organic phase-change materials such as paraffin and therefore have the potential to improve the performance of paraffin-based heat storage devices. In this work, we explore how the size of the polycyclic aromatic cores of asphaltenes affects the properties of paraffin-asphaltene systems by means of atomistic molecular dynamics simulations. We show that increasing the size of the asphaltene core from 7-8 aromatic rings to ∼20 rings drastically changes the aggregation behavior of asphaltenes. Instead of relatively small, compact aggregates formed by small-core asphaltene molecules, enlarged cores promote the formation of extended single-column structures stabilized in paraffin by asphaltene's aliphatic periphery. Chemical modification of the asphaltenes by removing the periphery leads to the formation of bundles of columns. In contrast to small-core molecules, asphaltenes with enlarged cores do not suppress paraffin crystallization even at high filler concentrations. Remarkably, asphaltenes with enlarged aromatic cores are able to increase the thermal conductivity of liquid paraffin to a greater extent compared to their small-core counterparts. This effect becomes even more pronounced for modified asphaltenes without the aliphatic side groups. Overall, our computational findings suggest that asphaltenes with enlarged aromatic cores can significantly improve the performance of heat storage devices based on organic phase change materials.

Targeting GD2-Positive Tumor Cells by Pegylated scFv Fragment-Drug Conjugates Carrying Maytansinoids DM1 and DM4.

Oligomerization of antibody fragments via modification with polyethylene glycol (pegylation) may alter their function and properties, leading to a multivalent interaction of the resulting constructs with the target antigen. In a recent study, we generated pegylated monomers and multimers of scFv fragments of GD2-specific antibodies using maleimide-thiol chemistry. Multimerization enhanced the antigen-binding properties and demonstrated a more efficient tumor uptake in a syngeneic GD2-positive mouse cancer model compared to monomeric antibody fragments, thereby providing a rationale for improving the therapeutic characteristics of GD2-specific antibody fragments. In this work, we obtained pegylated conjugates of scFv fragments of GD2-specific antibodies with maytansinoids DM1 or DM4 using tetravalent PEG-maleimide (PEG4). The protein products from the two-stage thiol-maleimide reaction resolved by gel electrophoresis indicated that pegylated scFv fragments constituted the predominant part of the protein bands, and most of the scFv formed pegylated monomers and dimers. The conjugates retained the ability to bind ganglioside GD2 comparable to that of the parental scFv fragment and to specifically interact with GD2-positive cells. Both induced significant inhibitory effects in the GD2-positive B78-D14 cell line, in contrast to the GD2-negative B16 cell line. The decrease in the B78-D14 cell viability when treated with scFv-PEG4-DM4 was more prominent than that for scFv-PEG4-DM1, and was characterized by a twofold lower half-maximal inhibitory concentration (IC50). Unlike the parental scFv fragment, the product of scFv and PEG4 conjugation (scFv-PEG4), consisting predominantly of pegylated scFv multimers and monomers, induced direct cell death in the GD2-positive B78-D14 cells. However, the potency of scFv-PEG4 was low in the selected concentration range, thus demonstrating that the cytotoxic effect of DM1 and DM4 within the antibody fragment-drug conjugates was primary. The suggested approach may contribute to development of novel configurations of antibody fragment-drug conjugates for cancer treatment.

Mesoscale computer modeling of asphaltene aggregation in liquid paraffin.

Asphaltenes represent a novel class of carbon nanofillers that are of potential interest for many applications, including polymer nanocomposites, solar cells, and domestic heat storage devices. In this work, we developed a realistic coarse-grained Martini model that was refined against the thermodynamic data extracted from atomistic simulations. This allowed us to explore the aggregation behavior of thousands of asphaltene molecules in liquid paraffin on a microsecond time scale. Our computational findings show that native asphaltenes with aliphatic side groups form small clusters that are uniformly distributed in paraffin. The chemical modification of asphaltenes via cutting off their aliphatic periphery changes their aggregation behavior: modified asphaltenes form extended stacks whose size increases with asphaltene concentration. At a certain large concentration (44 mol. %), the stacks of modified asphaltenes partly overlap, leading to the formation of large, disordered super-aggregates. Importantly, the size of such super-aggregates increases with the simulation box due to phase separation in the paraffin-asphaltene system. The mobility of native asphaltenes is systematically lower than that of their modified counterparts since the aliphatic side groups mix with paraffin chains, slowing down the diffusion of native asphaltenes. We also show that diffusion coefficients of asphaltenes are not very sensitive to the system size: enlarging the simulation box results in some increase in diffusion coefficients, with the effect being less pronounced at high asphaltene concentrations. Overall, our findings provide valuable insight into the aggregation behavior of asphaltenes on spatial and time scales that are normally beyond the scales accessible for atomistic simulations.

Mutated Flt3Lg Provides Reduced Flt3 Recycling Compared to Wild-Type Flt3Lg and Retains the Specificity of Flt3Lg-Based CAR T-Cell Targeting in AML Models.

The cells of acute myeloid leukemia are defined by clonal growth and heterogenous immunophenotypes. Chimeric antigen receptors (CARs) commonly recognize molecular targets by single-chain antibody fragments (scFvs) specific to a tumor-associated antigen. However, ScFvs may form aggregates, thus stimulating tonic CAR T-cell activation and reducing CAR T-cell functioning in vivo. Harnessing natural ligands as recognition parts of CARs, specific targeting of membrane receptors can be achieved. Previously, we presented ligand-based Flt3-CAR T-cells targeting the Flt3 receptor. The extracellular part of Flt3-CAR consisted of full-size Flt3Lg. Meanwhile, upon recognition, Flt3-CAR may potentially activate Flt3, triggering proliferative signaling in blast cells. Moreover, the long-lasting presence of Flt3Lg may lead to Flt3 downregulation. In this paper, we present mutated Flt3Lg-based Flt3m-CAR ('m'-for 'mutant') T-cells targeting Flt3. The extracellular part of Flt3m-CAR consists of full-length Flt3Lg-L27P. We have determined that ED50 for recombinant Flt3Lg-L27P produced in CHO cells is at least 10-fold higher than for the wild-type Flt3Lg. We show that the mutation in the recognizing domain of Flt3m-CAR did not affect the specificity of Flt3m-CAR T-cells when compared to Flt3-CAR T-cells. Flt3m-CAR T-cells combine the specificity of ligand-receptor recognition with reduced Flt3Lg-L27P bioactivity, leading to potentially safer immunotherapy.

Flow cell sorting followed by PCR-based clonality testing may assist in questionable diagnosis and monitoring of acute lymphoblastic leukemia.

INTRODUCTION: Multicolor flow cytometry (MFC) has highly reliable and flexible algorithms for diagnosis and monitoring of acute lymphoblastic leukemia (ALL). However, MFC analysis can be affected by poor sample quality or novel therapeutic options (e.g., targeted therapies and immunotherapy). Therefore, an additional confirmation of MFC data may be needed. We propose a simple approach for validation of MFC findings in ALL by sorting questionable cells and analyzing immunoglobulin/T-cell receptor (IG/TR) gene rearrangements via EuroClonality-based multiplex PCR. PATIENTS AND METHODS: We obtained questionable MFC results for 38 biological samples from 37 patients. In total, 42 cell populations were isolated by flow cell sorting for downstream multiplex PCR. Most of the patients (n = 29) had B-cell precursor ALL and were investigated for measurable residual disease (MRD); 79% of them received CD19-directed therapy (blinatumomab or CAR-T). RESULTS: We established the clonal nature of 40 cell populations (95.2%). By using this technique, we confirmed very low MRD levels (<0.01% MFC-MRD). We also applied it to several ambiguous findings for diagnostic samples, including those with mixed-phenotype acute leukemia, and the results obtained impacted the final diagnosis. CONCLUSION: We have demonstrated possibilities of a combined approach (cell sorting and PCR-based clonality assessment) to validate MFC findings in ALL. The technique is easy to implement in diagnostic and monitoring workflows, as it does not require isolation of a large number of cells and knowledge of individual clonal rearrangements. We believe it provides important information for further treatment.

Recognizing Minor Leukemic Populations with Monocytic Features in Mixed-Phenotype Acute Leukemia by Flow Cell Sorting Followed by Cytogenetic and Molecular Studies: Report of Five Exemplary Cases.

Mixed-phenotype acute leukemia (MPAL), a rare and heterogeneous category of acute leukemia, is characterized by cross-lineage antigen expression. Leukemic blasts in MPAL can be represented either by one population with multiple markers of different lineages or by several single-lineage populations. In some cases, a major blast population may coexist with a smaller population that has minor immunophenotypic abnormalities and may be missed even by an experienced pathologist. To avoid misdiagnosis, we suggest sorting doubtful populations and leukemic blasts and searching for similar genetic aberrations. Using this approach, we examined questionable monocytic populations in five patients with dominant leukemic populations of B-lymphoblastic origin. Cell populations were isolated either for fluorescence in situ hybridization or for clonality assessment by multiplex PCR or next-generation sequencing. In all cases, monocytic cells shared the same gene rearrangements with dominant leukemic populations, unequivocally confirming the same leukemic origin. This approach is able to identify implicit cases of MPAL and therefore leads to the necessary clinical management for patients.

Identification of Alternative Splicing in Proteomes of Human Melanoma Cell Lines without RNA Sequencing Data.

Alternative splicing is one of the main regulation pathways in living cells beyond simple changes in the level of protein expression. Most of the approaches proposed in proteomics for the identification of specific splicing isoforms require a preliminary deep transcriptomic analysis of the sample under study, which is not always available, especially in the case of the re-analysis of previously acquired data. Herein, we developed new algorithms for the identification and validation of protein splice isoforms in proteomic data in the absence of RNA sequencing of the samples under study. The bioinformatic approaches were tested on the results of proteome analysis of human melanoma cell lines, obtained earlier by high-resolution liquid chromatography and mass spectrometry (LC-MS). A search for alternative splicing events for each of the cell lines studied was performed against the database generated from all known transcripts (RefSeq) and the one composed of peptide sequences, which included all biologically possible combinations of exons. The identifications were filtered using the prediction of both retention times and relative intensities of fragment ions in the corresponding mass spectra. The fragmentation mass spectra corresponding to the discovered alternative splicing events were additionally examined for artifacts. Selected splicing events were further validated at the mRNA level by quantitative PCR.

Minibody-Based and scFv-Based Antibody Fragment-Drug Conjugates Selectively Eliminate GD2-Positive Tumor Cells.

Ganglioside GD2 is a well-established target expressed on multiple solid tumors, many of which are characterized by low treatment efficiency. Antibody-drug conjugates (ADCs) have demonstrated marked success in a number of solid tumors, and GD2-directed drug conjugates may also hold strong therapeutic potential. In a recent study, we showed that ADCs based on the approved antibody dinutuximab and the drugs monomethyl auristatin E (MMAE) or F (MMAF) manifested potent and selective cytotoxicity in a panel of tumor cell lines and strongly inhibited solid tumor growth in GD2-positive mouse cancer models. Here, we employed two different GD2-binding moieties-minibodies and scFv fragments that carry variable antibody domains identical to those of dinutuximab, and site-directly conjugated them to MMAE or MMAF by thiol-maleimide chemistry with drug-to-antibody ratios (DAR) of 2 and 1, respectively. Specific binding of the antibody fragment-drug conjugates (FDCs) to GD2 was confirmed in direct ELISA, flow cytometry, and confocal microscopy. Selective cytotoxic and cytostatic effects of the conjugates were observed in GD2-positive but not GD2-negative neuroblastoma and melanoma cell lines. Minibody-based FDCs demonstrated more pronounced cytotoxic effects and stronger antigen binding compared to scFv-based FDCs. The developed molecules may offer considerable practical benefit, since antibody fragment-drug conjugates are capable of enhancing therapeutic efficacy of ADCs by improving their pharmacokinetic characteristics and reducing side effects.

Splice-site variant in the RPS7 5'-UTR leads to a decrease in the mRNA level and development of Diamond-Blackfan anemia.

Diamond-Blackfan anemia (DBA) is an inherited bone marrow failure syndrome characterized by erythroid aplasia. Pathogenic variants in ribosomal protein (RP) genes, GATA1, TSR2, and EPO, are considered to be the etiology of DBA. Variants in 5'-untranslated regions (UTRs) of these genes are poorly studied and can complicate the variant interpretation. We investigated the functional consequences NM_001011.4:c.-19 + 1G > T variant in the donor splice-site of the RPS7 5'-UTR. This variant was found in a family where two sons with DBA were carriers. Father, who also had this variant, developed myelodysplastic syndrome, which caused his death. Search for candidate causal variants and copy number variations in DBA-associated genes left RPS7 variant as the best candidate. Trio whole exome sequencing analysis revealed no pathogenic variants in other genes. Functional analysis using luciferase expression system revealed that this variant leads to disruption of splicing. Also, a decrease in the levels of mRNA and protein expression was detected. In conclusion, the established consequences of 5'-UTR splice-site variant c.-19 + 1G > T in the RPS7 gene provide evidence that it is likely pathogenic.

Cooling-Rate Computer Simulations for the Description of Crystallization of Organic Phase-Change Materials.

A molecular-level insight into phase transformations is in great demand for many molecular systems. It can be gained through computer simulations in which cooling is applied to a system at a constant rate. However, the impact of the cooling rate on the crystallization process is largely unknown. To this end, here we performed atomic-scale molecular dynamics simulations of organic phase-change materials (paraffins), in which the cooling rate was varied over four orders of magnitude. Our computational results clearly show that a certain threshold (1.2 × 1011 K/min) in the values of cooling rates exists. When cooling is slower than the threshold, the simulations qualitatively reproduce an experimentally observed abrupt change in the temperature dependence of the density, enthalpy, and thermal conductivity of paraffins upon crystallization. Beyond this threshold, when cooling is too fast, the paraffin's properties in simulations start to deviate considerably from experimental data: the faster the cooling, the larger part of the system is trapped in the supercooled liquid state. Thus, a proper choice of a cooling rate is of tremendous importance in computer simulations of organic phase-change materials, which are of great promise for use in domestic heat storage devices.

Machine Learning with Enormous "Synthetic" Data Sets: Predicting Glass Transition Temperature of Polyimides Using Graph Convolutional Neural Networks.

In the present work, we address the problem of utilizing machine learning (ML) methods to predict the thermal properties of polymers by establishing "structure-property" relationships. Having focused on a particular class of heterocyclic polymers, namely polyimides (PIs), we developed a graph convolutional neural network (GCNN), being one of the most promising tools for working with big data, to predict the PI glass transition temperature T g as an example of the fundamental property of polymers. To train the GCNN, we propose an original methodology based on using a "transfer learning" approach with an enormous "synthetic" data set for pretraining and a small experimental data set for its fine-tuning. The "synthetic" data set contains more than 6 million combinatorically generated repeating units of PIs and theoretical values of their T g values calculated using the well-established Askadskii's quantitative structure-property relationship (QSPR) computational scheme. Additionally, an experimental data set for 214 PIs was also collected from the literature for training, fine-tuning, and validation of the GCNN. Both "synthetic" and experimental data sets are included into a PolyAskInG database (Polymer Askadskii's Intelligent Gateway). By using the PolyAskInG database, we developed GCNN which allows estimation of T g of PI with a mean absolute error (MAE) of about 20 K, which is 1.5 times lower than in the case of Askadskii QSPR analysis (33 K). To prove the efficiency and usability of the proposed GCNN architecture and training methodology for predicting polymer properties, we also employed "transfer learning" to develop alternative GCNN pretrained on proxy-characteristics taken from the popular quantum-chemical QM9 database for small compounds and fine-tuned on an experimental T g values data set from PolyAskInG database. The obtained results indicate that pretraining of GCNN on the "synthetic" polymer data set provides MAE which is almost twice as low as that in the case of using the QM9 data set in the pretraining stage (∼41 K). Furthermore, we address the questions associated with the influence of the differences in the size of the experimental and "synthetic" data sets (so-called "reality gap" problem), as well as their chemical composition on the training quality. Our results state the overall priority of using polymer data sets for developing deep neural networks, and GCNN in particular, for efficient prediction of polymer properties. Moreover, our work opens up a challenge for the theoretically supported generation of large "synthetic" data sets of polymer properties for the training of the complex ML models. The proposed methodology is rather versatile and may be generalized for predicting other properties of different polymers and copolymers synthesized through the polycondensation reaction.

Pneumonia and Related Conditions in Critically Ill Patients-Insights from Basic and Experimental Studies.

Pneumonia is an acute infectious disease with high morbidity and mortality rates. Pneumonia's development, severity and outcome depend on age, comorbidities and the host immune response. In this study, we combined theoretical and experimental investigations to characterize pneumonia and its comorbidities as well as to assess the host immune response measured by TREC/KREC levels in patients with pneumonia. The theoretical study was carried out using the Columbia Open Health Data (COHD) resource, which provides access to clinical concept prevalence and co-occurrence from electronic health records. The experimental study included TREC/KREC assays in young adults (18-40 years) with community-acquired (CAP) (n = 164) or nosocomial (NP) (n = 99) pneumonia and healthy controls (n = 170). Co-occurring rates between pneumonia, sepsis, acute respiratory distress syndrome (ARDS) and some other related conditions common in intensive care units were the top among 4170, 3382 and 963 comorbidities in pneumonia, sepsis and ARDS, respectively. CAP patients had higher TREC levels, while NP patients had lower TREC/KREC levels compared to controls. Low TREC and KREC levels were predictive for the development of NP, ARDS, sepsis and lethal outcome (AUCTREC in the range 0.71-0.82, AUCKREC in the range 0.67-0.74). TREC/KREC analysis can be considered as a potential prognostic test in patients with pneumonia.

Influence of Asphaltene Modification on Structure of P3HT/Asphaltene Blends: Molecular Dynamics Simulations.

Further development and commercialization of bulk heterojunction (BHJ) solar cells require the search for novel low-cost materials. The present study addresses the relations between the asphaltenes' chemical structure and the morphology of the poly(3-hexylthiohene) (P3HT)/asphaltene blends as potential materials for the design of BHJ solar cells. By means of all-atom molecular dynamics simulations, the formation of heterophase morphology is observed for the P3HT-based blends with carboxyl-containing asphaltenes, as well as the aggregation of the asphaltenes into highly ordered stacks. Although the π-π interactions between the polyaromatic cores of the asphaltenes in solutions are sufficient for the molecules to aggregate into ordered stacks, in a blend with a conjugated polymer, additional stabilizing factors are required, such as hydrogen bonding between carboxyl groups. It is found that the asphaltenes' aliphatic side groups may improve significantly the miscibility between the polymer and the asphaltenes, thereby preventing the formation of heterophase morphology. The results also demonstrate that the carboxyl-containing asphaltenes/P3HT ratio should be at least 1:1, as a decrease in concentration of the asphaltenes leads to the folding of the polymer chains, lower ordering in the polymer phase and the destruction of the interpenetrating 3D structure formed by P3HT and the asphaltene phases. Overall, the results of the present study for the first time reveal the aggregation behavior of the asphaltenes of varying chemical structures in P3HT, as well the influence of their presence and concentration on the polymer phase structure and blend morphology, paving the way for future development of BHJ solar cells based on the conjugated polymer/asphaltene blends.

Rheological and Mechanical Properties of Thermoplastic Crystallizable Polyimide-Based Nanocomposites Filled with Carbon Nanotubes: Computer Simulations and Experiments.

Recently, a strong structural ordering of thermoplastic semi-crystalline polyimides near single-walled carbon nanotubes (SWCNTs) was found that can enhance their mechanical properties. In this study, a comparative analysis of the results of microsecond-scale all-atom computer simulations and experimental measurements of thermoplastic semi-crystalline polyimide R-BAPB synthesized on the basis of dianhydride R (1,3-bis-(3',4-dicarboxyphenoxy) benzene) and diamine BAPB (4,4'-bis-(4″-aminophenoxy) biphenyl) near the SWCNTs on the rheological properties of nanocomposites was performed. We observe the viscosity increase in the SWCNT-filled R-BAPB in the melt state both in computer simulations and experiments. For the first time, it is proven by computer simulation that this viscosity change is related to the structural ordering of the R-BAPB in the vicinity of SWCNT but not to the formation of interchain linkage. Additionally, strong anisotropy of the rheological properties of the R-BAPB near the SWCNT surface was detected due to the polyimide chain orientation. The increase in the viscosity of the polymer in the viscous-flow state and an increase in the values of the mechanical characteristics (Young's modulus and yield peak) of the SWCNT-R-BAPB nanocomposites in the glassy state are stronger in the directions along the ordering of polymer chains close to the carbon nanofiller surface. Thus, the new experimental data obtained on the R-BAPB-based nanocomposites filled with SWCNT, being extensively compared with simulation results, confirm the idea of the influence of macromolecular ordering near the carbon nanotube on the mechanical characteristics of the composite material.

Therapeutic efficacy of antibody-drug conjugates targeting GD2-positive tumors.

BACKGROUND: Both ganglioside GD2-targeted immunotherapy and antibody-drug conjugates (ADCs) have demonstrated clinical success as solid tumor therapies in recent years, yet no research has been carried out to develop anti-GD2 ADCs against solid tumors. This is the first study to analyze cytotoxic activity of clinically relevant anti-GD2 ADCs in a wide panel of cell lines with varying GD2 expression and their effects in mouse models of GD2-positive solid cancer. METHODS: Anti-GD2 ADCs were generated based on the GD2-specific antibody ch14.18 approved for the treatment of neuroblastoma and commonly used drugs monomethyl auristatin E (MMAE) or F (MMAF), conjugated via a cleavable linker by thiol-maleimide chemistry. The antibody was produced in a mammalian expression system, and its specific binding to GD2 was analyzed. Antigen-binding properties and biodistribution of the ADCs in mice were studied in comparison with the parent antibody. Cytotoxic effects of the ADCs were evaluated in a wide panel of GD2-positive and GD2-negative tumor cell lines of neuroblastoma, glioma, sarcoma, melanoma, and breast cancer. Their antitumor effects were studied in the B78-D14 melanoma and EL-4 lymphoma syngeneic mouse models. RESULTS: The ch14.18-MMAE and ch14.18-MMAF ADCs retained antigen-binding properties of the parent antibody. Direct dependence of the cytotoxic effect on the level of GD2 expression was observed in cell lines of different origin for both ADCs, with IC50 below 1 nM for the cells with high GD2 expression and no cytotoxic effect for GD2-negative cells. Within the analyzed cell lines, ch14.18-MMAF was more effective in the cells overexpressing GD2, while ch14.18-MMAE had more prominent activity in the cells expressing low GD2 levels. The ADCs had a similar biodistribution profile in the B78-D14 melanoma model compared with the parent antibody, reaching 7.7% ID/g in the tumor at 48 hours postinjection. The average tumor size in groups treated with ch14.18-MMAE or ch14.18-MMAF was 2.6 times and 3.8 times smaller, respectively, compared with the control group. Antitumor effects of the anti-GD2 ADCs were also confirmed in the EL-4 lymphoma model. CONCLUSION: These findings validate the potential of ADCs targeting ganglioside GD2 in treating multiple GD2-expressing solid tumors.

Computer Simulations of Deep Eutectic Solvents: Challenges, Solutions, and Perspectives.

Deep eutectic solvents (DESs) are one of the most rapidly evolving types of solvents, appearing in a broad range of applications, such as nanotechnology, electrochemistry, biomass transformation, pharmaceuticals, membrane technology, biocomposite development, modern 3D-printing, and many others. The range of their applicability continues to expand, which demands the development of new DESs with improved properties. To do so requires an understanding of the fundamental relationship between the structure and properties of DESs. Computer simulation and machine learning techniques provide a fruitful approach as they can predict and reveal physical mechanisms and readily be linked to experiments. This review is devoted to the computational research of DESs and describes technical features of DES simulations and the corresponding perspectives on various DES applications. The aim is to demonstrate the current frontiers of computational research of DESs and discuss future perspectives.

Natural Flt3Lg-Based Chimeric Antigen Receptor (Flt3-CAR) T Cells Successfully Target Flt3 on AML Cell Lines.

Relapsed/refractory acute myeloid leukemia (AML) cannot be cured with chemotherapy alone, as the blasts survive the treatment. Chimeric antigen receptor (CAR) approaches for AML are being actively developed. CARs promote immune reactions through recognition of the target molecular epitopes at the surface of cancer cells. The recognition involves the extracellular portion of the CAR protein, which corresponds to either the antibody or the physiological binding partner of the targeted antigen. Here, we design a chimeric receptor with a full-length natural Flt3-ligand recognition module that targets Flt3 tyrosine kinase, known as an adverse marker in AML. We demonstrate specific killing of Flt3-positive THP-1 cells by Flt3-CAR T cells and the lack of cytotoxicity towards Flt3-negative U937 cells. We prove that the inherent cytolytic capacity of T cells is essential for the killing. Finally, we confirm the authenticity of targeting by its competitive dose-dependent inhibition with a soluble Flt3-ligand. The developed system can be viewed as a non-immunogenic functional equivalent of scFv-mediated targeting. The robust in vitro antitumor effects of Flt3-CAR T cells, combined with their low off-target cytotoxicity, hold promise for AML treatment.

TREC/KREC Levels in Young COVID-19 Patients.

COVID-19 patients with acute respiratory distress syndrome (ARDS) have an immune imbalance when systemic inflammation and dysfunction of circulating T and B cells lead to a more severe disease. Using TREC/KREC analysis, we studied the level of mature naive T and B cells in peripheral blood of COVID-19 patients and its relationship with clinical and laboratory data. TREC/KREC analysis was performed by multiplex real-time quantitative PCR on a sample of 36 patients aged 45 years or younger. The reduced TREC/KREC level was observed in ARDS patients compared with non-ARDS patients, and similar results were found for the deceased patients. During days 6 to 20 of hospitalization, a higher neutrophil-to-lymphocyte ratio (NLR) was detected in ARDS patients compared with non-ARDS patients. TREC/KREC negatively correlated with NLR; the highest correlation was recorded for TREC per 100,000 cells with the coefficient of determination R2 = 0.527. Thus, TREC/KREC analysis is a potential prognostic marker for assessing the severity and outcome in COVID-19.

Effects of Amino Acid Side-Chain Length and Chemical Structure on Anionic Polyglutamic and Polyaspartic Acid Cellulose-Based Polyelectrolyte Brushes.

We used atomistic molecular dynamics (MD) simulations to study polyelectrolyte brushes based on anionic α,L-glutamic acid and α,L-aspartic acid grafted on cellulose in the presence of divalent CaCl2 salt at different concentrations. The motivation is to search for ways to control properties such as sorption capacity and the structural response of the brush to multivalent salts. For this detailed understanding of the role of side-chain length, the chemical structure and their interplay are required. It was found that in the case of glutamic acid oligomers, the longer side chains facilitate attractive interactions with the cellulose surface, which forces the grafted chains to lie down on the surface. The additional methylene group in the side chain enables side-chain rotation, enhancing this effect. On the other hand, the shorter and more restricted side chains of aspartic acid oligomers prevent attractive interactions to a large degree and push the grafted chains away from the surface. The difference in side-chain length also leads to differences in other properties of the brush in divalent salt solutions. At a low grafting density, the longer side chains of glutamic acid allow the adsorbed cations to be spatially distributed inside the brush resulting in a charge inversion. With an increase in grafting density, the difference in the total charge of the aspartic and glutamine brushes disappears, but new structural features appear. The longer sides allow for ion bridging between the grafted chains and the cellulose surface without a significant change in main-chain conformation. This leads to the brush structure being less sensitive to changes in salt concentration.