HIV-1 VRC01 Germline-Targeting Immunogens Select Distinct Epitope-Specific B Cell Receptors.

Activating precursor B cell receptors of HIV-1 broadly neutralizing antibodies requires specifically designed immunogens. Here, we compared the abilities of three such germline-targeting immunogens against the VRC01-class receptors to activate the targeted B cells in transgenic mice expressing the germline VH of the VRC01 antibody but diverse mouse light chains. Immunogen-specific VRC01-like B cells were isolated at different time points after immunization, their VH and VL genes were sequenced, and the corresponding antibodies characterized. VRC01 B cell sub-populations with distinct cross-reactivity properties were activated by each immunogen, and these differences correlated with distinct biophysical and biochemical features of the germline-targeting immunogens. Our study indicates that the design of effective immunogens to activate B cell receptors leading to protective HIV-1 antibodies will require a better understanding of how the biophysical properties of the epitope and its surrounding surface on the germline-targeting immunogen influence its interaction with the available receptor variants in vivo.

An all-atom protein generative model.

Proteins mediate their functions through chemical interactions; modeling these interactions, which are typically through sidechains, is an important need in protein design. However, constructing an all-atom generative model requires an appropriate scheme for managing the jointly continuous and discrete nature of proteins encoded in the structure and sequence. We describe an all-atom diffusion model of protein structure, Protpardelle, which represents all sidechain states at once as a "superposition" state; superpositions defining a protein are collapsed into individual residue types and conformations during sample generation. When combined with sequence design methods, our model is able to codesign all-atom protein structure and sequence. Generated proteins are of good quality under the typical quality, diversity, and novelty metrics, and sidechains reproduce the chemical features and behavior of natural proteins. Finally, we explore the potential of our model to conduct all-atom protein design and scaffold functional motifs in a backbone- and rotamer-free way.

Computational design of transmembrane pores.

Transmembrane channels and pores have key roles in fundamental biological processes1 and in biotechnological applications such as DNA nanopore sequencing2-4, resulting in considerable interest in the design of pore-containing proteins. Synthetic amphiphilic peptides have been found to form ion channels5,6, and there have been recent advances in de novo membrane protein design7,8 and in redesigning naturally occurring channel-containing proteins9,10. However, the de novo design of stable, well-defined transmembrane protein pores that are capable of conducting ions selectively or are large enough to enable the passage of small-molecule fluorophores remains an outstanding challenge11,12. Here we report the computational design of protein pores formed by two concentric rings of α-helices that are stable and monodisperse in both their water-soluble and their transmembrane forms. Crystal structures of the water-soluble forms of a 12-helical pore and a 16-helical pore closely match the computational design models. Patch-clamp electrophysiology experiments show that, when expressed in insect cells, the transmembrane form of the 12-helix pore enables the passage of ions across the membrane with high selectivity for potassium over sodium; ion passage is blocked by specific chemical modification at the pore entrance. When incorporated into liposomes using in vitro protein synthesis, the transmembrane form of the 16-helix pore-but not the 12-helix pore-enables the passage of biotinylated Alexa Fluor 488. A cryo-electron microscopy structure of the 16-helix transmembrane pore closely matches the design model. The ability to produce structurally and functionally well-defined transmembrane pores opens the door to the creation of designer channels and pores for a wide variety of applications.

A submillimeter bundled microtubular flow battery cell with ultrahigh volumetric power density.

Flow batteries are a promising energy storage solution. However, the footprint and capital cost need further reduction for flow batteries to be commercially viable. The flow cell, where electron exchange takes place, is a central component of flow batteries. Improving the volumetric power density of the flow cell (W/Lcell) can reduce the size and cost of flow batteries. While significant progress has been made on flow battery redox, electrode, and membrane materials to improve energy density and durability, conventional flow batteries based on the planar cell configuration exhibit a large cell size with multiple bulky accessories such as flow distributors, resulting in low volumetric power density. Here, we introduce a submillimeter bundled microtubular (SBMT) flow battery cell configuration that significantly improves volumetric power density by reducing the membrane-to-membrane distance by almost 100 times and eliminating the bulky flow distributors completely. Using zinc-iodide chemistry as a demonstration, our SBMT cell shows peak charge and discharge power densities of 1,322 W/Lcell and 306.1 W/Lcell, respectively, compared with average charge and discharge power densities of <60 W/Lcell and 45 W/Lcell, respectively, of conventional planar flow battery cells. The battery cycled for more than 220 h corresponding to >2,500 cycles at off-peak conditions. Furthermore, the SBMT cell has been demonstrated to be compatible with zinc-bromide, quinone-bromide, and all-vanadium chemistries. The SBMT flow cell represents a device-level innovation to enhance the volumetric power of flow batteries and potentially reduce the size and cost of the cells and the entire flow battery.

Fully synthetic platform to rapidly generate tetravalent bispecific nanobody-based immunoglobulins.

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human VH3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor-binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the VH and VL domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

Wnt-5a-ROR2 signaling provokes metastatic colonization and angiogenesis in renal cell carcinoma and the axis activation is suppressed by prunetin.

Wnt-5a is a protein that is encoded by the WNT5A gene and is a ligand for the ROR2 receptor. However, its biological impact on clear cell renal cell carcinoma (ccRCC) remains unclear. In this study, the prognostic significance of concurrent WNT5A and ROR2 expression levels was observed to predict unfavorable overall survival and disease-specific survival. High Wnt-5a expression was detected in a ccRCC cell line panel but not in HK-2 cells, a normal proximal tubular cell line. Inhibition of DNA methyltransferase by 5-azaC in 786-O and Caki-2 cells resulted in Wnt-5a upregulation, indicating potential epigenetic modification. Furthermore, the results revealed the repression of cell movement in vitro and metastatic colonization in vivo upon WNT5A and ROR2 knockdown. The suppressions of angiogenesis in vivo and tubular-like structure formation in endothelial cells in vitro were also observed after silencing WNT5A and ROR2 expression. In addition, alteration in the downstream gene signature of the Wnt-5a-ROR2 signaling was discovered to be similar to that in MTA1-CTNNB1 axis. Moreover, prunetin treatment was found to reverse the gene signature derived from Wnt-5a-ROR2 signaling activation and to abolish ccRCC cell migration and proliferation. Overall, this study demonstrates the clinical and functional significance of the Wnt-5a-ROR2 axis and identify prunetin as a potential precision medicine for ccRCC patients harboring aberrant Wnt-5a-ROR2 signaling pathways.

Stromal Rigidity Stress Accelerates Pancreatic Intraepithelial Neoplasia Progression and Chromosomal Instability via Nuclear Protein Tyrosine Kinase 2 Localization.

Because the mechanotransduction by stromal stiffness stimulates the rupture and repair of the nuclear envelope in pancreatic progenitor cells, accumulated genomic aberrations are under selection in the tumor microenvironment. Analysis of cell growth, micronuclei, and phosphorylated Ser-139 residue of the histone variant H2AX (γH2AX) foci linked to mechanotransduction pressure in vivo during serial orthotopic passages of mouse KrasLSL-G12D/+;Trp53flox/flox;Pdx1-Cre (KPC) cancer cells in the tumor and in migrating through the size-restricted 3-µm micropores. To search for pancreatic cancer cell-of-origin, analysis of single-cell data sets revealed that the extracellular matrix shaped an alternate route of acinar-ductal transdifferentiation of acinar cells into topoisomerase II α (TOP2A)-overexpressing cancer cells and derived subclusters with copy number amplifications in MYC-PTK2 (protein tyrosine kinase 2) locus and PIK3CA. High-PTK2 expression is associated with 171 differentially methylated CpG loci, 319 differentially expressed genes, and poor overall survival in The Cancer Genome Atlas-Pancreatic Adenocarcinoma cohort. Abolished RGD-integrin signaling by disintegrin KG blocked the PTK2 phosphorylation, increased cancer apoptosis, decreased vav guanine nucleotide exchange factor 1 (VAV1) expression, and prolonged overall survival in the KPC mice. Reduction of α-smooth muscle actin deposition in the CD248 knockout KPC mice remodeled the tissue stroma and down-regulated TOP2A expression in the epithelium. In summary, stromal stiffness induced the onset of cancer cells-of-origin by ectopic TOP2A expression, and the genomic amplification of MYC-PTK2 locus via alternative transdifferentiation of pancreatic progenitor cells is the vulnerability useful for disintegrin KG treatment.

M-TUBE enables large-volume bacterial gene delivery using a high-throughput microfluidic electroporation platform.

Conventional cuvette-based and microfluidics-based electroporation approaches for bacterial gene delivery have distinct advantages, but they are typically limited to relatively small sample volumes, reducing their utility for applications requiring high throughput such as the generation of mutant libraries. Here, we present a scalable, large-scale bacterial gene delivery approach enabled by a disposable, user-friendly microfluidic electroporation device requiring minimal device fabrication and straightforward operation. We demonstrate that the proposed device can outperform conventional cuvettes in a range of situations, including across Escherichia coli strains with a range of electroporation efficiencies, and we use its large-volume bacterial electroporation capability to generate a library of transposon mutants in the anaerobic gut commensal Bifidobacterium longum.

Synthesis of functionalized mesoporous silica nanoparticles for colorimetric and fluorescence sensing of selective metal (Fe3+) ions in aqueous solution.

The fabrication of red fluorescent hybrid mesoporous silica-based nanosensor materials has promised the bioimaging and selective detection of toxic pollutants in aqueous solutions. In this study, we present a hybrid mesoporous silica nanosensor in which the propidium iodide (PI) was used to conveniently integrate into the mesopore walls using bis(trimethoxysilylpropyl silane) precursors. Various characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared (FTIR), N2 adsorption-desorption, zeta potential, particle size analysis, thermogravimetric, and UV-visible analysis were used to analyze the prepared materials. The prepared PI integrated mesoporous silica nanoparticles (PI-MSNs) selective metal ion sensing capabilities were tested with a variety of heavy metal ions (100 mM), including Ni2+, Cd2+, Co2+, Zn2+, Cr3+, Cu2+, Al3+, Mg2+, Hg2+ and Fe3+ ions. Among the investigated metal ions, the prepared PI-MSNs demonstrated selective monitoring of Fe3+ ions with a significant visible colorimetric pink color change into orange and quenching of pink fluorescence in an aqueous suspension. The selective sensing behavior of PI-MSNs might be due to the interaction of Fe3+ ions with the integrated PI functional fluorophore present in the mesopore walls. Therefore, we emphasize that the prepared PI-MSNs could be efficient for selective monitoring of Fe3+ ions in an aqueous solution and in the biological cellular microenvironment.

Interleukin-2 superkines by computational design.

Affinity maturation of protein­protein interactions is an important approach in the development of therapeutic proteins such as cytokines. Typical experimental strategies involve targeting the cytokine-receptor interface with combinatorial libraries and then selecting for higher-affinity variants. Mutations to the binding scaffold are usually not considered main drivers for improved affinity. Here we demonstrate that computational design can provide affinity-enhanced variants of interleukin-2 (IL-2) "out of the box" without any requirement for interface engineering. Using a strategy of global IL-2 structural stabilization targeting metastable regions of the three-dimensional structure, rather than the receptor binding interfaces, we computationally designed thermostable IL-2 variants with up to 40-fold higher affinity for IL-2Rß without any library-based optimization. These IL-2 analogs exhibited CD25-independent activities on T and natural killer (NK) cells both in vitro and in vivo, mimicking the properties of the IL-2 superkine "super-2" that was engineered through yeast surface display [A. M. Levin et al., Nature, 484, 529­533 (2012)]. Structure-guided stabilization of cytokines is a powerful approach to affinity maturation with applications to many cytokine and protein­protein interactions.

Asymmetric Full-Color Vectorial Meta-holograms Empowered by Pairs of Exceptional Points.

Holography holds tremendous promise in applications such as immersive virtual reality and optical communications. With the emergence of optical metasurfaces, planar optical components that have the remarkable ability to precisely manipulate the amplitude, phase, and polarization of light on the subwavelength scale have expanded the potential applications of holography. However, the realization of metasurface-based full-color vectorial holography remains particularly challenging. Here, we report a general approach utilizing a modified Gerchberg-Saxton algorithm to achieve spatially aligned full-color display and incorporating wavelength information with an image compensation strategy. We combine the Pancharatnam-Berry phase and pairs of exceptional points to address the issue of redundant twin images that generally appear for the two orthogonal circular polarizations and to enable full polarization control of the vectorial field. Our results enable the realization of an asymmetric full-color vectorial meta-hologram, paving the way for the development of full-color display, complex beam generation, and secure data storage applications.

Dickkopf-1 (DKK1) blockade mitigates osteogenesis imperfecta (OI) related bone disease.

BACKGROUND: The current treatment of osteogenesis imperfecta (OI) is imperfect. Our study thus delves into the potential of using Dickkopf-1 antisense (DKK1-AS) to treat OI. METHODS: We analysed serum DKK1 levels and their correlation with lumbar spine and hip T-scores in OI patients. Comparative analyses were conducted involving bone marrow stromal cells (BMSCs) and bone tissues from wild-type mice, untreated OI mice, and OI mice treated with DKK1-ASor DKK1-sense (DKK1-S). RESULTS: Significant inverse correlations were noted between serum DKK1 levels and lumbar spine (correlation coefficient = - 0.679, p = 0.043) as well as hip T-scores (correlation coefficient = - 0.689, p = 0.042) in OI patients. DKK1-AS improved bone mineral density (p = 0.002), trabecular bone volume/total volume fraction (p < 0.001), trabecular separation (p = 0.010), trabecular thickness (p = 0.001), trabecular number (p < 0.001), and cortical thickness (p < 0.001) in OI mice. DKK1-AS enhanced the transcription of collagen 1α1, osteocalcin, runx2, and osterix in BMSC from OI mice (all p < 0.001), resulting in a higher von Kossa-stained matrix area (p < 0.001) in ex vivo osteogenesis assays. DKK1-AS also reduced osteoclast numbers (p < 0.001), increased ß-catenin and T-cell factor 4 immunostaining reactivity (both p < 0.001), enhanced mineral apposition rate and bone formation rate per bone surface (both p < 0.001), and decreased osteoclast area (p < 0.001) in OI mice. DKK1-AS upregulated osteoprotegerin and downregulated nuclear factor-kappa B ligand transcription (both p < 0.001). Bone tissues from OI mice treated with DKK1-AS exhibited significantly higher breaking force compared to untreated OI mice (p < 0.001). CONCLUSIONS: Our study elucidates that DKK1-AS has the capability to enhance bone mechanical properties, restore the transcription of osteogenic genes, promote osteogenesis, and inhibit osteoclastogenesis in OI mice.

Frontoparietal and salience network synchronizations during nonsymbolic magnitude processing predict brain age and mathematical performance in youth.

The development and refinement of functional brain circuits crucial to human cognition is a continuous process that spans from childhood to adulthood. Research increasingly focuses on mapping these evolving configurations, with the aim to identify markers for functional impairments and atypical development. Among human cognitive systems, nonsymbolic magnitude representations serve as a foundational building block for future success in mathematical learning and achievement for individuals. Using task-based frontoparietal (FPN) and salience network (SN) features during nonsymbolic magnitude processing alongside machine learning algorithms, we developed a framework to construct brain age prediction models for participants aged 7-30. Our study revealed differential developmental profiles in the synchronization within and between FPN and SN networks. Specifically, we observed a linear increase in FPN connectivity, concomitant with a decline in SN connectivity across the age span. A nonlinear U-shaped trajectory in the connectivity between the FPN and SN was discerned, revealing reduced FPN-SN synchronization among adolescents compared to both pediatric and adult cohorts. Leveraging the Gradient Boosting machine learning algorithm and nested fivefold stratified cross-validation with independent training datasets, we demonstrated that functional connectivity measures of the FPN and SN nodes predict chronological age, with a correlation coefficient of .727 and a mean absolute error of 2.944 between actual and predicted ages. Notably, connectivity within the FPN emerged as the most contributing feature for age prediction. Critically, a more matured brain age estimate is associated with better arithmetic performance. Our findings shed light on the intricate developmental changes occurring in the neural networks supporting magnitude representations. We emphasize brain age estimation as a potent tool for understanding cognitive development and its relationship to mathematical abilities across the critical developmental period of youth. PRACTITIONER POINTS: This study investigated the prolonged changes in the brain's architecture across childhood, adolescence, and adulthood, with a focus on task-state frontoparietal and salience networks. Distinct developmental pathways were identified: frontoparietal synchronization strengthens consistently throughout development, while salience network connectivity diminishes with age. Furthermore, adolescents show a unique dip in connectivity between these networks. Leveraging advanced machine learning methods, we accurately predicted individuals' ages based on these brain circuits, with a more mature estimated brain age correlating with better math skills.

Study of individual domains contributing to MALT1 dimerization in BCL10-independent and dependent assembly.

The CARMA-BCL10-MALT1 (CBM) signalosome functions as a pivotal supramolecular module, integrating diverse receptor-induced signaling pathways to regulate BCL10-dependent NF-kB activation in innate and adaptive immunity. Conversely, the API2-MALT1 fusion protein in t(11; 18)(q21; q21) MALT lymphoma constitutively induces BCL10-independent NF-kB activation. MALT1 dimer formation is indispensable for the requisite proteolytic activity and is critical for NF-kB activation regulation in both scenarios. However, the molecular assembly of MALT1 individual domains in CBM activation remains elusive. Here we report the crystal structure of the MALT1 death domain (DD) at a resolution of 2.1 Å, incorporating reconstructed residues in previously disordered loops 1 and 2. Additionally, we observe a conformational regulation element (CRE) regulating stem-helix formation in NLRPs pyrin (PYD) within the MALT1 DD structure. The structure reveals a stem-helix-mediated dimer further corroborated in solution. To elucidate how the BCL10 filament facilitates MALT1 dimerization, we reconstitute a BCL10-CARD-MALT1-DD-IG1-IG2 complex model. We propose a N+7 rule for BCL10-dependent MALT1 dimerization via the IG1-IG2 domain and for MALT1-dependent cleavage in trans. Biochemical data further indicates concentration-dependent dimerization of the MALT1 IG1-IG2 domain, facilitating MALT1 dimerization in BCL10-independent manner. Our findings provide a structural and biochemical foundation for understanding MALT1 dimeric mechanisms, shedding light on potential BCL10-independent MALT1 dimer formation and high-order BCL10-MALT1 assembly.

Recent Advancements in Electroporation Technologies: From Bench to Clinic.

Over the past decade, the increased adoption of electroporation-based technologies has led to an expansion of clinical research initiatives. Electroporation has been utilized in molecular biology for mammalian and bacterial transfection; for food sanitation; and in therapeutic settings to increase drug uptake, for gene therapy, and to eliminate cancerous tissues. We begin this article by discussing the biophysics required for understanding the concepts behind the cell permeation phenomenon that is electroporation. We then review nano- and microscale single-cell electroporation technologies before scaling up to emerging in vivo applications.

Exploring the molecular regulation of vernalization-induced flowering synchrony in Arabidopsis.

Many plant populations exhibit synchronous flowering, which can be advantageous in plant reproduction. However, molecular mechanisms underlying flowering synchrony remain poorly understood. We studied the role of known vernalization-response and flower-promoting pathways in facilitating synchronized flowering in Arabidopsis thaliana. Using the vernalization-responsive Col-FRI genotype, we experimentally varied germination dates and daylength among individuals to test flowering synchrony in field and controlled environments. We assessed the activity of flowering regulation pathways by measuring gene expression across leaves produced at different time points during development and through a mutant analysis. We observed flowering synchrony across germination cohorts in both environments and discovered a previously unknown process where flower-promoting and repressing signals are differentially regulated between leaves that developed under different environmental conditions. We hypothesized this mechanism may underlie synchronization. However, our experiments demonstrated that signals originating from sources other than leaves must also play a pivotal role in synchronizing flowering time, especially in germination cohorts with prolonged growth before vernalization. Our results suggest flowering synchrony is promoted by a plant-wide integration of flowering signals across leaves and among organs. To summarize our findings, we propose a new conceptual model of vernalization-induced flowering synchrony and provide suggestions for future research in this field.

Metastatic tumor antigen 1 contributes to hepatocarcinogenesis posttranscriptionally through RNA-binding function.

BACKGROUND AND AIMS: Both nuclear and cytoplasmic overexpression of metastatic tumor antigen 1 (MTA1) contributes to tumorigenesis of HCC. Most studies have focused on nuclear MTA1 whose function is mainly a chromatin modifier regulating the expression of various cancer-promoting genes. By contrast, the molecular mechanisms of cytoplasmic MTA1 in carcinogenesis remain elusive. Here, we reveal a role of MTA1 in posttranscriptional gene regulation. APPROACH AND RESULTS: We conducted the in vitro and in vivo RNA-protein interaction assays indicating that MTA1 could bind directly to the 3'-untranslated region of MYC RNA. Mutation at the first glycine of the conserved GXXG loop within a K-homology II domain-like structure in MTA1 (G78D) resulted in the loss of RNA-binding activity. We used gain- and loss-of-function strategy showing that MTA1, but not the G78D mutant, extended the half-life of MYC and protected it from the lethal -7-mediated degradation. The G78D mutant exhibited lower activity in promoting tumorigenesis than wild-type in vitro and in vivo. Furthermore, RNA-immunoprecipitation sequencing analysis demonstrated that MTA1 binds various oncogenesis-related mRNAs besides MYC . The clinical relevance of cytoplasmic MTA1 and its interaction with MYC were investigated using HBV-HCC cohorts with or without early recurrence. The results showed that higher cytoplasmic MTA1 level and MTA1- MYC interaction were associated with early recurrence. CONCLUSIONS: MTA1 is a generic RNA-binding protein. Cytoplasmic MTA1 and its binding to MYC is associated with early recurrence in patients with HBV-HCC. This function enables it to regulate gene expression posttranscriptionally and contributes to hepatocarcinogenesis.

Clinical effectiveness of nirmatrelvir plus ritonavir on the short- and long-term outcome in high-risk children with COVID-19.

This study investigated the clinical effectiveness of nirmatrelvir plus ritonavir (NMV-r) on short-term outcome and the risk of postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) among pediatric patients with coronavirus disease 2019 (COVID-19). This retrospective cohort study used the TriNetX research network to identify pediatric patients between 12 and 18 years with COVID-19 between January 1, 2022 and August 31, 2023. The propensity score matching (PSM) method was used to match patients receiving NMV-r (NMV-r group) with those who did not receive NMV-r (control group). Two cohorts comprising 633 patients each (NMV-r and control groups), with balanced baseline characteristics, were identified using the PSM method. During the initial 30 days, the NMV-r group showed a lower incidence of all-cause hospitalization, mortality, or ED visits (hazard ratio [HR] = 0.546, 95% confidence interval [CI]: 0.372-0.799, p = 0.002). Additionally, the NMV-r group had a significantly lower risk of all-cause hospitalization compared with the control group (HR = 0.463, 95% CI: 0.269-0.798), with no deaths occurring in either group. In the 30-180-day follow-up period, the NMV-r group exhibited a non-significantly lower incidence of post-acute sequelae of SARS-CoV-2 infection (PASC), encompassing symptoms such as fatigue, cardiopulmonary symptoms, pain, cognitive impairments, headache, dizziness, sleep disorders, anxiety, and depression, compared to the control group. This study underscores the potential effectiveness of NMV-r in treating high-risk pediatric patients with COVID-19, demonstrating significant reductions in short-term adverse outcomes such as emergency department visits, hospitalization, or mortality within the initial 30-day period. Additionally, NMV-r shows promise in potentially preventing the development of PASC.

Progress in Photochemical and Electrochemical C-N Bond Formation for Urea Synthesis.

ConspectusHere, we discuss recent advances and pressing challenges in achieving sustainable urea synthesis. Urea stands out as the most prevalent nitrogen-based fertilizer used across the globe, making up over 50% of all manufactured fertilizers. Historically, the Bosch-Meiser process has been the go-to chemical manufacturing method for urea production. This procedure, characterized by its high-temperature and high-pressure conditions, reacts ammonia with carbon dioxide to form ammonium carbamate. Subsequently, this ammonium carbamate undergoes dehydration, facilitated by heat, producing solid urea. A concerning aspect of this method is its dependency on fossil fuels, as nearly all the process heat comes from nonrenewable sources. Consequently, the Bosch-Meiser process leaves behind a considerable carbon footprint. Current estimates predict that unchecked, carbon emissions from urea production alone might skyrocket, reaching a staggering 286 MtCO2,eq/yr by 2050. Such projections paint a clear picture regarding the necessity for more eco-friendly, sustainable urea production methods. Recently, the scientific community has shown growing interest in forming C-N bonds using alternative methods. Shifting toward photochemical or electrochemical processes, as opposed to traditional thermal-based processes, promises the potential for complete electrification of urea synthesis. This shift toward process electrification is not just an incremental change; it represents a groundbreaking advancement, the first of many steps, toward achieving deep decarbonization in the chemical manufacturing sector. Since the turn of 2020, there has been a surge in research focusing on photochemical and electrochemical urea synthesis. These methods capitalize on co-reduction of carbon dioxide with nitrogenous reactants like NOx and N2. Despite the progress, there are significant challenges that hinder these processes from reaching their full potential. In this comprehensive review, we shed light on the advances made in electrified C-N bond formation. More importantly, we focus on the invaluable insights gathered over the years, especially concerning catalytic reaction mechanisms. We have dedicated a section to underline key focal areas for up-and-coming research, emphasizing catalyst, electrolyte, and reactor design. It is undeniable that catalyst design remains at the heart of the matter, as managing the co-reduction of two distinct reactants (CO2 and nitrogenous species) is complex. This process results in a myriad of intermediates, which must be adeptly managed to both maintain catalyst activity and avoid catalyst deactivation. Moreover, the electrolytes play a pivotal role, essentially dictating the creation of optimal microenvironments that drive reaction selectivity. Finally, reactor engineering stands out as crucial to ensure optimal mass transport for all involved reactants and subsequent products. We touch upon the broader environmental ramifications of urea production and bring to light potential obstacles for alternative synthesis routes. A notable mention is the urgency of accelerating the uptake and large-scale implementation of renewable energy sources.

Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.

BACKGROUND: Ruling out obstructive coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) is time-consuming and challenging. This study developed a deep learning (DL) model to assist in detecting obstructive CAD on CCTA to streamline workflows. METHODS: In total, 2929 DICOM files and 7945 labels were extracted from curved planar reformatted CCTA images. A modified Inception V3 model was adopted. To validate the artificial intelligence (AI) model, two cardiologists labelled and adjudicated the classification of coronary stenosis on CCTA. The model was trained to differentiate the coronary artery into binary stenosis classifications <50% and ≥50% stenosis. Using the quantitative coronary angiography (QCA) consensus results as a reference standard, the performance of the AI model and CCTA radiology readers was compared by calculating Cohen's kappa coefficients at patient and vessel levels. The net reclassification index was used to evaluate the net benefit of the DL model. RESULTS: The diagnostic accuracy of the AI model was 92.3% and 88.4% at the patient and vessel levels, respectively. Compared with CCTA radiology readers, the AI model had a better agreement for binary stenosis classification at both patient and vessel levels (Cohen kappa coefficient: .79 vs. .39 and .77 vs. .40, p < .0001). The AI model also exhibited significantly improved model discrimination and reclassification (Net reclassification index = .350; Z = 4.194; p < .001). CONCLUSIONS: The developed AI model identified obstructive CAD, and the model results correlated well with QCA results. Incorporating the model into the reporting system of CCTA may improve workflows.