bluuebunny/crossref_metadata_2025_split huggingface dataset:
Infant body composition at 6 and 24 months: what are the driving factors?
Authors: Santos Ina S. , Costa Caroline S. , Hills Andrew P. , Ariff Shabina , Wickramasinghe V. Pujitha , Norris Shane , Murphy-Alford Alexia J. , Slater Christine , Lucas Nishani , Nyati Lukhanyo H. , Kurpad Anura V. , Ahuja Kiran D. K. , Kuriyan Rebecca ,   Multi-center Infant Body Composition Reference Study- MIBCRS, Nyati Lukhanyo , Ahmad Tanvir , Beckett Jeffrey M. , Bielemann Renata M. , Byrne Nuala M. , Charania Laila , Christian Michele P. , Divya Priscilla J. , Hanley Anne , Herath Manoja P. , Ismail Leila C. , Jayasinghe Sisitha , Lanerolle Pulani , Loechl Cornelia , Moktar Najat , Senerath Upul , Soofi Sajid , Street Steven J. , Valle Neiva C. J. , Yameen Ayesha 
Published: August 2023

Abstract
Background/Objective
Available evidence on infant body composition is limited. This study aimed to investigate factors associated with body composition at 6 and 24 months.

Subjects/Methods
Multicenter study with data from a 0 to 6-mo cohort (Australia, India and South Africa) and a 3 to 24-mo cohort (Brazil, Pakistan, South Africa, and Sri Lanka). For the 0–6-mo cohort, body composition was assessed by air-displacement plethysmography (ADP) and for the 3–24-month cohort by the deuterium dilution (DD) technique. Fat mass (FM), fat-free mass (FFM), FM index (FMI), and FFM index (FFMI) were calculated. Independent variables comprised the Gini index of the country, maternal and infant characteristics, and breastfeeding pattern at 3 months. For the 3–24-mo cohort, breastfeeding, and minimum dietary diversity (MDD) at 12 months were also included. Crude and adjusted analyses stratified by sex were conducted by multilevel modelling using mixed models.

Results
At 6 months, every 1 kg increase in birth weight was associated with an increase of 0.716 kg in FFM and 0.582 kg/m2 in FFMI in girls, whereas in boys, the increase was of 0.277 kg in FFM. At 24 months, compared to those weaned before 12 months, girls still breastfed at 12 months presented a decrease of 0.225 kg in FM, 0.645 kg in FFM and 0.459 kg/m2 in FFMI, and in boys the decreases were of 0.467 kg in FM, 0.603 kg in FFM and 0.628 kg/m2 in FFMI.

Conclusion
Birth weight and breastfeeding are independent predictors of body composition in early life, irrespective of sex.
High-throughput characterization of HLA-E-presented CD94/NKG2x ligands reveals peptides which modulate NK cell activation
Authors: Huisman Brooke D. , Guan Ning , Rückert Timo , Garner Lee , Singh Nishant K. , McMichael Andrew J. , Gillespie Geraldine M. , Romagnani Chiara , Birnbaum Michael E. 
Published: August 2023

AbstractHLA-E is a non-classical class I MHC protein involved in innate and adaptive immune recognition. While recent studies have shown HLA-E can present diverse peptides to NK cells and T cells, the HLA-E repertoire recognized by CD94/NKG2x has remained poorly defined, with only a limited number of peptide ligands identified. Here we screen a yeast-displayed peptide library in the context of HLA-E to identify 500 high-confidence unique peptides that bind both HLA-E and CD94/NKG2A or CD94/NKG2C. Utilizing the sequences identified via yeast display selections, we train prediction algorithms and identify human and cytomegalovirus (CMV) proteome-derived, HLA-E-presented peptides capable of binding and signaling through both CD94/NKG2A and CD94/NKG2C. In addition, we identify peptides which selectively activate NKG2C+ NK cells. Taken together, characterization of the HLA-E-binding peptide repertoire and identification of NK activity-modulating peptides present opportunities for studies of NK cell regulation in health and disease, in addition to vaccine and therapeutic design.
A machine-learning approach to human ex vivo lung perfusion predicts transplantation outcomes and promotes organ utilization
Authors: Sage Andrew T. , Donahoe Laura L. , Shamandy Alaa A. , Mousavi S. Hossein , Chao Bonnie T. , Zhou Xuanzi , Valero Jerome , Balachandran Sharaniyaa , Ali Aadil , Martinu Tereza , Tomlinson George , Del Sorbo Lorenzo , Yeung Jonathan C. , Liu Mingyao , Cypel Marcelo , Wang Bo , Keshavjee Shaf 
Published: August 2023

AbstractEx vivo lung perfusion (EVLP) is a data-intensive platform used for the assessment of isolated lungs outside the body for transplantation; however, the integration of artificial intelligence to rapidly interpret the large constellation of clinical data generated during ex vivo assessment remains an unmet need. We developed a machine-learning model, termed InsighTx, to predict post-transplant outcomes using n = 725 EVLP cases. InsighTx model AUROC (area under the receiver operating characteristic curve) was 79 ± 3%, 75 ± 4%, and 85 ± 3% in training and independent test datasets, respectively. Excellent performance was observed in predicting unsuitable lungs for transplantation (AUROC: 90 ± 4%) and transplants with good outcomes (AUROC: 80 ± 4%). In a retrospective and blinded implementation study by EVLP specialists at our institution, InsighTx increased the likelihood of transplanting suitable donor lungs [odds ratio=13; 95% CI:4-45] and decreased the likelihood of transplanting unsuitable donor lungs [odds ratio=0.4; 95%CI:0.16–0.98]. Herein, we provide strong rationale for the adoption of machine-learning algorithms to optimize EVLP assessments and show that InsighTx could potentially lead to a safe increase in transplantation rates.
Hybridization of short-range and long-range charge transfer excited states in multiple resonance emitter
Authors: Lee Ha Lim , Kang Jihoon , Lim Junseop , Kim Seung Chan , Jeon Soon Ok , Lee Jun Yeob 
Published: August 2023

AbstractMultiple resonance (MR) thermally activated delayed fluorescence emitters have been actively studied as pure blue dopants for organic light-emitting diodes (OLEDs) because of excellent color purity and high efficiency. However, the reported MR emitter, 2,5,13,16-tetra-tert-butylindolo[3,2,1-jk]indolo[1′,2′,3′:1,7]indolo[2,3-b]carbazole (tDIDCz) based on bis-fused indolocarbazole framework could not demonstrate efficient triplet-to-singlet spin crossover. In this work, we report two isomeric MR emitters designed to promote triplet exciton harvesting by reconstructing the electronic structure of tDIDCz. To manage excited states, strong electron donors were introduced at the 2,5-/1,6-position of tDIDCz. As a result, 2,5-positions managed tDIDCz shows long-range charge transfer characteristics while preserving the MR nature. Quantum chemical calculation demonstrates direct spin-orbit coupling by long-range charge transfer and spin-vibronic coupling assisted reverse intersystem crossing by short-range charge transfer simultaneously contribute to triplet-to-singlet spin crossover. Consequently, high performance blue OLED recorded a high external quantum efficiency of 30.8% at a color coordinate of (0.13, 0.13).
Over-coupled resonator for broadband surface enhanced infrared absorption (SEIRA)
Authors: Paggi Laura , Fabas Alice , El Ouazzani Hasnaa , Hugonin Jean-Paul , Fayard Nikos , Bardou Nathalie , Dupuis Christophe , Greffet Jean-Jacques , Bouchon Patrick 
Published: August 2023

AbstractDetection of molecules is a key issue for many applications. Surface enhanced infrared absorption (SEIRA) uses arrays of resonant nanoantennas with good quality factors which can be used to locally enhance the illumination of molecules. The technique has proved to be an effective tool to detect small amount of material. However, nanoresonators can detect molecules on a narrow bandwidth so that a set of resonators is necessary to identify a molecule fingerprint. Here, we introduce an alternative paradigm and use low quality factor resonators with large radiative losses (over-coupled resonators). The bandwidth enables to detect all absorption lines between 5 and 10 μm, reproducing the molecular absorption spectrum. Counterintuitively, despite a lower quality factor, the system sensitivity is improved and we report a reflectivity variation as large as one percent per nanometer of molecular layer of PMMA. This paves the way to specific identification of molecules. We illustrate the potential of the technique with the detection of the explosive precursor 2,4-dinitrotoluene (DNT). There is a fair agreement with electromagnetic simulations and we also introduce an analytic model of the SEIRA signal obtained in the over-coupling regime.
Origin and arrangement of actin filaments for gliding motility in apicomplexan parasites revealed by cryo-electron tomography
Authors: Martinez Matthew , Mageswaran Shrawan Kumar , Guérin Amandine , Chen William David , Thompson Cameron Parker , Chavin Sabine , Soldati-Favre Dominique , Striepen Boris , Chang Yi-Wei 
Published: August 2023

AbstractThe phylum Apicomplexa comprises important eukaryotic parasites that invade host tissues and cells using a unique mechanism of gliding motility. Gliding is powered by actomyosin motors that translocate host-attached surface adhesins along the parasite cell body. Actin filaments (F-actin) generated by Formin1 play a central role in this critical parasitic activity. However, their subcellular origin, path and ultrastructural arrangement are poorly understood. Here we used cryo-electron tomography to image motile Cryptosporidium parvum sporozoites and reveal the cellular architecture of F-actin at nanometer-scale resolution. We demonstrate that F-actin nucleates at the apically positioned preconoidal rings and is channeled into the pellicular space between the parasite plasma membrane and the inner membrane complex in a conoid extrusion-dependent manner. Within the pellicular space, filaments on the inner membrane complex surface appear to guide the apico-basal flux of F-actin. F-actin concordantly accumulates at the basal end of the parasite. Finally, analyzing a Formin1-depleted Toxoplasma gondii mutant pinpoints the upper preconoidal ring as the conserved nucleation hub for F-actin in Cryptosporidium and Toxoplasma. Together, we provide an ultrastructural model for the life cycle of F-actin for apicomplexan gliding motility.
Orbital-symmetry effects on magnetic exchange in open-shell nanographenes
Authors: Du Qingyang , Su Xuelei , Liu Yufeng , Jiang Yashi , Li Can , Yan KaKing , Ortiz Ricardo , Frederiksen Thomas , Wang Shiyong , Yu Ping 
Published: August 2023

AbstractOpen-shell nanographenes appear as promising candidates for future applications in spintronics and quantum technologies. A critical aspect to realize this potential is to design and control the magnetic exchange. Here, we reveal the effects of frontier orbital symmetries on the magnetic coupling in diradical nanographenes through scanning probe microscope measurements and different levels of theoretical calculations. In these open-shell nanographenes, the exchange energy exhibits a remarkable variation between 20 and 160 meV. Theoretical calculations reveal that frontier orbital symmetries play a key role in affecting the magnetic coupling on such a large scale. Moreover, a triradical nanographene is demonstrated for investigating the magnetic interaction among three unpaired electrons with unequal magnetic exchange, in agreement with Heisenberg spin model calculations. Our results provide insights into both theoretical design and experimental realization of nanographene materials with different exchange interactions through tuning the orbital symmetry, potentially useful for realizing magnetically operable graphene-based nanomaterials.
Bone marrow adiposity modulation after long duration spaceflight in astronauts
Authors: Liu Tammy , Melkus Gerd , Ramsay Tim , Sheikh Adnan , Laneuville Odette , Trudel Guy 
Published: August 2023

AbstractSpace travel requires metabolic adaptations from multiple systems. While vital to bone and blood production, human bone marrow adipose (BMA) tissue modulation in space is unknown. Here we show significant downregulation of the lumbar vertebrae BMA in 14 astronauts, 41 days after landing from six months’ missions on the International Space Station. Spectral analyses indicated depletion of marrow adipose reserves. We then demonstrate enhanced erythropoiesis temporally related to low BMA. Next, we demonstrated systemic and then, local lumbar vertebrae bone anabolism temporally related to low BMA. These support the hypothesis that BMA is a preferential local energy source supplying the hypermetabolic bone marrow postflight, leading to its downregulation. A late postflight upregulation abolished the lower BMA of female astronauts and BMA modulation amplitude was higher in younger astronauts. The study design in the extreme environment of space can limit these conclusions. BMA modulation in astronauts can help explain observations on Earth.
Searching for ductile superconducting Heusler X2YZ compounds
Authors: Hoffmann Noah , Cerqueira Tiago F. T. , Borlido Pedro , Sanna Antonio , Schmidt Jonathan , Marques Miguel A. L. 
Published: August 2023

AbstractHeusler compounds attract a great deal of attention from researchers thanks to a wealth of interesting properties, among which is superconductivity. Here we perform an extensive study of the superconducting and elastic properties of the cubic (full-)Heusler family using a mixture of ab initio methods, as well as interpretable and predictive machine-learning models. By analyzing the statistical distributions of these properties and comparing them to anti-perovskites, we recognize universal behaviors that should be common to all conventional superconductors while others turn out to be specific to the material family. In total, we discover a total of eight hypothetical materials with critical temperatures above 10 K to be compared with the current record of Tc = 4.7 K in this family. Furthermore, we expect most of these materials to be highly ductile, making them potential candidates for the manufacture of wires and tapes for superconducting magnets.
Design of refractory multi-principal-element alloys for high-temperature applications
Authors: Ouyang Gaoyuan , Singh Prashant , Su Ranran , Johnson Duane D. , Kramer Matthew J. , Perepezko John H. , Senkov Oleg N. , Miracle Daniel , Cui Jun 
Published: August 2023

AbstractRefractory multi-principal-element alloys (RMPEAs) exhibit high specific strength at elevated temperatures (T). However, current RMPEAs lack a balance of room-temperature (RT) ductility, high-T strength, and high-T creep resistance. Using density-functional theory methods, we scanned composition space using four criteria: (1) formation energies for operational stability: $$-150\le {E}_{{\rm {f}}}$$

−
150
≤

E

f

≤ +70 meV per atom; (2) higher strength found via interstitial electron density with Young’s moduli E > 250 GPa; (3) inverse Pugh ratio for ductility: G/B < 0.57; and (4) high melting points: Tm > 2500 °C. Using rapid bulk alloy synthesis and characterization, we validated theory and down-selected promising alloy compositions and discovered Mo72.3W12.8Ta10.0Ti2.5Zr2.5 having well-balanced RT and high-T mechanical properties. This alloy has comparable high-T compressive strength to well-known MoNbTaW but is more ductile and more creep resistant. It is also superior to a commercial Mo-based refractory alloy and a nickel-based superalloy (Haynes-282) with improved high-T tensile strength and creep resistance.
Predicting corrosion inhibition efficiencies of small organic molecules using data-driven techniques
Authors: Li Xuejiao , Vaghefinazari Bahram , Würger Tim , Lamaka Sviatlana V. , Zheludkevich Mikhail L. , Feiler Christian 
Published: August 2023

AbstractSelecting effective corrosion inhibitors from the vast chemical space is not a trivial task, as it is essentially infinite. Fortunately, machine learning techniques have shown great potential in generating shortlists of inhibitor candidates prior to large-scale experimental testing. In this work, we used the corrosion responses of 58 small organic molecules on the magnesium alloy AZ91 and utilized molecular descriptors derived from their geometry and density functional theory calculations to encode their molecular information. Statistical methods were applied to select the most relevant features to the target property for support vector regression and kernel ridge regression models, respectively, to predict the behavior of untested compounds. The performance of the two supervised learning approaches were compared and the robustness of the data-driven models were assessed by experimental blind testing.
A Strep A vaccine global demand and return on investment forecast to inform industry research and development prioritization
Authors: Walkinshaw Donald R. , Wright Meghan E. E. , Williams Marni , Scarapicchia Tanya M. F. , Excler Jean-Louis , Wiley Ryan E. , Mullin Anne E. 
Published: August 2023

AbstractInvestment in Strep A vaccine R&D is disproportionately low relative to the large burden of Strep A diseases globally. This study presents a novel Strep A vaccine global demand and financial forecast model with estimates of potential global demand and associated revenue and profits for a hypothetical Strep A vaccine as well as a net present value (NPV) analysis of return on capital investments required to develop the vaccine. A positive NPV was calculated for a variety of developer scenarios and target populations, including the global rollout of the vaccine in private and public markets by a multinational pharmaceutical corporation and a staged rollout by a developing country vaccine manufacturer for both infant and child populations. The results suggest there is a viable commercial market for a Strep A vaccine. It is hoped that this study will help to inform industry decision-making and drive increased prioritization of, and investment in, Strep A vaccine research and development.
Malonyl-CoA is a conserved endogenous ATP-competitive mTORC1 inhibitor
Authors: Nicastro Raffaele , Brohée Laura , Alba Josephine , Nüchel Julian , Figlia Gianluca , Kipschull Stefanie , Gollwitzer Peter , Romero-Pozuelo Jesus , Fernandes Stephanie A. , Lamprakis Andreas , Vanni Stefano , Teleman Aurelio A. , De Virgilio Claudio , Demetriades Constantinos 
Published: August 2023

AbstractCell growth is regulated by the mammalian/mechanistic target of rapamycin complex 1 (mTORC1), which functions both as a nutrient sensor and a master controller of virtually all biosynthetic pathways. This ensures that cells are metabolically active only when conditions are optimal for growth. Notably, although mTORC1 is known to regulate fatty acid biosynthesis, how and whether the cellular lipid biosynthetic capacity signals back to fine-tune mTORC1 activity remains poorly understood. Here we show that mTORC1 senses the capacity of a cell to synthesise fatty acids by detecting the levels of malonyl-CoA, an intermediate of this biosynthetic pathway. We find that, in both yeast and mammalian cells, this regulation is direct, with malonyl-CoA binding to the mTOR catalytic pocket and acting as a specific ATP-competitive inhibitor. When fatty acid synthase (FASN) is downregulated/inhibited, elevated malonyl-CoA levels are channelled to proximal mTOR molecules that form direct protein–protein interactions with acetyl-CoA carboxylase 1 (ACC1) and FASN. Our findings represent a conserved and unique homeostatic mechanism whereby impaired fatty acid biogenesis leads to reduced mTORC1 activity to coordinately link this metabolic pathway to the overall cellular biosynthetic output. Moreover, they reveal the existence of a physiological metabolite that directly inhibits the activity of a signalling kinase in mammalian cells by competing with ATP for binding.
Superconductivity from a melted insulator in Josephson junction arrays
Authors: Mukhopadhyay S. , Senior J. , Saez-Mollejo J. , Puglia D. , Zemlicka M. , Fink J. M. , Higginbotham A. P. 
Published: August 2023

AbstractArrays of Josephson junctions are governed by a competition between superconductivity and repulsive Coulomb interactions, and are expected to exhibit diverging low-temperature resistance when interactions exceed a critical level. Here we report a study of the transport and microwave response of Josephson arrays with interactions exceeding this level. Contrary to expectations, we observe that the array resistance drops dramatically as the temperature is decreased—reminiscent of superconducting behaviour—and then saturates at low temperature. Applying a magnetic field, we eventually observe a transition to a highly resistive regime. These observations can be understood within a theoretical picture that accounts for the effect of thermal fluctuations on the insulating phase. On the basis of the agreement between experiment and theory, we suggest that apparent superconductivity in our Josephson arrays arises from melting the zero-temperature insulator.
Genome-wide prediction of disease variant effects with a deep protein language model
Authors: Brandes Nadav , Goldman Grant , Wang Charlotte H. , Ye Chun Jimmie , Ntranos Vasilis 
Published: August 2023

AbstractPredicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.
Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets
Authors: Zhao Jing Hua , Stacey David , Eriksson Niclas , Macdonald-Dunlop Erin , Hedman Åsa K. , Kalnapenkis Anette , Enroth Stefan , Cozzetto Domenico , Digby-Bell Jonathan , Marten Jonathan , Folkersen Lasse , Herder Christian , Jonsson Lina , Bergen Sarah E. , Gieger Christian , Needham Elise J. , Surendran Praveen ,   Estonian Biobank Research Team, Metspalu Andres , Milani Lili , Mägi Reedik , Nelis Mari , Hudjašov Georgi , Paul Dirk S. , Polasek Ozren , Thorand Barbara , Grallert Harald , Roden Michael , Võsa Urmo , Esko Tonu , Hayward Caroline , Johansson Åsa , Gyllensten Ulf , Powell Nick , Hansson Oskar , Mattsson-Carlgren Niklas , Joshi Peter K. , Danesh John , Padyukov Leonid , Klareskog Lars , Landén Mikael , Wilson James F. , Siegbahn Agneta , Wallentin Lars , Mälarstig Anders , Butterworth Adam S. , Peters James E. 
Published: August 2023

AbstractCirculating proteins have important functions in inflammation and a broad range of diseases. To identify genetic influences on inflammation-related proteins, we conducted a genome-wide protein quantitative trait locus (pQTL) study of 91 plasma proteins measured using the Olink Target platform in 14,824 participants. We identified 180 pQTLs (59 cis, 121 trans). Integration of pQTL data with eQTL and disease genome-wide association studies provided insight into pathogenesis, implicating lymphotoxin-α in multiple sclerosis. Using Mendelian randomization (MR) to assess causality in disease etiology, we identified both shared and distinct effects of specific proteins across immune-mediated diseases, including directionally discordant effects of CD40 on risk of rheumatoid arthritis versus multiple sclerosis and inflammatory bowel disease. MR implicated CXCL5 in the etiology of ulcerative colitis (UC) and we show elevated gut CXCL5 transcript expression in patients with UC. These results identify targets of existing drugs and provide a powerful resource to facilitate future drug target prioritization.