The availability of highly accurate protein structure predictions from AlphaFold2 (AF2) and similar tools has hugely expanded the applicability of molecular replacement (MR) for crystal structure solution. Many structures can be solved routinely using raw models, structures processed to remove unreliable parts or models split into distinct structural units. There is therefore an open question around how many and which cases still require experimental phasing methods such as single-wavelength anomalous diffraction (SAD). Here, this question is addressed using a large set of PDB depositions that were solved by SAD. A large majority (87%) could be solved using unedited or minimally edited AF2 predictions. A further 18 (4%) yield straightforwardly to MR after splitting of the AF2 prediction using Slice'N'Dice, although different splitting methods succeeded on slightly different sets of cases. It is also found that further unique targets can be solved by alternative modelling approaches such as ESMFold (four cases), alternative MR approaches such as ARCIMBOLDO and AMPLE (two cases each), and multimeric model building with AlphaFold-Multimer or UniFold (three cases). Ultimately, only 12 cases, or 3% of the SAD-phased set, did not yield to any form of MR tested here, offering valuable hints as to the number and the characteristics of cases where experimental phasing remains essential for macromolecular structure solution.

Highly accurate protein structure prediction can generate accurate models of protein and protein–protein complexes in X-ray crystallography. However, the question of how to make more effective use of predicted models for completing structure analysis, and which strategies should be employed for the more challenging cases such as multi-helical structures, multimeric structures and extremely large structures, both in the model preparation and in the completion steps, remains open for discussion. In this paper, a new strategy is proposed based on the framework of direct methods and dual-space iteration, which can greatly simplify the pre-processing steps of predicted models both in normal and in challenging cases. Following this strategy, full-length models or the conservative structural domains could be used directly as the starting model, and the phase error and the model bias between the starting model and the real structure would be modified in the direct-methods-based dual-space iteration. Many challenging cases (from CASP14) have been tested for the general applicability of this constructive strategy, and almost complete models have been generated with reasonable statistics. The hybrid strategy therefore provides a meaningful scheme for X-ray structure determination using a predicted model as the starting point.

Form factors based on aspherical models of atomic electron density have brought great improvement in the accuracies of hydrogen atom parameters derived from X-ray crystal structure refinement. Today, two main groups of such models are available, the banks of transferable atomic densities parametrized using the Hansen–Coppens multipole model which allows for rapid evaluation of atomic form factors and Hirshfeld atom refinement (HAR)-related methods which are usually more accurate but also slower. In this work, a model that combines the ideas utilized in the two approaches is tested. It uses atomic electron densities based on Hirshfeld partitions of electron densities, which are precalculated and stored in a databank. This model was also applied during the refinement of the structures of five small molecules. A comparison of the resulting hydrogen atom parameters with those derived from neutron diffraction data indicates that they are more accurate than those obtained with the Hansen–Coppens based databank, and only slightly less accurate than those obtained with a version of HAR that neglects the crystal environment. The advantage of using HAR becomes more noticeable when the effects of the environment are included. To speed up calculations, atomic densities were represented by multipole expansion with spherical harmonics up to l = 7, which used numerical radial functions (a different approach to that applied in the Hansen–Coppens model). Calculations of atomic form factors for the small protein crambin (at 0.73 Å resolution) took only 68 s using 12 CPU cores.

Metal-based complexes with their unique chemical properties, including multiple oxidation states, radio-nuclear capabilities and various coordination geometries yield value as potential pharmaceuticals. Understanding the interactions between metals and biological systems will prove key for site-specific coordination of new metal-based lead compounds. This study merges the concepts of target coordination with fragment-based drug methodologies, supported by varying the anomalous scattering of rhenium along with infrared spectroscopy, and has identified rhenium metal sites bound covalently with two amino acid types within the model protein. A time-based series of lysozyme-rhenium-imidazole (HEWL-Re-Imi) crystals was analysed systematically over a span of 38 weeks. The main rhenium covalent coordination is observed at His15, Asp101 and Asp119. Weak (i.e. noncovalent) interactions are observed at other aspartic, asparagine, proline, tyrosine and tryptophan side chains. Detailed bond distance comparisons, including precision estimates, are reported, utilizing the diffraction precision index supplemented with small-molecule data from the Cambridge Structural Database. Key findings include changes in the protein structure induced at the rhenium metal binding site, not observed in similar metal-free structures. The binding sites are typically found along the solvent-channel-accessible protein surface. The three primary covalent metal binding sites are consistent throughout the time series, whereas binding to neighbouring amino acid residues changes through the time series. Co-crystallization was used, consistently yielding crystals four days after setup. After crystal formation, soaking of the compound into the crystal over 38 weeks is continued and explains these structural adjustments. It is the covalent bond stability at the three sites, their proximity to the solvent channel and the movement of residues to accommodate the metal that are important, and may prove useful for future radiopharmaceutical development including target modification.

Carbonic anhydrase (CA) was among the first proteins whose X-ray crystal structure was solved to atomic resolution. CA proteins have essentially the same fold and similar active centers that differ in only several amino acids. Primary sulfonamides are well defined, strong and specific binders of CA. However, minor variations in chemical structure can significantly alter their binding properties. Over 1000 sulfonamides have been designed, synthesized and evaluated to understand the correlations between the structure and thermodynamics of their binding to the human CA isozyme family. Compound binding was determined by several binding assays: fluorescence-based thermal shift assay, stopped-flow enzyme activity inhibition assay, isothermal titration calorimetry and competition assay for enzyme expressed on cancer cell surfaces. All assays have advantages and limitations but are necessary for deeper characterization of these protein–ligand interactions. Here, the concept and importance of intrinsic binding thermodynamics is emphasized and the role of structure–thermodynamics correlations for the novel inhibitors of CA IX is discussed – an isozyme that is overexpressed in solid hypoxic tumors, and thus these inhibitors may serve as anticancer drugs. The abundant structural and thermodynamic data are assembled into the Protein–Ligand Binding Database to understand general protein–ligand recognition principles that could be used in drug discovery.

Ultra-intense, ultra-fast X-ray free-electron lasers (XFELs) enable the imaging of single protein molecules under ambient temperature and pressure. A crucial aspect of structure reconstruction involves determining the relative orientations of each diffraction pattern and recovering the missing phase information. In this paper, we introduce a predicted model-aided algorithm for orientation determination and phase retrieval, which has been tested on various simulated datasets and has shown significant improvements in the success rate, accuracy and efficiency of XFEL data reconstruction.

The success of experimental phasing in macromolecular crystallography relies primarily on the accurate locations of heavy atoms bound to the target crystal. To improve the process of substructure determination, a modified phase-retrieval algorithm built on the framework of the relaxed alternating averaged reflection (RAAR) algorithm has been developed. Importantly, the proposed algorithm features a combination of the π-half phase perturbation for weak reflections and enforces the direct-method-based tangent formula for strong reflections in reciprocal space. The proposed algorithm is extensively demonstrated on a total of 100 single-wavelength anomalous diffraction (SAD) experimental datasets, comprising both protein and nucleic acid structures of different qualities. Compared with the standard RAAR algorithm, the modified phase-retrieval algorithm exhibits significantly improved effectiveness and accuracy in SAD substructure determination, highlighting the importance of additional constraints for algorithmic performance. Furthermore, the proposed algorithm can be performed without human intervention under most conditions owing to the self-adaptive property of the input parameters, thus making it convenient to be integrated into the structural determination pipeline. In conjunction with the IPCAS software suite, we demonstrated experimentally that automatic de novo structure determination is possible on the basis of our proposed algorithm.

Cryogenic electron microscopy (cryo-EM) is a pivotal technique for imaging macromolecular structures. However, despite extensive processing of large image sets collected in cryo-EM experiments to amplify the signal-to-noise ratio, the reconstructed 3D protein-density maps are often limited in quality due to residual noise, which in turn affects the accuracy of the macromolecular representation. Here, crefDenoiser is introduced, a denoising neural network model designed to enhance the signal in 3D cryo-EM maps produced with standard processing pipelines. The crefDenoiser model is trained without the need for `clean' ground-truth target maps. Instead, a custom dataset is employed, composed of real noisy protein half-maps sourced from the Electron Microscopy Data Bank repository. Competing with the current state-of-the-art, crefDenoiser is designed to optimize for the theoretical noise-free map during self-supervised training. We demonstrate that our model successfully amplifies the signal across a wide variety of protein maps, outperforming a classic map denoiser and following a network-based sharpening model. Without biasing the map, the proposed denoising method leads to improved visibility of protein structural features, including protein domains, secondary structure elements and modest high-resolution feature restoration.

Ultrafast, high-intensity X-ray free-electron lasers can perform diffraction imaging of single protein molecules. Various algorithms have been developed to determine the orientation of each single-particle diffraction pattern and reconstruct the 3D diffraction intensity. Most of these algorithms rely on the premise that all diffraction patterns originate from identical protein molecules. However, in actual experiments, diffraction patterns from multiple different molecules may be collected simultaneously. Here, we propose a predicted model-aided one-step classification–multireconstruction algorithm that can handle mixed diffraction patterns from various molecules. The algorithm uses predicted structures of different protein molecules as templates to classify diffraction patterns based on correlation coefficients and determines orientations using a correlation maximization method. Tests on simulated data demonstrated high accuracy and efficiency in classification and reconstruction.

Three solid solutions of [CH3NH3]CoxNi1−x(HCOO)3, with x = 0.25 (1), x = 0.50 (2) and x = 0.75 (3), were synthesized and their nuclear structures and magnetic properties were characterized using single-crystal neutron diffraction and magnetization measurements. At room temperature, all three compounds crystallize in the Pnma orthorhombic space group, akin to the cobalt and nickel end series members. On cooling, each compound undergoes a distinct series of structural transitions to modulated structures. Compound 1 exhibits a phase transition to a modulated structure analogous to the pure Ni compound [Cañadillas-Delgado, L., Mazzuca, L., Fabelo, O., Rodríguez-Carvajal, J. & Petricek, V. (2020). Inorg. Chem. 59, 17896–17905], whereas compound 3 maintains the behaviour observed in the pure Co compound reported previously [Canadillas-Delgado, L., Mazzuca, L., Fabelo, O., Rodriguez-Velamazan, J. A. & Rodriguez-Carvajal, J. (2019). IUCrJ, 6, 105–115], although in both cases the temperatures at which the phase transitions occur differ slightly from the pure phases. Monochromatic neutron diffraction measurements showed that the structural evolution of 2 diverges from that of either parent compound, with competing hydrogen bond interactions that drive the modulation throughout the series, producing a unique sequence of phases. It involves two modulated phases below 96 (3) and 59 (3) K, with different q vectors, similar to the pure Co compound (with modulated phases below 128 and 96 K); however, it maintains the modulated phase below magnetic order [at 22.5 (7) K], resembling the pure Ni compound (which presents magnetic order below 34 K), resulting in an improper modulated magnetic structure. Despite these large-scale structural changes, magnetometry data reveal that the bulk magnetic properties of these solid solutions form a linear continuum between the end members. Notably, doping of the metal site in these solid solutions allows for tuning of bulk magnetic properties, including magnetic ordering temperature, transition temperatures and the nature of nuclear phase transitions, through adjustment of metal ratios.

Traditional X-ray methods are extensively applied to commercial cement samples in order to determine their physical and chemical properties. Powder patterns are routinely used to quantify the composition of these phase mixtures, but structure determination becomes difficult because of reflection overlapping caused by the high number of different crystal structures. The fast-growing 3D electron diffraction technique and its related automated acquisition protocols arise as a potentially very interesting tool for the cement industry, since they enable the fast and systematic acquisition of diffraction data from individual particles. In this context, electron diffraction has been used in the investigation of the different crystalline phases present in various commercial clinkers for cement. Automated data collection procedures and subsequent data processing have enabled the structural characterization of the different crystal structures from which the α'H polymorph of Ca2SiO4 (belite) exhibited satellite reflections. Its average crystal structure has been known since 1971 and satellite reflections have been reported previously, yet the modulation was never fully described by means of the superspace formalism. Here, the incommensurately modulated structure is solved and refined using harmonic and crenel functions in the superspace group Pnma(α00)0ss, showing the potential of 3D electron diffraction for systematic crystallographic characterizations of cement. A full description of the different belite polymorphs is provided considering this modulated structure.

The title compound, [Co(NCS)2(C6H7N)4] or Co(NCS)2(4-methyl­pyridine)4, was prepared by the reaction of Co(NCS)2 with 4-methyl­pyridine in water and is isotypic to one of the polymorphs of Ni(NCS)2(4-methyl­pyridine)4 [Kerr & Williams (1977). Acta Cryst. B33, 3589–3592 and Soldatov et al. (2004). Cryst. Growth Des. 4, 1185–1194]. Comparison of the experimental X-ray powder pattern with that calculated from the single-crystal data proves that a pure phase has been obtained. The asymmetric unit consists of one CoII cation, two crystallographically independent thio­cyanate anions and four independent 4-meth­yl­pyridine ligands, all located in general positions. The CoII cations are sixfold coordinated to two terminally N-bonded thio­cyanate anions and four 4-methyl­pyridine coligands within slightly distorted octa­hedra. Between the complexes, a number of weak C—H⋯N and C—H⋯S contacts are found. This structure represent a polymorphic modification of Co(NCS)2(4-methyl­pyridine)4 already reported in the CCD [Harris et al. (2003). NASA Technical Reports, 211890]. In contrast to this form, the crystal structure of the new polymorph shows a denser packing, indicating that it is thermodynamically stable at least at low temperatures. Thermogravimetric and differential thermoanalysis reveal that the title compound starts to decomposes at about 100°C and that the coligands are removed in separate steps without any sign of a polymorphic transition before decomposition.

The observation of neutron interference using a triple Laue interferometer formed by two separate crystals opens the way to the construction and operation of skew-symmetric interferometers with extended arm separation and length. The specifications necessary for their successful operation are investigated here: most importantly, how the manufacturing tolerance and crystal alignments impact the interference visibility. In contrast with previous studies, both incoherent sources and the three-dimensional operation of the interferometer are considered. It is found that, with a Gaussian Schell model of an incoherent source, the integrated density of the particles leaving the interferometer is the same as that yielded by a coherent Gaussian source having a radius equal to the coherence length.

Low-energy electron diffraction patterns contain precise information about the structure of the surface studied. However, retrieving the real space lattice periodicity from complex diffraction patterns is challenging, especially when the modeled patterns originate from superlattices with large unit cells composed of several symmetry-equivalent domains without a simple relation to the substrate. This work presents ProLEED Studio software, built to provide simple, intuitive and precise modeling of low-energy electron diffraction patterns. The interactive graphical user interface allows real-time modeling of experimental diffraction patterns, change of depicted diffraction spot intensities, visualization of different diffraction domains, and manipulation of any lattice points or diffraction spots. The visualization of unit cells, lattice vectors, grids and scale bars as well as the possibility of exporting ready-to-publish models in bitmap and vector formats significantly simplifies the modeling process and publishing of results.

A systematic procedure is introduced for modeling charge-neutral non-polar surfaces of ionic minerals containing polyatomic anions. By integrating distance- and charge-based clustering to identify chemical species within the mineral bulk, our pipeline, PolyCleaver, renders a variety of theoretically viable surface terminations. As a demonstrative example, this approach was applied to forsterite (Mg2SiO4), unveiling a rich interface landscape based on interactions with formaldehyde, a relevant multifaceted molecule, and more particularly in prebiotic chemistry. This high-throughput method, going beyond techniques traditionally applied in the modeling of minerals, offers new insights into the potential catalytic properties of diverse surfaces, enabling a broader exploration of synthetic pathways in complex mineral systems.

Proteins are well known `shapeshifters' which change conformation to function. In crystallography, multiple conformational states are often present within the crystal and the resulting electron-density map. Yet, explicitly incorporating alternative states into models to disentangle multi-conformer ensembles is challenging. We previously reported the tool FLEXR, which, within a few minutes, automatically separates conformational signal from noise and builds the corresponding, often missing, structural features into a multi-conformer model. To make the method widely accessible for routine multi-conformer building as part of the computational toolkit for macromolecular crystallography, we present a graphical user interface (GUI) for FLEXR, designed as a plugin for Coot 1. The GUI implementation seamlessly connects FLEXR models with the existing suite of validation and modeling tools available in Coot. We envision that FLEXR will aid crystallographers by increasing access to a multi-conformer modeling method that will ultimately lead to a better representation of protein conformational heterogeneity in the Protein Data Bank. In turn, deeper insights into the protein conformational landscape may inform biology or provide new opportunities for ligand design. The code is open source and freely available on GitHub at https://github.com/TheFischerLab/FLEXR-GUI.

The strong metal–support interaction (SMSI) is a phenomenon observed in supported metal catalyst systems in which reducible metal oxide supports can form overlayers over the surface of active metal nanoparticles (NPs) under a hydrogen (H2) environment at elevated temperatures. SMSI has been shown to affect catalyst performance in many reactions by changing the type and number of active sites on the catalyst surface. Laboratory methods for the analysis of SMSI at the nanoparticle-ensemble level are lacking and mostly based on indirect evidence, such as gas chemisorption. Here, we demonstrate the possibility to detect and characterize SMSIs in Co/TiOx model catalysts using the laboratory X-ray standing wave (XSW) technique for a large ensemble of NPs at the bulk scale. We designed a thermally stable MoNx/SiNx periodic multilayer to retain XSW generation after reduction with H2 gas at 600°C. The model catalyst system was synthesized here by deposition of a thin TiOx layer on top of the periodic multilayer, followed by Co NP deposition via spare ablation. A partial encapsulation of Co NPs by TiOx was identified by analyzing the change in Ti atomic distribution. This novel methodological approach can be extended to observe surface restructuring of model catalysts in situ at high temperature (up to 1000°C) and pressure (≤3 mbar), and can also be relevant for fundamental studies in the thermal stability of membranes, as well as metallurgy.

A deep-learning algorithm is proposed for the inpainting of Bragg coherent diffraction imaging (BCDI) patterns affected by detector gaps. These regions of missing intensity can compromise the accuracy of reconstruction algorithms, inducing artefacts in the final result. It is thus desirable to restore the intensity in these regions in order to ensure more reliable reconstructions. The key aspect of the method lies in the choice of training the neural network with cropped sections of diffraction data and subsequently patching the predictions generated by the model along the gap, thus completing the full diffraction peak. This approach enables access to a greater amount of experimental data for training and offers the ability to average overlapping sections during patching. As a result, it produces robust and dependable predictions for experimental data arrays of any size. It is shown that the method is able to remove gap-induced artefacts on the reconstructed objects for both simulated and experimental data, which becomes essential in the case of high-resolution BCDI experiments.

Neutron diffraction beamlines have traditionally relied on deploying large detector arrays of 3He tubes or neutron-sensitive scintillators coupled with photomultipliers to efficiently probe crystallographic and microstructure information of a given material. Given the large upfront cost of custom-made data acquisition systems and the recent scarcity of 3He, new diffraction beamlines or upgrades to existing ones demand innovative approaches. This paper introduces a novel Timepix3-based event-mode imaging neutron diffraction detector system as well as first results of a silicon powder diffraction measurement made at the HIPPO neutron powder diffractometer at the Los Alamos Neutron Science Center. Notably, these initial measurements were conducted simultaneously with the 3He array on HIPPO, enabling direct comparison. Data reduction for this type of data was implemented in the MAUD code, enabling Rietveld analysis. Results from the Timepix3-based setup and HIPPO were benchmarked against McStas simulations, showing good agreement for peak resolution. With further development, systems such as the one presented here may substantially reduce the cost of detector systems for new neutron instrumentation as well as for upgrades of existing beamlines.

Small-angle neutron scattering is a widely used technique to study large-scale structures in bulk samples. The largest accessible length scale in conventional Bragg scattering is determined by the combination of the longest available neutron wavelength and smallest resolvable scattering angle. A method is presented that circumvents this limitation and is able to extract larger length scales from the low-q power-law scattering using a modification of the well known Porod law connecting the scattered intensity of randomly distributed objects to their specific surface area. It is shown that in the special case of a highly aligned domain structure the specific surface area extracted from the modified Porod law can be used to determine specific length scales of the domain structure. The analysis method is applied to study the micrometre-sized domain structure found in the intermediate mixed state of the superconductor niobium. The analysis approach allows the range of accessible length scales to be extended from 1 µm to up to 40 µm using a conventional small-angle neutron scattering setup.

This article presents a web-based framework to build a database without in-depth programming knowledge given a set of CIF dictionaries and a collection of CIFs. The framework consists of two main elements: the public site that displays the information contained in the CIFs in an ordered manner, and the restricted administrative site which defines how that information is stored, processed and, eventually, displayed. Thus, the web application allows users to easily explore, filter and access the data, download the original CIFs, and visualize the structures via JSmol. The modulated structures open database B-IncStrDB, the official International Union of Crystallography repository for this type of material and available through the Bilbao Crystallographic Server, has been re-implemented following the proposed framework.

The Australian Synchrotron Imaging and Medical Beamline (IMBL) uses a superconducting multipole wiggler (SCMPW) source, dual crystal Laue monochromator and 135 m propagation distance to enable imaging and computed tomography (CT) studies of large samples with mono-energetic radiation. This study aimed to quantify two methods for CT dose reduction: wiggler source operation at reduced magnetic field strength, and beam modulation with spatial filters placed upstream from the sample. Transmission measurements with copper were used to indirectly quantify the influence of third harmonic radiation. Operation at lower wiggler magnetic field strength reduces dose rates by an order of magnitude, and suppresses the influence of harmonic radiation, which is of significance near 30 keV. Beam shaping filters modulate the incident beam profile for near constant transmitted signal, and offer protection to radio-sensitive surface organs: the eye lens, thyroid and female breast. Their effect is to reduce the peripheral dose and the dose to the scanned volume by about 10% for biological samples of 35–50 mm diameter and by 20–30% for samples of up to 160 mm diameter. CT dosimetry results are presented as in-air measurements that are specific to the IMBL, and as ratios to in-air measurements that may be applied to other beamlines. As CT dose calculators for small animals are yet to be developed, results presented here and in a previous study may be used to estimate absorbed dose to organs near the surface and the isocentre.

HMRC has appointed

Germany-based fintech MODIFI has announced...

Moderna says recently completed studies have found its vaccine to have a neutralizing effect against all COVID-19 variants tested, including the delta variant.; Credit: Fred Tanneau/AFP via Getty Images

Studies have found that Moderna's COVID-19 vaccine is effective against several variants of concern, including the delta variant, the biotech company announced.

Moderna said Tuesday that recently completed studies have found the vaccine to have a neutralizing effect against all COVID-19 variants tested, including the beta, delta, eta and kappa variants.

While still highly effective against the delta variant, the study showed the vaccine was less effective against it and certain other variants than against the original strain of the virus.

The antibody response against the delta variant was about two times weaker than against the ancestral strain of the virus.

The news echoes other findings that the Moderna and Pfizer vaccines are highly effective against the delta variant. A study published this month in Nature found that Pfizer's vaccine was able to neutralize variants including delta, though at somewhat reduced strength.

"These new data are encouraging and reinforce our belief that the Moderna COVID-19 Vaccine should remain protective against newly detected variants," Stéphane Bancel, Moderna's chief executive officer, said in a statement. "These findings highlight the importance of continuing to vaccinate populations with an effective primary series vaccine."

The company also said it is developing a booster candidate: a 50-50 mix of its currently authorized COVID-19 vaccine and another messenger RNA vaccine it has developed.

The delta variant is spreading fast

The delta variant is the fast-moving form of the coronavirus that is now found in 96 countries, including the United States.

Last week, Dr. Anthony Fauci of the National Institutes of Health said the delta variant is "currently the greatest threat in the U.S. to our attempt to eliminate COVID-19," noting that the proportion of infections being caused by the variant is doubling every two weeks.

The delta variant is now infecting at least 1 out of every 5 people who get the virus in the United States. In some sections of the country, the variant is already far more common, particularly in parts of the Midwest and West. At its current pace, the delta variant is expected to be the dominant virus in the U.S. within weeks.

Dr. Maria Van Kerkhove, an infectious disease expert at the World Health Organization, called the delta variant "incredibly transmissible."

"These viruses are becoming more fit. The virus is evolving, and this is natural," she told NPR's Morning Edition. "It's more transmissible than the alpha variant, so we need to just do all we can to prevent as many infections as we can and do what we can do to reduce the spread."

This content is from Southern California Public Radio. View the original story at SCPR.org.

Halima Aden attends the premiere of Netflix's Travis Scott: Look Mom I Can Fly at Barker Hangar on Aug. 27, 2019, in Santa Monica, Calif.; Credit: Rich Fury/Getty Images

For Halima Aden, the decision to walk away from a career as the world's first hijab-wearing supermodel was fairly clear cut. She's felt used for so long, she says — by the modeling industry and by UNICEF, the organization she was photographed by as a child in a refugee camp in Kenya and later served as an ambassador for.

Aden has been featured on the covers of Vogue, Elle and Allure magazines. And she walked the runway for Rihanna's Fenty Beauty and Kanye West's Yeezy.

She tells Morning Edition host Rachel Martin she wanted to be a role model for young girls while being true to herself, but she wasn't accomplishing either. Modeling, she realized, was in "direct conflict" with who she is.

"I'm not a cover girl, I'm Halima from Kakuma," she says. "I want to be the reason why girls have confidence within themselves, not the reason for their insecurity."

Aden was raised in the Kakuma refugee camp in northwestern Kenya. She and her family moved to Minnesota in 2004 when she was 7.

It was there her journey as a model began, competing for Miss Minnesota USA in 2016, seeking a scholarship. She finished in the semifinals, and says from there, modeling "fell from the sky" into her lap.

Interview Highlights

You saw [modeling] not just as a chance to wear gorgeous clothes and to have your photo in magazines but also as a way to help people.

Growing up in America, not seeing representation, not seeing anybody who dressed like me look like me, it did make me feel like, wow, what's wrong with me, you know? And I'm sure if I had if I would have had representation growing up, I would have been so much more confident to wear my hijab, to be myself, to be authentic. But to be that person, to grow up and be on the cover of magazines, I've covered everything from Vogue to Allure, some of the biggest publications in fashion. And yet I still couldn't relate personally to my own image because that's not who I really am. That's not how I really dress. That's not how my hijab really looks. And, you know, fashion, it can be a very creative field, and I completely appreciate that. But my hijab was just getting spread so thin that I knew I had to give it all away, give it up. I'm not a cover girl. I am Halima from Kakuma. I want to be the reason why girls have confidence within themselves, not the reason for their insecurity.

When you say your hijab was being kind of styled out of existence, what passed for a hijab as you were walking down those runways?

Everything. Oh, my goodness. I had jeans at one point on my head as a hijab. I had Gucci pants styled as a turban. It just didn't even make sense, and I felt so far removed from the image itself.

During the pandemic you decided to walk away from fashion and UNICEF. Was it a complicated decision?

I'll be honest with you, the feelings that I've had towards the fashion industry and UNICEF, it was just multiplying as the years went on, so it was just festering. You know, because the fashion industry is very known to use these young girls and boys while their young, age 14 to like 24, I think is the average career of a model. And then they just replace them and move on to a newer model. And same with UNICEF. They've been photographing me and using me since the time I was a baby in a refugee camp. I remember getting those headshots taken and it made me feel, it's very dehumanizing. And so I wanted to show UNICEF, too. How does it feel to be used? It's not a good feeling. And so let's stop using people.

What are you going to do [next]?

For me right now, I don't know what's next. And that's OK. That's OK, because I'm young and I have time to figure it out. And I'm grateful. I'm grateful to the people that I've met. I'm grateful to the agents that I worked with. I'm grateful for the experiences I was able to have these last four years. But at the same time, I just am also grateful that I don't have to do that anymore because it was in direct conflict with who I am as an individual, as a human being.

This content is from Southern California Public Radio. View the original story at SCPR.org.

Microsoft-owned OpenAI has announced the general availability of its latest text-generating model GPT-4, through its API.

The emerging science of gene drives has the potential to address environmental and public health challenges, but gene-drive modified organisms are not ready to be released into the environment and require more research in laboratories and highly controlled field trials, says a new report from the National Academies of Sciences, Engineering, and Medicine.

A series of educational modules has been developed by the National Academies of Sciences, Engineering, and Medicine to help students in professional schools – law, public policy, medicine, journalism, and business – understand science and its role in decision making.

A new report from the National Academies of Sciences, Engineering, and Medicine provides a blueprint and eight overarching strategies for improving health care for the approximately 100,000 people in the United States living with sickle cell disease (SCD).

New models for studying the human brain — human neural organoids, transplants, and chimeras — show promise for advancing understanding of the brain and laying the groundwork for new therapeutic approaches to brain diseases that have so far proved hard to treat, says a new report from the National Academies of Sciences, Engineering, and Medicine.

For people who use wheelchairs, air travel comes with many hardships. A new report assesses the feasibility of securing travelers’ personal motorized wheelchairs in the cabin of an airplane as well as the safety and other considerations that must be analyzed.

To modernize the consumer price index — the most widely used measure of inflation in the U.S. — the Bureau of Labor Statistics should accelerate its use of new sources of data and develop price indexes based on different income levels, says a new report.

ESET researchers detected multiple, widespread phishing campaigns targeting SMBs in Poland during May 2024, distributing various malware families

Jiro's Pick this week is dark mode plot by Natan.Do you work in dark mode? If you do, you need to take a look at this entry by Natan, especially if you make presentations using the dark theme. As you... read more >>

Crucial for CIOs and CISOs to stay informed and proactive in the face of the evolving threats, reveals a study made exclusively available to ETCISO.

Meta announced the LLaMA in February this year in several sizes (7B, 13B, 33B, and 65B parameters) so it can be used by a range of users and companies. At I/O 2023, Google also talked about multiple LLMs that are suited to companies of different sizes.

Artificial intelligence (AI) based foundations models such as Meta's Llama 2 and OpenAI's GPT-4 are low on transparency, according to a global report.

WIPOTEC-OCS recently debuted a groundbreaking multi-function metal detection-checkweigher-vision module.

Wooster Products' StairMaster safety renovation treads provide sure footing on interior and exterior stairs and landings.

The ingredient aims to help producers amplify tomato flavor in response to shortages.

Penford Corp.'s PenPlus 2140 pre-gelatinized, modified potato starch is recommended for use in tortillas and baked goods.

Georgia-based HRS Heat Exchangers has been awarded the American 3-A Sanitary Standards approval for two of its key heat exchanger models for food and beverage use.

The design is intended to offer bakery customers faster installation.

Process equipment manufacturer Gericke USA, Somerset, NJ, has introduced the Turbo Compact Mixing (TCM) module.

The Turbo Compact Mixing (TCM) module from process equipment manufacturer Gericke USA, Somerset, NJ, meets ATEX requirements for operation in hazardous environments. 

KPM Analytics has announced three new instrument configurations for its Unity Scientific SpectraStar product line.

CitruSweet, ThauSweet bring lingering sweetness without the need to mask afternotes.

The ingredient is intended to provide producers with a natural-tasting sugar alternative.

HANTEMP Controls has unveiled a new line of stainless steel control valves & modules for pressure, temperature, and liquid control.