Model System Research Articles

Towards reliable and efficient modeling of [Cu2O2]2+-based compound electronic structures with the partially fixed reference space protocols.

This work reports a computationally efficient approach for reliable modeling of complex electronic structures based on [Cu2O2]2+ moieties. Specifically, we explore the recently developed partially fixed reference space (PFRS) protocol to minimize the active space size, taking into account the double d-shell effects. We show that the ground-state electronic structure of the core [Cu2O2]2+ model system is dominated by the d9/d10 occupations. The PFRS-crafted active spaces are further used to generate the reference wave functions for the multi-reference coupled cluster, configuration interaction, and multi-reference perturbation theory calculations. Specifically, we demonstrate that the bare [Cu2O2]2+ core can be modeled qualitatively using active spaces as small as CAS(2,2)PFRS. To obtain quantitative agreement with the reference DMRG(32,62)CI calculations, the CAS(4,4) has to be used in conjunction with the MRCCSD correction on top of it. This reliable and computationally efficient protocol is further used to model the electronic structure and properties of ammonia coordinated [Cu2O2]2+ complexes. Finally, based on the large amount of available experimental data regarding the oxo-peroxo equilibrium of [Cu2O2]2+-based systems, it is possible to formulate educated guesses regarding the effect of each experimental variable over each d-occupancy-specific state. With a large sample size of d-occupancy-specific state dependence with ligands and solvents, it should be possible to propose new ligands with specific d-occupancy and, therefore, oxidative properties based on the d-occupancy energy gaps of relatively low-cost calculations.

Affinity-Resolved Size Exclusion Chromatography Coupled to Mass Spectrometry: A Novel Tool to Study the Attribute-and-Function Relationship in Therapeutic Monoclonal Antibodies.

Assessment of critical quality attributes (CQAs) is an important aspect during the development of therapeutic monoclonal antibodies (mAbs). Attributes that affect either the target binding or Fc receptor engagement may have direct impacts on the drug safety and efficacy and thus are considered as CQAs. Native size exclusion chromatography (SEC)-based competitive binding assay has recently been reported and demonstrated significant benefits compared to conventional approaches for CQA identification, owing to its faster turn-around and higher multiplexity. Expanding on the similar concept, we report the development of a novel affinity-resolved size exclusion chromatography-mass spectrometry (AR-SEC-MS) method for rapid CQA evaluation in therapeutic mAbs. This method features wide applicability, fast turn-around, high multiplexity, and easy implementation. Using the well-studied Fc gamma receptor III-A (FcγRIIIa) and Fc interaction as a model system, the effectiveness of this method in studying the attribute-and-function relationship was demonstrated. Further, two case studies were detailed to showcase the application of this method in assessing CQAs related to antibody target binding, which included unusual N-linked glycosylation in a bispecific antibody and Met oxidation in a monospecific antibody, both occurring within the complementarity-determining regions (CDRs).

Co-exposure to polyethylene fiber and Salmonella enterica serovar Typhimurium alters microbiome and metabolome of in vitro chicken cecal mesocosms.

Researching the exposome, a summation of exposure to one's lifespan, will aid in determining the environmental factors that contribute to disease states. There is an emerging concern that microplastic-pathogen interactions in the gastrointestinal tract of broiler chickens may lead to an increase in Salmonella infection across flocks and eventually increased incidence of human salmonellosis cases. In this research article, we elucidated the effects of acute co-exposure to polyethylene microplastics and Salmonella enterica serovar Typhimurium on the ceca microbial community in vitro. Salmonella presence caused strong shifts in the cecal metabolome but not the microbiome. The inverse was true for polyethylene fiber. Polyethylene powder had almost no effect. The co-exposure had worse effects than either alone. This demonstrates that exposure effects to the gut microbial community are contaminant-specific. When combined, the interactions between exposures exacerbate changes to the gut environment, necessitating future experiments studying low-dose chronic exposure effects with in vivo model systems.

Cellular mechanisms of monozygotic twinning: clues from assisted reproduction.

Monozygotic (MZ) twins are believed to arise from the fission of a single fertilized embryo at different stages. Monochorionic MZ twins, who share one chorion, originate from the splitting of the inner cell mass (ICM) within a single blastocyst. In the classic model for dichorionic MZ twins, the embryo splits before compaction, developing into two blastocysts. However, there are a growing number of ART cases where a single blastocyst transfer results in dichorionic MZ twins, indicating that embryo splitting may occur even after blastocyst formation. For monochorionic MZ twins, we conducted a comprehensive analysis of the cellular mechanisms involved in ICM splitting, drawing from both ART cases and animal experiments. In addition, we critically re-examine the classic early splitting model for dichorionic MZ twins. We explore cellular mechanisms leading to two separated blastocysts in ART, potentially causing dichorionic MZ twins. Relevant studies including research articles, reviews, and conference papers were searched in the PubMed database. Cases of MZ twins from IVF clinics were found by using combinations of terms including 'monozygotic twins' with 'IVF case report', 'ART', 'single embryo transfer', or 'dichorionic'. The papers retrieved were categorized based on the implicated mechanisms or as those with unexplained mechanisms. Animal experiments relating to MZ twins were found using 'mouse embryo monozygotic twins', 'mouse 8-shaped hatching', 'zebrafish janus mutant', and 'nine-banded armadillo embryo', along with literature collected through day-to-day reading. The search was limited to articles in English, with no restrictions on publication date or species. For monochorionic MZ twins, ART cases and mouse experiments demonstrate evidence that a looser ICM in blastocysts has an increased chance of ICM separation. Physical forces facilitated by blastocoel formation or 8-shaped hatching are exerted on the ICM, resulting in monochorionic MZ twins. For dichorionic MZ twins, the classic model resembles artificial cloning of mouse embryos in vitro, requiring strictly controlled splitting forces, re-joining prevention, and proper aggregation, which allows the formation of two separate human blastocysts under physiological circumstances. In contrast, ART procedures involving the transfer of a single blastocysts after atypical hatching or vitrified-warmed cycles might lead to blastocyst separation. Differences in morphology, molecular mechanisms, and timing across various animal model systems for MZ twinning can impede this research field. As discussed in future directions, recent developments of innovative in vitro models of human embryos may offer promising avenues for providing fundamental novel insights into the cellular mechanisms of MZ twinning during human embryogenesis. Twin pregnancies pose high risks to both the fetuses and the mother. While single embryo transfer is commonly employed to prevent dizygotic twin pregnancies in ART, it cannot prevent the occurrence of MZ twins. Drawing from our understanding of the cellular mechanisms underlying monochorionic and dichorionic MZ twinning, along with insights into the genetic mechanisms, could enable improved prediction, prevention, and even intervention strategies during ART procedures. N/A.

Co-exposure to polyethylene fiber and Salmonella enterica serovar Typhimurium alters microbiome and metabolome of in vitro chicken cecal mesocosms.

Researching the exposome, a summation of exposure to one's lifespan, will aid in determining the environmental factors that contribute to disease states. There is an emerging concern that microplastic-pathogen interactions in the gastrointestinal tract of broiler chickens may lead to an increase in Salmonella infection across flocks and eventually increased incidence of human salmonellosis cases. In this research article, we elucidated the effects of acute co-exposure to polyethylene microplastics and Salmonella enterica serovar Typhimurium on the ceca microbial community in vitro. Salmonella presence caused strong shifts in the cecal metabolome but not the microbiome. The inverse was true for polyethylene fiber. Polyethylene powder had almost no effect. The co-exposure had worse effects than either alone. This demonstrates that exposure effects to the gut microbial community are contaminant-specific. When combined, the interactions between exposures exacerbate changes to the gut environment, necessitating future experiments studying low-dose chronic exposure effects with in vivo model systems.

Rainfall Runoff Modelling of Panchaganga River Using HEC-HMS Software and it's Analysis.

The present study of this project is intended on the formation of a working flood model of the river Panchaganga flood in the Kolhapur stretch which is in Maharashtra state in India. Using HEC-HMS the precipitation is used to estimate the run off along the watershed. The central aim of this project resides in the development of a calibrated working model of the 2019 floods. This model is later used to simulate the various possibilities of flood event. Rainfall Runoff Model which is a mathematical model which relates the rainfall and runoff with the use of catchment area or watershed area. Hydrological modeling can estimate for the runoff in the study area of the model by evaluating the precipitation and discharges inputs given to the HEC-HMS software. Hydrological models on the other hand estimates the surface runoff within the study area. In recent decades, India has experienced an increase in the frequency of flood disasters. Flood is a flow that overtops either hydraulic structure or river bank along a stream resulting in damage to the adjoining property or life. The primary reason behind this is the Climate change and Immense urbanization, which has resulting in alteration of basin characteristics. The development projects near riverbanks have the worst effects on a reach's ability to drain, which increases the likelihood of flood-like conditions. In this project an area of the Panchaganga river is to be taken and a flood mapping using HEC-HMS (Hydrological Modelling System) and GIS software is to be drawn. According to the drawn flood map there will be a suitable mitigation measure suggested and the effect of the suggested mitigation measure is to be modeled.

Development of a New Method for Evaluating Heat-and-Moisture Exchanger Performance.

A model system described in International Organization for Standardization 9360 is the standard method for estimating the humidifying performance of heat-and-moisture exchangers (HMEs). However, there are no reliable bedside methods for evaluating the ongoing humidification performance of HMEs. Therefore, this study aimed to develop 2 clinically applicable methods for estimating the ongoing humidifying performance of HMEs and to evaluate their reliability in a model system. Physiologically expired gas was simulated using a heated humidifier, and ventilation was delivered using a ventilator with constant flow through 3 different types of HMEs. Relative humidity (RH) was measured using a capacitive-type moisture sensor. Water content lost during expiration was calculated by integrating absolute humidity (AH), instantaneous gas flow measured at the expiratory outlet of the ventilator, and time. We also calculated the water content released and captured by the HMEs during tidal ventilation by integrating the difference in AH across the HMEs, instantaneous gas flow, and time. We found that the RH, temperature, and AH were almost constant on the expiratory outlet of the ventilator but rapidly varied near the HMEs. The water content lost by the 3 HMEs was associated with the manufacturer-reported values and inversely correlated with the calculated values of the water content exchanged by the HMEs. The water content released and captured by HMEs was closely correlated with the difference in HME weight measured at the end of inspiration and expiration; however, the water content captured by HMEs seemed to be overestimated. Our results demonstrated that our system was able to detect the differences in the performance of 3 models of HMEs and suggest that our method for calculating water loss is reliable for estimating the water retention performance of HMEs during mechanical ventilation, even in the presence of a constant flow.

Development of a New Method for Evaluating Heat-and-Moisture Exchanger Performance.

A model system described in International Organization for Standardization 9360 is the standard method for estimating the humidifying performance of heat-and-moisture exchangers (HMEs). However, there are no reliable bedside methods for evaluating the ongoing humidification performance of HMEs. Therefore, this study aimed to develop 2 clinically applicable methods for estimating the ongoing humidifying performance of HMEs and to evaluate their reliability in a model system. Physiologically expired gas was simulated using a heated humidifier, and ventilation was delivered using a ventilator with constant flow through 3 different types of HMEs. Relative humidity (RH) was measured using a capacitive-type moisture sensor. Water content lost during expiration was calculated by integrating absolute humidity (AH), instantaneous gas flow measured at the expiratory outlet of the ventilator, and time. We also calculated the water content released and captured by the HMEs during tidal ventilation by integrating the difference in AH across the HMEs, instantaneous gas flow, and time. We found that the RH, temperature, and AH were almost constant on the expiratory outlet of the ventilator but rapidly varied near the HMEs. The water content lost by the 3 HMEs was associated with the manufacturer-reported values and inversely correlated with the calculated values of the water content exchanged by the HMEs. The water content released and captured by HMEs was closely correlated with the difference in HME weight measured at the end of inspiration and expiration; however, the water content captured by HMEs seemed to be overestimated. Our results demonstrated that our system was able to detect the differences in the performance of 3 models of HMEs and suggest that our method for calculating water loss is reliable for estimating the water retention performance of HMEs during mechanical ventilation, even in the presence of a constant flow.

Validation of aerosol chemical composition and optical properties provided by Copernicus Atmosphere Monitoring Service (CAMS) using ground-based global data

Monitoring particulate matter (PM) air pollution in terms of both concentration and composition, is very important due to its effects on human health and climate. In the PRIMARY project we aim at retrieving the aerosol composition from space using the hyperspectral observations from the Italian Space Agency's PRISMA mission. To this end, we are developing a machine learning algorithm trained with synthetic top-of-atmosphere reflectances and underlying aerosol fields. As part of this process, we plan to use the global forecasts from the Copernicus Atmosphere Monitoring Service (CAMS) as the core to generate this synthetic dataset. However, to proceed in this direction, a preliminary assessment of the reliability of this model-based dataset when compared to observations is necessary, also to bias correct the output if needed. With this aim, we assess the representation of the aerosol chemical composition and the related optical properties at selected globally distributed sites in CAMS, comparing the simulations with near-surface aerosol chemical analyses from the SPARTAN network and column sun-photometer observations from the AERONET network. We found that CAMS forecasts skills changed over time due to updates in the modelling system, with the latter two version cycles (46 and 47) being similar. Generally, they reproduce the aerosol composition within a factor of 2. We found a substantial overestimation of organic matter (OM) by a factor of 3. Applying a correcting factor to OM (constant at the global level) warrants a much more realistic representation of PM2.5 total mass and relative fraction of single species in CAMS. From the so derived CAMS aerosol-speciated profiles, we calculate aerosol optical properties, needed for subsequent use in a radiative transfer model. Comparison against AERONET indeed shows that OM bias correction resulted in improvements in Extinction Ångstrom Exponent (α440nm870nm). Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Asymmetry Parameter (g) simulations resulted slightly degraded, confirming the possibility of using CAMS as the base for a synthetic retrieval training dataset.

Recursive partitioning analysis for survival stratification and early imaging prediction of molecular biomarker in glioma patients

BackgroundGlioma is the most common primary brain tumor with high mortality and disability rates. Recent studies have highlighted the significant prognostic consequences of subtyping molecular pathological markers using tumor samples, such as IDH, 1p/19q, and TERT. However, the relative importance of individual markers or marker combinations in affecting patient survival remains unclear. Moreover, the high cost and reliance on postoperative tumor samples hinder the widespread use of these molecular markers in clinical practice, particularly during the preoperative period. We aim to identify the most prominent molecular biomarker combination that affects patient survival and develop a preoperative MRI-based predictive model and clinical scoring system for this combination.MethodsA cohort dataset of 2,879 patients was compiled for survival risk stratification. In a subset of 238 patients, recursive partitioning analysis (RPA) was applied to create a survival subgroup framework based on molecular markers. We then collected MRI data and applied Visually Accessible Rembrandt Images (VASARI) features to construct predictive models and clinical scoring systems.ResultsThe RPA delineated four survival groups primarily defined by the status of IDH and TERT mutations. Predictive models incorporating VASARI features and clinical data achieved AUC values of 0.85 for IDH and 0.82 for TERT mutations. Nomogram-based scoring systems were also formulated to facilitate clinical application.ConclusionsThe combination of IDH-TERT mutation status alone can identify the most distinct survival differences in glioma patients. The predictive model based on preoperative MRI features, supported by clinical assessments, offers a reliable method for early molecular mutation prediction and constitutes a valuable scoring tool for clinicians in guiding treatment strategies.

Recursive partitioning analysis for survival stratification and early imaging prediction of molecular biomarker in glioma patients

BackgroundGlioma is the most common primary brain tumor with high mortality and disability rates. Recent studies have highlighted the significant prognostic consequences of subtyping molecular pathological markers using tumor samples, such as IDH, 1p/19q, and TERT. However, the relative importance of individual markers or marker combinations in affecting patient survival remains unclear. Moreover, the high cost and reliance on postoperative tumor samples hinder the widespread use of these molecular markers in clinical practice, particularly during the preoperative period. We aim to identify the most prominent molecular biomarker combination that affects patient survival and develop a preoperative MRI-based predictive model and clinical scoring system for this combination.MethodsA cohort dataset of 2,879 patients was compiled for survival risk stratification. In a subset of 238 patients, recursive partitioning analysis (RPA) was applied to create a survival subgroup framework based on molecular markers. We then collected MRI data and applied Visually Accessible Rembrandt Images (VASARI) features to construct predictive models and clinical scoring systems.ResultsThe RPA delineated four survival groups primarily defined by the status of IDH and TERT mutations. Predictive models incorporating VASARI features and clinical data achieved AUC values of 0.85 for IDH and 0.82 for TERT mutations. Nomogram-based scoring systems were also formulated to facilitate clinical application.ConclusionsThe combination of IDH-TERT mutation status alone can identify the most distinct survival differences in glioma patients. The predictive model based on preoperative MRI features, supported by clinical assessments, offers a reliable method for early molecular mutation prediction and constitutes a valuable scoring tool for clinicians in guiding treatment strategies.

Approaching Periodic Systems in Ensemble Density Functional Theory via Finite One-Dimensional Models

Abstract Ensemble Density Functional Theory (EDFT) is a generalization of ground-state Density Functional Theory (GS DFT), which is based on an exact formal theory of finite collections of a system's ground and excited states. EDFT in various forms has been shown to improve the accuracy of calculated energy level differences in isolated model systems, atoms, and molecules, but it is not yet clear how EDFT could be used to calculate band gaps for periodic systems. We extend the application of EDFT toward periodic systems by estimating the thermodynamic limit with increasingly large finite one-dimensional "particle in a box" systems, which approach the uniform electron gas (UEG). Using ensemble-generalized Hartree and Local Spin Density Approximation (LSDA) exchange-correlation functionals, we find that corrections go to zero in the infinite limit, as expected for a metallic system. However, there is a correction to the effective mass, with results comparable to other calculations on 1D, 2D, and 3D UEGs, which indicates promise for non-trivial results from EDFT on periodic systems.

Approaching Periodic Systems in Ensemble Density Functional Theory via Finite One-Dimensional Models

Abstract Ensemble Density Functional Theory (EDFT) is a generalization of ground-state Density Functional Theory (GS DFT), which is based on an exact formal theory of finite collections of a system's ground and excited states. EDFT in various forms has been shown to improve the accuracy of calculated energy level differences in isolated model systems, atoms, and molecules, but it is not yet clear how EDFT could be used to calculate band gaps for periodic systems. We extend the application of EDFT toward periodic systems by estimating the thermodynamic limit with increasingly large finite one-dimensional "particle in a box" systems, which approach the uniform electron gas (UEG). Using ensemble-generalized Hartree and Local Spin Density Approximation (LSDA) exchange-correlation functionals, we find that corrections go to zero in the infinite limit, as expected for a metallic system. However, there is a correction to the effective mass, with results comparable to other calculations on 1D, 2D, and 3D UEGs, which indicates promise for non-trivial results from EDFT on periodic systems.

Biomimetic Charge‐Neutral Anion Receptors for Reversible Binding and Release of Highly Hydrated Phosphate in Water

AbstractControl of phosphate capture and release is vital in environmental, biological, and pharmaceutical contexts. However, the binding of trivalent phosphate (PO43−) in water is exceptionally difficult due to its high hydration energy. Based on the anion coordination chemistry of phosphate, in this study, four charge‐neutral tripodal hexaurea receptors (L1–L4), which were equipped with morpholine and polyethylene glycol terminal groups to enhance their solubility in water, were synthesized to enable the pH‐triggered phosphate binding and release in aqueous solutions. Encouragingly, the receptors were found to bind PO43− anion in a 1 : 1 ratio via hydrogen bonds in 100 % water solutions, with L1 exhibiting the highest binding constant (1.2×103 M−1). These represent the first neutral anion ligands to bind phosphate in 100 % water and demonstrate the potential for phosphate capture and release in water through pH‐triggered mechanisms, mimicking native phosphate binding proteins. Furthermore, L1 can also bind multiple bioavailable phosphate species, which may serve as model systems for probing and modulating phosphate homeostasis in biological and biomedical researches.

Intrinsic PARG inhibitor sensitivity is mimicked by TIMELESS haploinsufficiency and rescued by nucleoside supplementation.

A subset of cancer cells are intrinsically sensitive to inhibitors targeting PARG, the poly(ADP-ribose) glycohydrolase that degrades PAR chains. Sensitivity is accompanied by persistent DNA replication stress, and can be induced by inhibition of TIMELESS, a replisome accelerator. However, the nature of the vulnerability responsible for intrinsic sensitivity remains undetermined. To understand PARG activity dependency, we analysed Timeless model systems and intrinsically sensitive ovarian cancer cells. We show that nucleoside supplementation rescues all phenotypes associated with PARG inhibitor sensitivity, including replisome speed and fork stalling, S-phase completion and mitotic entry, proliferation dynamics and clonogenic potential. Importantly nucleoside supplementation restores PARG inhibitor resistance despite the continued presence of PAR chains, indicating that sensitivity does not correlate with PAR levels. In addition, we show that inhibition of thymidylate synthase, an enzyme required for dNTP homeostasis, induces PARG-dependency. Together, these observations suggest that PARG inhibitor sensitivity reflects an inability to control replisome speed and/or maintain helicase-polymerase coupling in response to nucleotide imbalances.

Revealing elusive conformations of sucrose from hydrogen bond J-coupling in H2O: A combined NMR and quantum mechanics study.

Hydrogen bonding is a crucial feature of biomolecules, but its characterization in glycans dissolved in aqueous solutions is challenging due to rapid hydrogen exchange between hydroxyl groups and H2O. In principle, the scalar (J) coupling constant can reveal the relative orientation of the atoms in the molecule. In contrast to J-coupling through H-bonds reported in proteins and nucleic acids, research on J-coupling through H-bonds in glycans dissolved in water is lacking. Here, we use sucrose as a model system for H-bonding studies; its structure, which consists of glucose (Glc) and fructose (Frc), is well-studied, and it is readily available. We apply the in-phase, antiphase-HSQC-TOCSY and quantify previously unreported through H-bond J-values for Frc-OH1-Glc-OH2 in H2O. While earlier reports of Brown and Levy indicate this H-bond as having only a single direction, our reported findings indicate the potential presence of two involving these same atoms, namely, G2OH➔F1O and F1OH➔G2O (where F and G stand for Frc and Glc, respectively). The calculated density functional theory J-values for the G2OH➔F1O agree with the experimental values. Additionally, we detected four other possible H-bonds in sucrose, which require different phi, psi (ϕ, ψ) torsion angles. The ϕ, ψ values are consistent with previous predictions of du Penhoat et al. and Venable et al. Our results will provide new insights into the molecular structure of sucrose and its interactions with proteins.

Adaptive optical third-harmonic generation microscopy for in vivo imaging of tissues

Third-harmonic generation microscopy is a powerful label-free nonlinear imaging technique, providing essential information about structural characteristics of cells and tissues without requiring external labelling agents. In this work, we integrated a recently developed compact adaptive optics module into a third-harmonic generation microscope, to measure and correct for optical aberrations in complex tissues. Taking advantage of the high sensitivity of the third-harmonic generation process to material interfaces and thin membranes, along with the 1,300-nm excitation wavelength used here, our adaptive optical third-harmonic generation microscope enabled high-resolution in vivo imaging within highly scattering biological model systems. Examples include imaging of myelinated axons and vascular structures within the mouse spinal cord and deep cortical layers of the mouse brain, along with imaging of key anatomical features in the roots of the model plant Brachypodium distachyon. In all instances, aberration correction led to enhancements in image quality.

Generating Neuroimmune Assembloids Using Human Induced Pluripotent Stem Cell (iPSC)-Derived Cortical Organoids and Microglia.

The emergence of brain organoids has revolutionized our understanding of neurodevelopment and neurological diseases by providing an in vitro model system that recapitulates key aspects of human brain development. However, conventional organoid protocols often overlook the role of microglia, the resident immune cells of the central nervous system. Microglia dysfunction is implicated in various neurological disorders, highlighting the need for their inclusion in organoid models. Here, we present a novel method for generating neuroimmune assembloids using human-induced pluripotent stem cell (iPSC)-derived cortical organoids and microglia. Building upon our previous work generating myelinating cortical organoids, we extend our methodology to include the integration of microglia, ensuring their long-term survival and maturation within the organoids. We describe two integration methods: one involving direct addition of microglia progenitors to the organoids and an alternative approach where microglia and dissociated neuronal progenitors are aggregated together in a defined ratio. To facilitate downstream analysis, we also describe a dissociation protocol for single-cell RNA sequencing (scRNA-seq) and provide guidance on fixation, cryosectioning, and immunostaining of assembloid structures. Overall, our protocol provides a comprehensive framework for generating neuroimmune assembloids, offering researchers a valuable tool for studying the interactions between neural cell types and immune cells in the context of neurological diseases.

Generating Neuroimmune Assembloids Using Human Induced Pluripotent Stem Cell (iPSC)-Derived Cortical Organoids and Microglia.

The emergence of brain organoids has revolutionized our understanding of neurodevelopment and neurological diseases by providing an in vitro model system that recapitulates key aspects of human brain development. However, conventional organoid protocols often overlook the role of microglia, the resident immune cells of the central nervous system. Microglia dysfunction is implicated in various neurological disorders, highlighting the need for their inclusion in organoid models. Here, we present a novel method for generating neuroimmune assembloids using human-induced pluripotent stem cell (iPSC)-derived cortical organoids and microglia. Building upon our previous work generating myelinating cortical organoids, we extend our methodology to include the integration of microglia, ensuring their long-term survival and maturation within the organoids. We describe two integration methods: one involving direct addition of microglia progenitors to the organoids and an alternative approach where microglia and dissociated neuronal progenitors are aggregated together in a defined ratio. To facilitate downstream analysis, we also describe a dissociation protocol for single-cell RNA sequencing (scRNA-seq) and provide guidance on fixation, cryosectioning, and immunostaining of assembloid structures. Overall, our protocol provides a comprehensive framework for generating neuroimmune assembloids, offering researchers a valuable tool for studying the interactions between neural cell types and immune cells in the context of neurological diseases.

Ion-Mediated Structural Discontinuities in Phospholipid Vesicles.

Despite intense research, methods for controlling soft matter's spontaneous self-assembly into well-defined layers remain a significant challenge. We observed ion-induced structural discontinuities of phospholipid vesicles that can be exploited for controlled self-assembly of soft materials, using DOPC and NaCl as a model system. The observations were made for the 0.25 wt % lipid concentration. We used dynamic light scattering, zeta-potential measurement, cryo-electron microscopy, small-angle X-ray, and small-angle neutron scattering to understand the reason for the discontinuities. For salt concentrations below 8 mM, we observed a decrease in the liposome diameter with increased NaCl concentration. Above 8 mM, we measured a discontinuity; the radius increases within a very narrow salt concentration range within less than 0.1 mM and then decreases for values greater than 8 mM. At 75 mM, the radius becomes constant until it grows again at around 500 mM. Microscopy and scattering experiments show a transition from unilamellar to bilamellar at 8 mM and to trilamellar at 75 mM. At 500 mM, we found a heterogeneous liposome system with many different bilayer numbers. All the experimental observations indicate that declining solvent quality and increasing osmotic pressure direct lipids to expel preferentially to the inner compartment. Upon reaching a critical concentration, excess lipids can form a new bilayer. This spontaneous self-assembly process causes simultaneous shrinkage of the aqueous core and expansion of the vesicle. This approach opens an intriguing path for controlling the self-assembly of bioinspired colloids.