Molecules Of Interest Research Articles

Experimental sticking coefficients of CO and N_2 on sub-micrometric cosmic grain analogs

Measuring the sticking coefficient of molecules pertinent to astrochemistry - such as CO - on substrates that mimic interstellar dust grains is crucial for the comprehensive understanding of gas-grain chemical processes. Although astrochemical models assume a sticking coefficient of 1, recent laboratory experiments on H2O and CO2 have revealed significantly lower values when measured on small grain analogs. As the effect of grain size on molecular adsorption has been largely ignored to date, further experiments are needed to determine the accretion rates of species known to freeze out on dust grains. Our aim is to determine the sticking coefficients of CO and N2 on sub-micrometric silicate and carbon grains. By quantifying realistic sticking coefficients on these dust grain analogs, we can improve the accuracy of astrochemists' predictions of molecular abundances as affected by gas-grain interactions. The molecules of interest were added to various substrates at 10 K in an ultra-high vacuum. The amount of adsorbate that stuck to the substrate was quantified using X-ray photoelectron spectroscopy. These quantities were compared to a reference with a sticking coefficient of 1, allowing the deduction of the sticking coefficient for each substrate. The average sticking coefficients of CO and N2 on grain analogs are 0.17 for CO and 0.14 for N2 on olivine powder, and 0.05 for CO and 0.07 on N2 on soot, instead of the presumed 1. This is in line with the low values previously reported for H2O and CO2 These laboratory results indicate that CO and N2 in addition to H2O and CO2 also exhibit a low sticking coefficient on dust grain analogs. It is thus necessary to reconsider the interactions between gaseous species and dust particles as a low-efficiency process. This reduction in accretion and reaction rates has important implications for how we understand astrochemistry.

Tandem "One-Shot" Measurement of Residual Chemical Shift Anisotropy and Residual Dipolar Coupling using Biphasic Supramolecular Peptide Liquid Crystals.

Both solitary and tandem applications of residual chemical shift anisotropy (RCSA) and residual dipolar coupling (RDC) show great potential for the structural and configurational determination of organic molecules. A critical component of both RDC and RCSA methodologies is the alignment medium, whose availability is limited, especially for RCSA measurement. Moreover, reported RDC and RCSA acquisitions mainly rely on two experiments conducted under two different conditions, which are relatively time-consuming and easily cause experimental errors. Herein, a biphasic supramolecular lyotropic liquid crystalline (LLC) system was developed through the self-assembly of C21H43-CONH-V4K3-CONH2, which could act as an alignment medium for not only RDC but also RCSA extraction in DMSO-d6. Notably, the RCSA extraction was easily achieved via one-shot measurement from a single one-dimensional 13C NMR experiment, with no need for special instruments, devices, and correction. Relying on the biphasic LLC medium, meanwhile, RDC data were simply extracted from a single F1-coupled HSQC experiment, different from the standard protocol that requires two spectral acquisitions corresponding to the isotropic and anisotropic conditions. Collectively, the biphasic LLC medium is applicable for tandem RCSA and RDC measurements in one single sample, advancing the stereochemical elucidation of molecules of interest.

Modeling Ligands into Maps Derived from Electron Cryomicroscopy.

Deciphering the protein-ligand interactions in a macromolecular complex is crucial for understanding the molecular mechanism, underlying biological processes, and drug development. In recent years, cryogenic sample electron microscopy (cryoEM) has emerged as a powerful technique to determine the structures of macromolecules and to investigate the mode of ligand binding at near-atomic resolution. Identifying and modeling non-protein molecules in cryoEM maps is often challenging due to anisotropic resolution across the molecule of interest and inherent noise in the data. In this article, the readers are introduced to various software and methods currently used for ligand identification, model building, and refinement of atomic coordinates using selected macromolecules. One of the simplest ways to identify the presence of a ligand, as illustrated with the enolase enzyme, is to subtract the two maps obtained with and without the ligand. The extra density of the ligand is likely to stand out in the difference map even at a higher threshold. There are instances, as shown in the case of metabotropic Glutamate receptor mGlu5, when such simple difference maps cannot be generated. The recently introduced method of deriving the Fo-Fc omit map can serve as a tool for validating and demonstrating the presence of the ligand. Finally, using the well-studied β-galactosidase as an example, the effect of resolution on modeling the ligands and solvent molecules in cryoEM maps is analyzed, and an outlook on how cryoEM can be used in drug discovery is presented.

Binding and sensing diverse small molecules using shape-complementary pseudocycles.

We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

Automated green sample preparation for quantitative extraction of lipids in different sample matrices

An essential step in all analytical workflows is the quantitative and robust extraction of the molecules of interest. While typical lipid extractions use hazardous solvents from non-renewable sources, in this work, an extraction protocol utilizing green solvents such as ethanol and ethyl acetate is presented. The workflow was also automated to reduce variability and increase robustness as well as sample throughput. Moreover, this minimizes the contamination risks and lowers the operator's exposure to organic solvents. The developed workflow was critically evaluated by the recovery of various lipid standards from different matrices (human plasma, human serum, HepG2 cells) yielding quantitative values around 80–90 % for most lipid classes. The investigation into concentration dependency reveals the robustness of the method, demonstrating consistent recoveries across various lipid concentrations and matrix contents. In non-targeted lipidomics analyses, the green solvents proved to be comparable to established protocols that use conventional solvents such as methyl‑tert-butylether (MTBE) for lipid extraction.

Derivatization, solid-phase microextraction and gas chromatography for determination of dialdehydes—biomarkers of oxidative stress

Dialdehydes are often used as biomarkers, molecules of interest for diagnosis, medical studies, and scientific research. A well-known example is malondialdehyde, which is a biomarker of oxidative stress formed during lipid peroxidation. We used combination of derivatization with O-(1,2,3,4,5)-pentafluorobenzylhydroxylamine, headspace solid-phase microextraction and gas chromatography with flame ionization detector for the analysis of dialdehydes. This combination allows to ensure the stability of analytes by derivatization, to separate them from the matrix, to preconcentrate by solid-phase microextraction, and to perform determination of dialdehydes. All the parameters affecting sensitivity and selectivity (pH and time of derivatization, sorption time, temperature of sorption, salt addition) were studied specifically for malondialdehyde, glyoxal, and methylglyoxal. The addition of salting-out agent resulted in decrease in the signal; therefore, a possible matrix effect was tested using simulated body fluid as model solution with ion composition similar to blood plasma. Established conditions for this method for dialdehydes showed 84–102% recovery in the model solution and allowed to reach the limits of quantification 0.2–0.8 μmol/L, which is low enough for the analysis of real samples. This method has the potential to be automated and is environmentally friendly because it does not require organic solvents and single-used filters or cartridges.

Low energy electron scattering cross sections of cyanotriacetylene (HC7N) based on ab-initio R-matrix method

Cyanotriacetylene (HC7N) is a linear unsaturated molecule detected in various regions of space. In this present study, we explored the quantum dynamics of low-energy electron collisions with linear cyanopolyyne molecule (HC7N) to identify the locations and structural features of their metastable negative ions (also known as transient negative ions). We employed the R-matrix method for handling low-energy electron scattering studies. To uncover trends among cyanopolyynes molecules, we have also incorporated results from Cyanoacetylene (HC3N) and Cyanodiacetylene (HC5N). Notably, we observed that the number of π* resonances increases and shifts to lower energies as the number of triple bonds increases in higher-order molecules. Our theoretical calculations contain elastic, differential, and momentum cross-sections in the elastic part. Additionally, we calculated excitation and ionization cross-sections in the inelastic regime. This comprehensive theoretical data on electron scattering will be valuable for understanding the molecular chemistry involving this interesting molecule.

Real-Time Monitoring of Hydrolysis Reactions of Pyrophosphates with Dissolution Dynamic Nuclear Polarization.

Dissolution dynamic nuclear polarization (d-DNP) has enabled applications such as the real-time monitoring of chemical reactions. Such applications are mainly for 13C and 15N spins with long spin-lattice relaxation times in the molecules of interest. However, the only applications for phosphorus using d-DNP are pH imaging and nucleation during crystallization due to the short relaxation times. Here we show that it is possible to observe enzyme reactions using d-DNP with phosphorus. Hyperpolarized 31P spins in pyrophosphate were obtained using bullet-DNP, which requires less dilution of highly polarized solid samples. Real-time monitoring of the hydrolysis reaction of pyrophosphate by inorganic pyrophosphatase from baker's yeast at physiological pH and was successfully achieved and the reaction rate was determined. This is an important reaction for a wide range of applications related to medicine, agriculture, and quantum life science.

Tunable optical properties of isoreticular UiO-67 MOFs for photocatalysis: a theoretical study.

A theoretical study of the reported photocatalytic systems based on Zr-based MOF (UiO-67) with biphenyl-4,4'-dicarboxylic acid (bpdc) and 2,2'-bipyridine-5,5'-dicarboxylic acid (bpydc) as linkers was performed. Quantum chemical calculations were carried out to understand the optical properties of the materials and to facilitate the rational design of new UiO-67 derivatives with potentially improved features as photocatalysts under ambient conditions. Hence, the effect of the structural modifications on the optical properties was studied considering different designs based on the nature of the linkers: in 1 only the bpdc linker was considered, or the mixture 1 : 1 between bpdc and bpydc linkers (labeled as 1A). Also, substituents R, -NH2, and -SH, were included in the 1A MOF only over the bpdc linker (labeled as 1A-bpdc-R) and on both bpdc and bpydc linkers (labeled as 1A-R). Thus a family of six isoreticular UiO-67 derivatives was theoretically characterized using Density Functional Theory (DFT) calculations on the ground singlet (S0) and first excited states (singlet and triplet) using Time-Dependent Density Functional Theory (TD-DFT), multiconfigurational post-Hartree-Fock method via Complete Active Space Self-Consistent Field (CASSCF). In addition, the use of periodic DFT calculations suggest that the energy transfer (ET) channel between bpdc and bpydc linkers might generate more luminescence quenching of 1A when compare to 1. Besides, the results suggest that the 1A-R (R: -SH and NH2) can be used under ambient conditions; however, the ET exhibited by 1A, cannot take place in the same magnitude in these systems. These ET can favor the photocatalytic reduction of a potential metal ion, that can coordinate with the bpydc ligand, via LMCT transition. Consequently, the MOF might be photocatalytically active against molecules of interest (such as H2, N2, CO2, among others) with photo-reduced metal ions. These theoretical results serve as a useful tool to guide experimental efforts in the design of new photocatalytic MOF-based systems.

Combined Metabolomic and NIRS Analyses Reveal Biochemical and Metabolite Changes in Goat Milk Kefir under Different Heat Treatments and Fermentation Times.

Dairy products are an important source of protein and other nutrients in the Mediterranean diet. In these countries, the most common sources of milk for producing dairy products are cow, goat, sheep, and buffalo. Andalusia is traditionally the largest producer of goat milk in Spain. Kefir is a fermented product made from bacteria and yeasts and has health benefits beyond its nutritional properties. There is a lack of knowledge about the molecular mechanisms and metabolites that bring about these benefits. In this work, the combination of analytical techniques (GC-FID, UHPLC-MS-QToF, GC-QqQ-MS, and GC-ToF-MS) resulted in the detection of 105 metabolites in kefir produced with goat milk from two different thermal treatments (raw and pasteurized) fermented at four time points (12, 24, 36, and 48 h, using 0 h as the control). Of these, 27 metabolites differed between kefir produced with raw and pasteurized milk. These changes could possibly be caused by the effect of pasteurization on the microbial population in the starting milk. Some interesting molecules were identified, such as shikimic acid, dehydroabietic acid, GABA, and tyramine, which could be related to antibacterial properties, strengthening of the immune system, and arterial pressure. Moreover, a viability assay of the NIRS technique was performed to evaluate its use in monitoring the fermentation and classification of samples, which resulted in a 90% accuracy in comparison to correctly classified samples according to their fermentation time. This study represents the most comprehensive metabolomic analysis of goat milk kefir so far, revealing the intricate changes in metabolites during fermentation and the impact of milk treatment.

DetSpace: a web server for engineering detectable pathways for bio-based chemical production.

Tackling climate change challenges requires replacing current chemical industrial processes through the rational and sustainable use of biodiversity resources. To that end, production routes to key bio-based chemicals for the bioeconomy have been identified. However, their production still remains inefficient in terms of titers, rates, and yields; because of the hurdles found when scaling up. In order to make production more efficient, strategies like automated screening and dynamic pathway regulation through biosensors have been applied as part of strain optimization. However, to date, no systematic way exists to design a genetic circuit that is responsive to concentrations of a given target compound. Here, the DetSpace web server provides a set of integrated tools that allows a user to select and design a biological circuit that performs the sensing of a molecule of interest by its enzymatic conversion to a detectable molecule through a transcription factor. In that way, the DetSpace web server allows synthetic biologists to easily design biosensing routes for the dynamic regulation of metabolic pathways in applications ranging from genetic circuits design, screening, production, and bioremediation of bio-based chemicals, to diagnostics and drug delivery.

Dissecting prostate Cancer: Single-Cell insight into Macrophage Diversity, molecular Prognosticators, and the role of Peptidylprolyl Isomerase F

BackgroundProstate cancer remains a prominent challenge in oncology, with advanced stages showing poor prognosis. The tumor microenvironment (TME), and particularly tumor-associated macrophages (TAMs), plays a crucial role in disease progression. This study explores the single-cell transcriptomics of prostate cancer, determines macrophage heterogeneity, identifies prognostic gene markers, and assesses the role of PPIF in TAMs. MethodsSingle-cell RNA sequencing data from the GEO database (GSE176031) and transcriptome data from the TCGA were processed to characterize cell populations and identify prognostic genes in prostate cancer. Macrophage subpopulations were examined through clustering, followed by gene set scoring based on migration, activation, and proliferation. PPIF expression in macrophages was investigated using multiplex immunofluorescence staining on matched prostate cancer and adjacent non-tumoral tissues. ResultsThe single-cell analysis identified 9,178 cells, categorized into 10 principal cell types, with macrophages constituting a significant part of the immune microenvironment. Four macrophage subgroups demonstrated distinct functional pathways: phagocytic, immune-regulatory, and proliferative. A total of 39 genes correlated with prostate cancer prognosis were identified, of which 10 carried the most significant prognostic information. Peptidylprolyl Isomerase F (PPIF) expression was significantly higher in TAMs from tumor tissue than normal tissue, indicating its potential regulatory role in the immune microenvironment. ConclusionThe intricate cellular architecture of the prostate cancer TME has been elucidated, with a focus on macrophage heterogeneity and functional specialization. Prognostic genes, including PPIF, were associated with survival outcomes, providing potential therapeutic targets. PPIF’s prominent expression in TAMs may serve as a lever in cancer progression, warranting further investigation as a biomarker and a molecule of interest for therapeutic targeting within the prostate cancer milieu.

Peptide derived from plant defensins: A promising 68Ga radiolabelled agent for diagnostic of infection foci in PET.

The development of new radiopharmaceuticals for the detection of hidden infection foci has great relevance for early detection and the selection of the correct treatment, particularly in immunosuppressed patients. In that sense, the labelling of antimicrobial peptides (AMPs) that are capable of binding specifically to the pathogenic microorganism which causes the infection, should provide a sufficiently specific agent, able to distinguish an infection from a sterile inflammation. Defensins are particularly interesting molecules with antimicrobial activity, the EcgDf1 defensin was identified from the genome of a Uruguayan native plant, Erythrina crista-galli, the 'Ceibo' tree. Our group has previously reported a synthetic biologically active short analogue EcgDf21 (ERFTGGHCRGFRRRCFCTKHC) successfully labelled with 99mTc. Herein we present a shorter analogue which also preserves the γ-core domain, as a pharmacophore for a potential infection detection agent. This peptide was derivatized with the bifunctional chelating agent 1,4,7-triazacyclononane-1,4,7-triacetic acid (NOTA) through a lysine linker in the amino-terminal group (NOTA-KGHCRGFRRRC) and radiolabelled with 68Ga ([68Ga]Ga-NOTA-K-EcgDf1(10)). The [68Ga]Ga-NOTA-K-EcgDf1(10) labelling procedure rendered a product with high radiochemical purity and stability in the labelling milieu. The Log P value indicated that the complex has a hydrophilic behaviour, confirmed by the biodistribution profile. The [68Ga]Ga-NOTA-K-EcgDf1(10) complex demonstrated specific binding to cultures of Candida albicans and Aspergillus niger. Its biodistribution showed renal elimination and low accumulation in the rest of the body. It was possible to successfully differentiate sterile inflammation from infection by PET images in nude mice with a target/non-target ratio of 3.3 for C. albicans and 3.7 for A. niger, respectively.

Diacylglycerol kinase is a keystone regulator of signaling relevant to the pathophysiology of asthma.

Signal transduction by G protein-coupled receptors (GPCRs), receptor tyrosine kinases (RTKs) and immunoreceptors converge at the activation of phospholipase C (PLC) for the hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) into inositol 1,4,5-trisphosphate (IP3) and diacylglycerol (DAG). This is a point for second-messenger bifurcation where DAG via protein kinase C (PKC) and IP3 via calcium activate distinct protein targets and regulate cellular functions. IP3 signaling is regulated by multiple calcium influx and efflux proteins involved in calcium homeostasis. A family of lipid kinases belonging to DAG kinases (DGKs) converts DAG to phosphatidic acid (PA), negatively regulating DAG signaling and pathophysiological functions. PA, through a series of biochemical reactions, is recycled to produce new molecules of PIP2. Therefore, DGKs act as a central switch in terminating DAG signaling and resynthesis of membrane phospholipids precursor. Interestingly, calcium and PKC regulate the activation of α and ζ isoforms of DGK that are predominantly expressed in airway and immune cells. Thus, DGK forms a feedback and feedforward control point and plays a crucial role in fine-tuning phospholipid stoichiometry, signaling, and functions. In this review, we discuss the previously underappreciated complex and intriguing DAG/DGK-driven mechanisms in regulating cellular functions associated with asthma, such as contraction and proliferation of airway smooth muscle (ASM) cells and inflammatory activation of immune cells. We highlight the benefits of manipulating DGK activity in mitigating salient features of asthma pathophysiology and shed light on DGK as a molecule of interest for heterogeneous diseases such as asthma.

Squaramide Formation for DNA-Encoded Library Synthesis.

DNA-encoded libraries (DELs) can be considered as one of the most powerful tools for the discovery of small molecules of biological interest. However, the ability to access large DELs is contingent upon having chemical transformations that work in aqueous phase and generate minimal DNA alterations and the availability of building blocks compatible with on-DNA chemistry. In addition, accessing scaffolds of interest to medicinal chemists can be challenging in a DEL setting because of inherent limitations of DNA-supported chemistry. In this context, a squaramide formation reaction was developed by using a two-step process. The mild and high-yielding reaction tolerates a wide array of functional groups and was shown to be safe for DNA, thereby making this methodology ideal for DELs.

Antibacterial Hydrogel Adhesives Based on Bifunctional Telechelic Dendritic-Linear-Dendritic Block Copolymers.

Antibiotic-resistant pathogens have been declared by the WHO as one of the major public health threats facing humanity. For that reason, there is an urgent need for materials with inherent antibacterial activity able to replace the use of antibiotics, and in this context, hydrogels have emerged as a promising strategy. Herein, we introduce the next generation of cationic hydrogels with antibacterial activity and high versatility that can be cured on demand in less than 20 s using thiol-ene click chemistry (TEC) in aqueous conditions. The approach capitalizes on a two-component system: (i) telechelic polyester-based dendritic-linear-dendritic (DLDs) block copolymers of different generations heterofunctionalized with allyl and ammonium groups, as well as (ii) polyethylene glycol (PEG) cross-linkers functionalized with thiol groups. These hydrogels resulted in highly tunable materials where the antibacterial performance can be adjusted by modifying the cross-linking density. Off-stoichiometric hydrogels showed narrow antibacterial activity directed toward Gram-negative bacteria. The presence of pending allyls opens up many possibilities for functionalization with biologically interesting molecules. As a proof-of-concept, hydrophilic cysteamine hydrochloride as well as N-hexyl-4-mercaptobutanamide, as an example of a thiol with a hydrophobic alkyl chain, generated three-component networks. In the case of cysteamine derivatives, a broader antibacterial activity was noted than the two-component networks, inhibiting the growth of Gram-positive bacteria. Additionally, these systems presented high versatility, with storage modulus values ranging from 270 to 7024 Pa and different stability profiles ranging from 1 to 56 days in swelling experiments. Good biocompatibility toward skin cells as well as strong adhesion to multiple surfaces place these hydrogels as interesting alternatives to conventional antibiotics.

Tert‐Butyl as a Functional Group: Non‐Directed Catalytic Hydroxylation of Sterically Congested Primary C−H Bonds

AbstractThe tert‐butyl group is a common aliphatic motif extensively employed to implement steric congestion and conformational rigidity in organic and organometallic molecules. Because of the combination of a high bond dissociation energy (~100 kcal mol−1) and limited accessibility, in the absence of directing groups, neither radical nor organometallic approaches are effective for the chemical modification of tert‐butyl C−H bonds. Herein we overcome these limits by employing a highly electrophilic manganese catalyst, [Mn(CF3bpeb)(OTf)2], that operates in the strong hydrogen bond donor solvent nonafluoro‐tert‐butyl alcohol (NFTBA) and catalytically activates hydrogen peroxide to generate a powerful manganese‐oxo species that effectively oxidizes tert‐butyl C−H bonds. Leveraging on the interplay of steric, electronic, medium and torsional effects, site‐selective and product chemoselective hydroxylation of the tert‐butyl group is accomplished with broad reaction scope, delivering primary alcohols as largely dominant products in preparative yields. Late‐stage hydroxylation at tert‐butyl sites is demonstrated on 6 densely functionalized molecules of pharmaceutical interest. This work uncovers a novel disconnection approach, harnessing tert‐butyl as a potential functional group in strategic synthetic planning for complex molecular architectures.

Tert-Butyl as a Functional Group: Non-Directed Catalytic Hydroxylation of Sterically Congested Primary C-H Bonds.

The tert-butyl group is a common aliphatic motif extensively employed to implement steric congestion and conformational rigidity in organic and organometallic molecules. Because of the combination of a high bond dissociation energy (~ 100 kcal mol-1) and limited accessibility, in the absence of directing groups, neither radical nor organometallic approaches are effective for the chemical modification of tert-butyl C-H bonds. Herein we overcome these limits by employing a highly electrophilic manganese catalyst, [Mn(CF3bpeb)(OTf)2], that operates in the strong hydrogen bond donor solvent nonafluoro-tert-butyl alcohol (NFTBA) and catalytically activates hydrogen peroxide to generate a powerful manganese-oxo species that effectively oxidizes tert-butyl C-H bonds. Leveraging on the interplay of steric, electronic, medium and torsional effects, site-selective and product chemoselective hydroxylation of the tert-butyl group is accomplished with broad reaction scope, delivering primary alcohols as largely dominant products in preparative yields. Late-stage hydroxylation at tert-butyl sites is demonstrated on 6 densely functionalized molecules of pharmaceutical interest. This work uncovers a novel disconnection approach, harnessing tert-butyl as a potential functional group in strategic synthetic planning for complex molecular architectures.

Mitigation of safety and environmental challenges posed by refrigerants

The abatement of safety and environmental burden associated with low and ultra-low Global Warming Potential (GWP) refrigerants is a critical undertaking. As the industry shifts towards more environmentally friendly alternatives, mitigating the potential risks and ensuring safety standards becomes paramount. The adoption of mildly and highly flammable refrigerants contributes significantly to minimizing the greenhouse gas impact on the environment, aligning with global climate and sustainability goals. However, it is essential to address safety concerns and potential environmental implications associated with the end use of these refrigerants.A method to mitigate the safety risk in a flammable refrigerant based heating, ventilation, air-conditioning, and refrigeration (HVACR) system is the primary focus of this paper. Advent of A2L and A3 refrigerants as replacements to high GWP refrigerants requires careful handling of leak episodes to lower or eliminate the risk associated with creating flammable mixtures capable of fire/explosion hazard. Solid materials tailored to target the molecule of interest (i.e., refrigerant.) by engineering the microporous structure as well as chemically functionalizing the surface to attract and hold on to the chemical compound being removed from the gas stream was realized. Quantitative analysis reveals the adsorbent's effectiveness in reducing leak potential in the range of 40 %–100 % for various refrigerants. Strategic placement and active leak management with negative pressure offer promising avenues for capturing leaked refrigerants, enhancing overall safety.

Digital-SMLM for precisely localizing emitters within the diffraction limit

Abstract Precisely pinpointing the positions of emitters within the diffraction limit is crucial for quantitative analysis or molecular mechanism investigation in biomedical research but has remained challenging unless exploiting single molecule localization microscopy (SMLM). Via integrating experimental spot dataset with deep learning, we develop a new approach, Digital-SMLM, to accurately predict emitter numbers and positions for sub-diffraction-limit spots with an accuracy of up to 98 % and a root mean square error as low as 14 nm. Digital-SMLM can accurately resolve two emitters at a close distance, e.g. 30 nm. Digital-SMLM outperforms Deep-STORM in predicting emitter numbers and positions for sub-diffraction-limited spots and recovering the ground truth distribution of molecules of interest. We have validated the generalization capability of Digital-SMLM using independent experimental data. Furthermore, Digital-SMLM complements SMLM by providing more accurate event number and precise emitter positions, enabling SMLM to closely approximate the natural state of high-density cellular structures.