bluuebunny/crossref_metadata_2025 huggingface dataset:
Bax Inhibitor-1 preserves pancreatic β-cell proteostasis by limiting proinsulin misfolding and programmed cell death
Authors: Blanc Marina , Habbouche Lama , Xiao Peng , Lebeaupin Cynthia , Janona Marion , Vaillant Nathalie , Irondelle Marie , Gilleron Jérôme , Murcy Florent , Rousseau Déborah , Luci Carmelo , Barouillet Thibault , Marchetti Sandrine , Lacas-Gervais Sandra , Yvan-Charvet Laurent , Gual Philippe , Cardozo Alessandra K. , Bailly-Maitre Béatrice
Published: May 2024

The prevalence of diabetes steadily increases worldwide mirroring the prevalence of obesity. Endoplasmic reticulum (ER) stress is activated in diabetes and contributes to β-cell dysfunction and apoptosis through the activation of a terminal unfolded protein response (UPR). Our results uncover a new role for Bax Inhibitor-One (BI-1), a negative regulator of inositol-requiring enzyme 1 (IRE1α) in preserving β-cell health against terminal UPR-induced apoptosis and pyroptosis in the context of supraphysiological loads of insulin production. BI-1-deficient mice experience a decline in endocrine pancreatic function in physiological and pathophysiological conditions, namely obesity induced by high-fat diet (HFD). We observed early-onset diabetes characterized by hyperglycemia, reduced serum insulin levels, β-cell loss, increased pancreatic lipases and pro-inflammatory cytokines, and the progression of metabolic dysfunction. Pancreatic section analysis revealed that BI-1 deletion overburdens unfolded proinsulin in the ER of β-cells, confirmed by ultrastructural signs of ER stress with overwhelmed IRE1α endoribonuclease (RNase) activity in freshly isolated islets. ER stress led to β-cell dysfunction and islet loss, due to an increase in immature proinsulin granules and defects in insulin crystallization with the presence of Rod-like granules. These results correlated with the induction of autophagy, ER phagy, and crinophagy quality control mechanisms, likely to alleviate the atypical accumulation of misfolded proinsulin in the ER. In fine, BI-1 in β-cells limited IRE1α RNase activity from triggering programmed β-cell death through apoptosis and pyroptosis (caspase-1, IL-1β) via NLRP3 inflammasome activation and metabolic dysfunction. Pharmaceutical IRE1α inhibition with STF-083010 reversed β-cell failure and normalized the metabolic phenotype. These results uncover a new protective role for BI-1 in pancreatic β-cell physiology as a stress integrator to modulate the UPR triggered by accumulating unfolded proinsulin in the ER, as well as autophagy and programmed cell death, with consequences on β-cell function and insulin secretion.
The NTE domain of PTENα/β promotes cancer progression by interacting with WDR5 via its SSSRRSS motif
Authors: Huang Xiaolei , Zhang Cheng , Shang Xinci , Chen Yichang , Xiao Qin , Wei Zhengguo , Wang Guanghui , Zhen Xuechu , Xu Guoqiang , Min Jinrong , Shen Shaoming , Liu Yanli
Published: May 2024

PTENα/β, two variants of PTEN, play a key role in promoting tumor growth by interacting with WDR5 through their N-terminal extensions (NTEs). This interaction facilitates the recruitment of the SET1/MLL methyltransferase complex, resulting in histone H3K4 trimethylation and upregulation of oncogenes such as NOTCH3, which in turn promotes tumor growth. However, the molecular mechanism underlying this interaction has remained elusive. In this study, we determined the first crystal structure of PTENα-NTE in complex with WDR5, which reveals that PTENα utilizes a unique binding motif of a sequence SSSRRSS found in the NTE domain of PTENα/β to specifically bind to the WIN site of WDR5. Disruption of this interaction significantly impedes cell proliferation and tumor growth, highlighting the potential of the WIN site inhibitors of WDR5 as a way of therapeutic intervention of the PTENα/β associated cancers. These findings not only shed light on the important role of the PTENα/β-WDR5 interaction in carcinogenesis, but also present a promising avenue for developing cancer treatments that target this pathway.
Disentangling oncogenic amplicons in esophageal adenocarcinoma
Authors: Ng Alvin Wei Tian , McClurg Dylan Peter , Wesley Ben , Zamani Shahriar A. , Black Emily , Miremadi Ahmad , Giger Olivier , Hoopen Rogier ten , Devonshire Ginny , Redmond Aisling M. , Grehan Nicola , Jammula Sriganesh , Blasko Adrienn , Li Xiaodun , Aparicio Samuel , Tavaré Simon ,   Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) Consortium, Edwards Paul A. W. , Grehan Nicola , Nutzinger Barbara , Loreno Christine , Abbas Sujath , Freeman Adam , Smyth Elizabeth C. , O’Donovan Maria , Miremadi Ahmad , Malhotra Shalini , Tripathi Monika , Cheah Calvin , Coles Hannah , Millington Curtis , Eldridge Matthew , Secrier Maria , Jammula Sriganesh , Davies Jim , Crichton Charles , Carroll Nick , Hardwick Richard H. , Safranek Peter , Hindmarsh Andrew , Sujendran Vijayendran , Hayes Stephen J. , Ang Yeng , Sharrocks Andrew , Preston Shaun R. , Bagwan Izhar , Save Vicki , Skipworth Richard J. E. , Hupp Ted R. , O’Neill J. Robert , Tucker Olga , Beggs Andrew , Taniere Philippe , Puig Sonia , Contino Gianmarco , Underwood Timothy J. , Walker Robert C. , Grace Ben L. , Lagergren Jesper , Gossage James , Davies Andrew , Chang Fuju , Mahadeva Ula , Goh Vicky , Ciccarelli Francesca D. , Sanders Grant , Berrisford Richard , Chan David , Cheong Ed , Kumar Bhaskar , Sreedharan L. , Parsons Simon L. , Soomro Irshad , Kaye Philip , Saunders John , Lovat Laurence , Haidry Rehan , Scott Michael , Sothi Sharmila , Lishman Suzy , Hanna George B. , Peters Christopher J. , Moorthy Krishna , Grabowska Anna , Turkington Richard , McManus Damian , Coleman Helen , Petty Russell D. , Bartlet Freddie , Nowicki-Osuch Karol , Fitzgerald Rebecca C.
Published: May 2024

Esophageal adenocarcinoma is a prominent example of cancer characterized by frequent amplifications in oncogenes. However, the mechanisms leading to amplicons that involve breakage-fusion-bridge cycles and extrachromosomal DNA are poorly understood. Here, we use 710 esophageal adenocarcinoma cases with matched samples and patient-derived organoids to disentangle complex amplicons and their associated mechanisms. Short-read sequencing identifies ERBB2, MYC, MDM2, and HMGA2 as the most frequent oncogenes amplified in extrachromosomal DNAs. We resolve complex extrachromosomal DNA and breakage-fusion-bridge cycles amplicons by integrating of de-novo assemblies and DNA methylation in nine long-read sequenced cases. Complex amplicons shared between precancerous biopsy and late-stage tumor, an enrichment of putative enhancer elements and mobile element insertions are potential drivers of complex amplicons’ origin. We find that patient-derived organoids recapitulate extrachromosomal DNA observed in the primary tumors and single-cell DNA sequencing capture extrachromosomal DNA-driven clonal dynamics across passages. Prospectively, long-read and single-cell DNA sequencing technologies can lead to better prediction of clonal evolution in esophageal adenocarcinoma.
Dynamin1 long- and short-tail isoforms exploit distinct recruitment and spatial patterns to form endocytic nanoclusters
Authors: Jiang Anmin , Kudo Kye , Gormal Rachel S. , Ellis Sevannah , Guo Sikao , Wallis Tristan P. , Longfield Shanley F. , Robinson Phillip J. , Johnson Margaret E. , Joensuu Merja , Meunier Frédéric A.
Published: May 2024

Endocytosis requires a coordinated framework of molecular interactions that ultimately lead to the fission of nascent endocytic structures. How cytosolic proteins such as dynamin concentrate at discrete sites that are sparsely distributed across the plasma membrane remains poorly understood. Two dynamin-1 major splice variants differ by the length of their C-terminal proline-rich region (short-tail and long-tail). Using sptPALM in PC12 cells, neurons and MEF cells, we demonstrate that short-tail dynamin-1 isoforms ab and bb display an activity-dependent recruitment to the membrane, promptly followed by their concentration into nanoclusters. These nanoclusters are sensitive to both Calcineurin and dynamin GTPase inhibitors, and are larger, denser, and more numerous than that of long-tail isoform aa. Spatiotemporal modelling confirms that dynamin-1 isoforms perform distinct search patterns and undergo dimensional reduction to generate endocytic nanoclusters, with short-tail isoforms more robustly exploiting lateral trapping in the generation of nanoclusters compared to the long-tail isoform.
Premature skewing of T cell receptor clonality and delayed memory expansion in HIV-exposed infants
Authors: Dzanibe Sonwabile , Wilk Aaron J. , Canny Susan , Ranganath Thanmayi , Alinde Berenice , Rubelt Florian , Huang Huang , Davis Mark M. , Holmes Susan P. , Jaspan Heather B. , Blish Catherine A. , Gray Clive M.
Published: May 2024

While preventing vertical HIV transmission has been very successful, HIV-exposed uninfected infants (iHEU) experience an elevated risk to infections compared to HIV-unexposed and uninfected infants (iHUU). Here we present a longitudinal multimodal analysis of infant immune ontogeny that highlights the impact of HIV/ARV exposure. Using mass cytometry, we show alterations in T cell memory differentiation between iHEU and iHUU being significant from week 15 of life. The altered memory T cell differentiation in iHEU was preceded by lower TCR Vβ clonotypic diversity and linked to TCR clonal depletion within the naïve T cell compartment. Compared to iHUU, iHEU had elevated CD56loCD16loPerforin+CD38+CD45RA+FcεRIγ+ NK cells at 1 month postpartum and whose abundance pre-vaccination were predictive of vaccine-induced pertussis and rotavirus antibody responses post 3 months of life. Collectively, HIV/ARV exposure disrupted the trajectory of innate and adaptive immunity from birth which may underlie relative vulnerability to infections in iHEU.
Dynamics of growing carbon nanotube interfaces probed by machine learning-enabled molecular simulations
Authors: Hedman Daniel , McLean Ben , Bichara Christophe , Maruyama Shigeo , Larsson J. Andreas , Ding Feng
Published: May 2024

Carbon nanotubes (CNTs), hollow cylinders of carbon, hold great promise for advanced technologies, provided their structure remains uniform throughout their length. Their growth takes place at high temperatures across a tube-catalyst interface. Structural defects formed during growth alter CNT properties. These defects are believed to form and heal at the tube-catalyst interface but an understanding of these mechanisms at the atomic-level is lacking. Here we present DeepCNT-22, a machine learning force field (MLFF) to drive molecular dynamics simulations through which we unveil the mechanisms of CNT formation, from nucleation to growth including defect formation and healing. We find the tube-catalyst interface to be highly dynamic, with large fluctuations in the chiral structure of the CNT-edge. This does not support continuous spiral growth as a general mechanism, instead, at these growth conditions, the growing tube edge exhibits significant configurational entropy. We demonstrate that defects form stochastically at the tube-catalyst interface, but under low growth rates and high temperatures, these heal before becoming incorporated in the tube wall, allowing CNTs to grow defect-free to seemingly unlimited lengths. These insights, not readily available through experiments, demonstrate the remarkable power of MLFF-driven simulations and fill long-standing gaps in our understanding of CNT growth mechanisms.
De novo motor learning creates structure in neural activity that shapes adaptation
Authors: Chang Joanna C. , Perich Matthew G. , Miller Lee E. , Gallego Juan A. , Clopath Claudia
Published: May 2024

Animals can quickly adapt learned movements to external perturbations, and their existing motor repertoire likely influences their ease of adaptation. Long-term learning causes lasting changes in neural connectivity, which shapes the activity patterns that can be produced during adaptation. Here, we examined how a neural population’s existing activity patterns, acquired through de novo learning, affect subsequent adaptation by modeling motor cortical neural population dynamics with recurrent neural networks. We trained networks on different motor repertoires comprising varying numbers of movements, which they acquired following various learning experiences. Networks with multiple movements had more constrained and robust dynamics, which were associated with more defined neural ‘structure’—organization in the available population activity patterns. This structure facilitated adaptation, but only when the changes imposed by the perturbation were congruent with the organization of the inputs and the structure in neural activity acquired during de novo learning. These results highlight trade-offs in skill acquisition and demonstrate how different learning experiences can shape the geometrical properties of neural population activity and subsequent adaptation.
Sustainable upcycling of mixed spent cathodes to a high-voltage polyanionic cathode material
Authors: Ji Guanjun , Tang Di , Wang Junxiong , Liang Zheng , Ji Haocheng , Ma Jun , Zhuang Zhaofeng , Liu Song , Zhou Guangmin , Cheng Hui-Ming
Published: May 2024

Sustainable battery recycling is essential for achieving resource conservation and alleviating environmental issues. Many open/closed-loop strategies for critical metal recycling or direct recovery aim at a single component, and the reuse of mixed cathode materials is a significant challenge. To address this barrier, here we propose an upcycling strategy for spent LiFePO4 and Mn-rich cathodes by structural design and transition metal replacement, for which uses a green deep eutectic solvent to regenerate a high-voltage polyanionic cathode material. This process ensures the complete recycling of all the elements in mixed cathodes and the deep eutectic solvent can be reused. The regenerated LiFe0.5Mn0.5PO4 has an increased mean voltage (3.68 V versus Li/Li+) and energy density (559 Wh kg–1) compared with a commercial LiFePO4 (3.38 V and 524 Wh kg–1). The proposed upcycling strategy can expand at a gram-grade scale and was also applicable for LiFe0.5Mn0.5PO4 recovery, thus achieving a closed-loop recycling between the mixed spent cathodes and the next generation cathode materials. Techno-economic analysis shows that this strategy has potentially high environmental and economic benefits, while providing a sustainable approach for the value-added utilization of waste battery materials.
Atomically dispersed asymmetric cobalt electrocatalyst for efficient hydrogen peroxide production in neutral media
Authors: Liu Longxiang , Kang Liqun , Feng Jianrui , Hopkinson David G. , Allen Christopher S. , Tan Yeshu , Gu Hao , Mikulska Iuliia , Celorrio Veronica , Gianolio Diego , Wang Tianlei , Zhang Liquan , Li Kaiqi , Zhang Jichao , Zhu Jiexin , Held Georg , Ferrer Pilar , Grinter David , Callison June , Wilding Martin , Chen Sining , Parkin Ivan , He Guanjie
Published: May 2024

Electrochemical hydrogen peroxide (H2O2) production (EHPP) via a two-electron oxygen reduction reaction (2e- ORR) provides a promising alternative to replace the energy-intensive anthraquinone process. M-N-C electrocatalysts, which consist of atomically dispersed transition metals and nitrogen-doped carbon, have demonstrated considerable EHPP efficiency. However, their full potential, particularly regarding the correlation between structural configurations and performances in neutral media, remains underexplored. Herein, a series of ultralow metal-loading M-N-C electrocatalysts are synthesized and investigated for the EHPP process in the neutral electrolyte. CoNCB material with the asymmetric Co-C/N/O configuration exhibits the highest EHPP activity and selectivity among various as-prepared M-N-C electrocatalyst, with an outstanding mass activity (6.1 × 105 A gCo−1 at 0.5 V vs. RHE), and a high practical H2O2 production rate (4.72 mol gcatalyst−1 h−1 cm−2). Compared with the popularly recognized square-planar symmetric Co-N4 configuration, the superiority of asymmetric Co-C/N/O configurations is elucidated by X-ray absorption fine structure spectroscopy analysis and computational studies.
Double-negative B cells and DNASE1L3 colocalise with microbiota in gut-associated lymphoid tissue
Authors: Montorsi Lucia , Pitcher Michael J. , Zhao Yuan , Dionisi Chiara , Demonti Alicia , Tull Thomas J. , Dhami Pawan , Ellis Richard J. , Bishop Cynthia , Sanderson Jeremy D. , Jain Sahil , D’Cruz David , Gibbons Deena L. , Winkler Thomas H. , Bemark Mats , Ciccarelli Francesca D. , Spencer Jo
Published: May 2024

Intestinal homeostasis is maintained by the response of gut-associated lymphoid tissue to bacteria transported across the follicle associated epithelium into the subepithelial dome. The initial response to antigens and how bacteria are handled is incompletely understood. By iterative application of spatial transcriptomics and multiplexed single-cell technologies, we identify that the double negative 2 subset of B cells, previously associated with autoimmune diseases, is present in the subepithelial dome in health. We show that in this location double negative 2 B cells interact with dendritic cells co-expressing the lupus autoantigens DNASE1L3 and C1q and microbicides. We observe that in humans, but not in mice, dendritic cells expressing DNASE1L3 are associated with sampled bacteria but not DNA derived from apoptotic cells. We propose that fundamental features of autoimmune diseases are microbiota-associated, interacting components of normal intestinal immunity.
A HIMU-like component in Mariana Convergent Margin magma sources during initial arc rifting revealed by melt inclusions
Authors: Li Xiaohui , Ishizuka Osamu , Stern Robert J. , Li Sanzhong , Lai Zhiqing , Somerville Ian , Suo Yanhui , Chen Long , Yu Hongxia
Published: May 2024

Compositions of island arc and back-arc basin basalts are often used to trace the recycling of subducted materials. However, the contribution of subducted components to the mantle source during initial arc rifting before back-arc basin spreading is not yet well constrained. The northernmost Mariana arc is ideal for studying this because the transition from rifting to back-arc spreading is happening here. Here we report major and trace element and Pb isotopic compositions of olivine-hosted melt inclusions from lavas erupted during initial rifting at 24°N (NSP-24) and compare them with those in active arc front at 21°N and mature back-arc basin at 18°N. NSP-24 high-K melt inclusions have highly radiogenic Pb compositions and are close to those of the HIMU end-member, suggesting the presence of this component in the magma source. The HIMU-like component may be stored in the over-riding plate and released into arc magma with rifting. HIMU-type seamounts may be subducted elsewhere beneath the Mariana arc, but obvious HIMU-type components appear only in the initial stages of arc rifting due to the low melting degree and being consumed during the process of back-arc spreading.
Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types
Authors: Kang Junho , Lee Jun Hyeong , Cha Hongui , An Jinhyeon , Kwon Joonha , Lee Seongwoo , Kim Seongryong , Baykan Mert Yakup , Kim So Yeon , An Dohyeon , Kwon Ah-Young , An Hee Jung , Lee Se-Hoon , Choi Jung Kyoon , Park Jong-Eun
Published: May 2024

The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8887 TCGA, and 1261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n = 1261) including our lung cancer cohort (n = 497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.
Electric-field tunable Type-I to Type-II band alignment transition in MoSe2/WS2 heterobilayers
Authors: Kistner-Morris Jed , Shi Ao , Liu Erfu , Arp Trevor , Farahmand Farima , Taniguchi Takashi , Watanabe Kenji , Aji Vivek , Lui Chun Hung , Gabor Nathaniel
Published: May 2024

Semiconductor heterojunctions are ubiquitous components of modern electronics. Their properties depend crucially on the band alignment at the interface, which may exhibit straddling gap (type-I), staggered gap (type-II) or broken gap (type-III). The distinct characteristics and applications associated with each alignment make it highly desirable to switch between them within a single material. Here we demonstrate an electrically tunable transition between type-I and type-II band alignments in MoSe2/WS2 heterobilayers by investigating their luminescence and photocurrent characteristics. In their intrinsic state, these heterobilayers exhibit a type-I band alignment, resulting in the dominant intralayer exciton luminescence from MoSe2. However, the application of a strong interlayer electric field induces a transition to a type-II band alignment, leading to pronounced interlayer exciton luminescence. Furthermore, the formation of the interlayer exciton state traps free carriers at the interface, leading to the suppression of interlayer photocurrent and highly nonlinear photocurrent-voltage characteristics. This breakthrough in electrical band alignment control, interlayer exciton manipulation, and carrier trapping heralds a new era of versatile optical and (opto)electronic devices composed of van der Waals heterostructures.
Ammonium-derived nitrous oxide is a global source in streams
Authors: Wang Shanyun , Lan Bangrui , Yu Longbin , Xiao Manyi , Jiang Liping , Qin Yu , Jin Yucheng , Zhou Yuting , Armanbek Gawhar , Ma Jingchen , Wang Manting , Jetten Mike S. M. , Tian Hanqin , Zhu Guibing , Zhu Yong-Guan
Published: May 2024

Global riverine nitrous oxide (N2O) emissions have increased more than 4-fold in the last century. It has been estimated that the hyporheic zones in small streams alone may contribute approximately 85% of these N2O emissions. However, the mechanisms and pathways controlling hyporheic N2O production in stream ecosystems remain unknown. Here, we report that ammonia-derived pathways, rather than the nitrate-derived pathways, are the dominant hyporheic N2O sources (69.6 ± 2.1%) in agricultural streams around the world. The N2O fluxes are mainly in positive correlation with ammonia. The potential N2O metabolic pathways of metagenome-assembled genomes (MAGs) provides evidence that nitrifying bacteria contain greater abundances of N2O production-related genes than denitrifying bacteria. Taken together, this study highlights the importance of mitigating agriculturally derived ammonium in low-order agricultural streams in controlling N2O emissions. Global models of riverine ecosystems need to better represent ammonia-derived pathways for accurately estimating and predicting riverine N2O emissions.
mTORC1 regulates cell survival under glucose starvation through 4EBP1/2-mediated translational reprogramming of fatty acid metabolism
Authors: Levy Tal , Voeltzke Kai , Hruby Laura , Alasad Khawla , Bas Zuelal , Snaebjörnsson Marteinn , Marciano Ran , Scharov Katerina , Planque Mélanie , Vriens Kim , Christen Stefan , Funk Cornelius M. , Hassiepen Christina , Kahler Alisa , Heider Beate , Picard Daniel , Lim Jonathan K. M. , Stefanski Anja , Bendrin Katja , Vargas-Toscano Andres , Kahlert Ulf D. , Stühler Kai , Remke Marc , Elkabets Moshe , Grünewald Thomas G. P. , Reichert Andreas S. , Fendt Sarah-Maria , Schulze Almut , Reifenberger Guido , Rotblat Barak , Leprivier Gabriel
Published: May 2024

Energetic stress compels cells to evolve adaptive mechanisms to adjust their metabolism. Inhibition of mTOR kinase complex 1 (mTORC1) is essential for cell survival during glucose starvation. How mTORC1 controls cell viability during glucose starvation is not well understood. Here we show that the mTORC1 effectors eukaryotic initiation factor 4E binding proteins 1/2 (4EBP1/2) confer protection to mammalian cells and budding yeast under glucose starvation. Mechanistically, 4EBP1/2 promote NADPH homeostasis by preventing NADPH-consuming fatty acid synthesis via translational repression of Acetyl-CoA Carboxylase 1 (ACC1), thereby mitigating oxidative stress. This has important relevance for cancer, as oncogene-transformed cells and glioma cells exploit the 4EBP1/2 regulation of ACC1 expression and redox balance to combat energetic stress, thereby supporting transformation and tumorigenicity in vitro and in vivo. Clinically, high EIF4EBP1 expression is associated with poor outcomes in several cancer types. Our data reveal that the mTORC1-4EBP1/2 axis provokes a metabolic switch essential for survival during glucose starvation which is exploited by transformed and tumor cells.
Enzyme-assisted high throughput sequencing of an expanded genetic alphabet at single base resolution
Authors: Wang Bang , Bradley Kevin M. , Kim Myong-Jung , Laos Roberto , Chen Cen , Gerloff Dietlind L. , Manfio Luran , Yang Zunyi , Benner Steven A.
Published: May 2024

With just four building blocks, low sequence information density, few functional groups, poor control over folding, and difficulties in forming compact folds, natural DNA and RNA have been disappointing platforms from which to evolve receptors, ligands, and catalysts. Accordingly, synthetic biology has created “artificially expanded genetic information systems” (AEGIS) to add nucleotides, functionality, and information density. With the expected improvements seen in AegisBodies and AegisZymes, the task for synthetic biologists shifts to developing for expanded DNA the same analytical tools available to natural DNA. Here we report one of these, an enzyme-assisted sequencing of expanded genetic alphabet (ESEGA) method to sequence six-letter AEGIS DNA. We show how ESEGA analyses this DNA at single base resolution, and applies it to optimized conditions for six-nucleotide PCR, assessing the fidelity of various DNA polymerases, and extending this to AEGIS components with functional groups. This supports the renewed exploitation of expanded DNA alphabets in biotechnology.
Spin-orbit torque manipulation of sub-terahertz magnons in antiferromagnetic α-Fe2O3
Authors: Yang Dongsheng , Kim Taeheon , Lee Kyusup , Xu Chang , Liu Yakun , Wang Fei , Zhao Shishun , Kumar Dushyant , Yang Hyunsoo
Published: May 2024

The ability to electrically manipulate antiferromagnetic magnons, essential for extending the operating speed of spintronic devices into the terahertz regime, remains a major challenge. This is because antiferromagnetic magnetism is challenging to perturb using traditional methods such as magnetic fields. Recent developments in spin-orbit torques have opened a possibility of accessing antiferromagnetic magnetic order parameters and controlling terahertz magnons, which has not been experimentally realised yet. Here, we demonstrate the electrical manipulation of sub-terahertz magnons in the α-Fe2O3/Pt antiferromagnetic heterostructure. By applying the spin-orbit torques in the heterostructure, we can modify the magnon dispersion and decrease the magnon frequency in α-Fe2O3, as detected by time-resolved magneto-optical techniques. We have found that optimal tuning occurs when the Néel vector is perpendicular to the injected spin polarisation. Our results represent a significant step towards the development of electrically tunable terahertz spintronic devices.
Transcription stress at telomeres leads to cytosolic DNA release and paracrine senescence
Authors: Siametis Athanasios , Stratigi Kalliopi , Giamaki Despoina , Chatzinikolaou Georgia , Akalestou-Clocher Alexia , Goulielmaki Evi , Luke Brian , Schumacher Björn , Garinis George A.
Published: May 2024

Transcription stress has been linked to DNA damage -driven aging, yet the underlying mechanism remains unclear. Here, we demonstrate that Tcea1−/− cells, which harbor a TFIIS defect in transcription elongation, exhibit RNAPII stalling at oxidative DNA damage sites, impaired transcription, accumulation of R-loops, telomere uncapping, chromatin bridges, and genome instability, ultimately resulting in cellular senescence. We found that R-loops at telomeres causally contribute to the release of telomeric DNA fragments in the cytoplasm of Tcea1−/− cells and primary cells derived from naturally aged animals triggering a viral-like immune response. TFIIS-defective cells release extracellular vesicles laden with telomeric DNA fragments that target neighboring cells, which consequently undergo cellular senescence. Thus, transcription stress elicits paracrine signals leading to cellular senescence, promoting aging.
Proteome partitioning constraints in long-term laboratory evolution
Authors: Mori Matteo , Patsalo Vadim , Euler Christian , Williamson James R. , Scott Matthew
Published: May 2024

Adaptive laboratory evolution experiments provide a controlled context in which the dynamics of selection and adaptation can be followed in real-time at the single-nucleotide level. And yet this precision introduces hundreds of degrees-of-freedom as genetic changes accrue in parallel lineages over generations. On short timescales, physiological constraints have been leveraged to provide a coarse-grained view of bacterial gene expression characterized by a small set of phenomenological parameters. Here, we ask whether this same framework, operating at a level between genotype and fitness, informs physiological changes that occur on evolutionary timescales. Using a strain adapted to growth in glucose minimal medium, we find that the proteome is substantially remodeled over 40 000 generations. The most striking change is an apparent increase in enzyme efficiency, particularly in the enzymes of lower-glycolysis. We propose that deletion of metabolic flux-sensing regulation early in the adaptation results in increased enzyme saturation and can account for the observed proteome remodeling.
Targeted protein degradation in mycobacteria uncovers antibacterial effects and potentiates antibiotic efficacy
Authors: Won Harim I. , Zinga Samuel , Kandror Olga , Akopian Tatos , Wolf Ian D. , Schweber Jessica T. P. , Schmid Ernst W. , Chao Michael C. , Waldor Maya , Rubin Eric J. , Zhu Junhao
Published: May 2024

Proteolysis-targeting chimeras (PROTACs) represent a new therapeutic modality involving selectively directing disease-causing proteins for degradation through proteolytic systems. Our ability to exploit targeted protein degradation (TPD) for antibiotic development remains nascent due to our limited understanding of which bacterial proteins are amenable to a TPD strategy. Here, we use a genetic system to model chemically-induced proximity and degradation to screen essential proteins in Mycobacterium smegmatis (Msm), a model for the human pathogen M. tuberculosis (Mtb). By integrating experimental screening of 72 protein candidates and machine learning, we find that drug-induced proximity to the bacterial ClpC1P1P2 proteolytic complex leads to the degradation of many endogenous proteins, especially those with disordered termini. Additionally, TPD of essential Msm proteins inhibits bacterial growth and potentiates the effects of existing antimicrobial compounds. Together, our results provide biological principles to select and evaluate attractive targets for future Mtb PROTAC development, as both standalone antibiotics and potentiators of existing antibiotic efficacy.
Deep learning with plasma plume image sequences for anomaly detection and prediction of growth kinetics during pulsed laser deposition
Authors: Harris Sumner B. , Rouleau Christopher M. , Xiao Kai , Vasudevan Rama K.
Published: May 2024

Materials synthesis platforms that are designed for autonomous experimentation are capable of collecting multimodal diagnostic data that can be utilized for feedback to optimize material properties. Pulsed laser deposition (PLD) is emerging as a viable autonomous synthesis tool, and so the need arises to develop machine learning (ML) techniques that are capable of extracting information from in situ diagnostics. Here, we demonstrate that intensified-CCD image sequences of the plasma plume generated during PLD can be used for anomaly detection and the prediction of thin film growth kinetics. We develop multi-output (2 + 1)D convolutional neural network regression models that extract deep features from plume dynamics that not only correlate with the measured chamber pressure and incident laser energy, but more importantly, predict parameters of an auto-catalytic film growth model derived from in situ laser reflectivity experiments. Our results demonstrate how ML with in situ plume diagnostics data in PLD can be utilized to maintain deposition conditions in an optimal regime. Further, the predictive capabilities of plume dynamics on the kinetics of film growth or other film properties prior to deposition provides a means for rapid pre-screening of growth conditions for the non-expert, which promises to accelerate materials optimization with PLD.
Accelerated MRI reconstructions via variational network and feature domain learning
Authors: Giannakopoulos Ilias I. , Muckley Matthew J. , Kim Jesi , Breen Matthew , Johnson Patricia M. , Lui Yvonne W. , Lattanzi Riccardo
Published: May 2024

We introduce three architecture modifications to enhance the performance of the end-to-end (E2E) variational network (VarNet) for undersampled MRI reconstructions. We first implemented the Feature VarNet, which propagates information throughout the cascades of the network in an N-channel feature-space instead of a 2-channel feature-space. Then, we add an attention layer that utilizes the spatial locations of Cartesian undersampling artifacts to further improve performance. Lastly, we combined the Feature and E2E VarNets into the Feature-Image (FI) VarNet, to facilitate cross-domain learning and boost accuracy. Reconstructions were evaluated on the fastMRI dataset using standard metrics and clinical scoring by three neuroradiologists. Feature and FI VarNets outperformed the E2E VarNet for 4$$\times$$
×
, 5$$\times$$
×
and 8$$\times$$
×
Cartesian undersampling in all studied metrics. FI VarNet secured second place in the public fastMRI leaderboard for 4$$\times$$
×
Cartesian undersampling, outperforming all open-source models in the leaderboard. Radiologists rated FI VarNet brain reconstructions with higher quality and sharpness than the E2E VarNet reconstructions. FI VarNet excelled in preserving anatomical details, including blood vessels, whereas E2E VarNet discarded or blurred them in some cases. The proposed FI VarNet enhances the reconstruction quality of undersampled MRI and could enable clinically acceptable reconstructions at higher acceleration factors than currently possible.
Stem cells derived exosomes as biological nano carriers for VCR sulfate for treating breast cancer stem cells
Authors: Farouk Ahmed H. , Aref Ahmed , Fathy Belal A. , Abdallah Ahmed N.
Published: May 2024

Due to vincristine sulfate’s (VCR sulfate) toxicity and non-specific targeting, which might adversely damage healthy cells, its clinical application is restricted. In this study, we loaded VCR sulfate on exosomes generated from mesenchymal stem cells (MSCs) to enhance its targeted distribution. Exosomes are able to deliver molecules to specific cells and tissues and have therapeutic potential. In this study, we isolated exosomes from MSCs, and using probe-sonication approach loaded them with VCR sulfate. Using SRB assay, the cytotoxicity of VCR sulfate-Exo was assessed in T47D breast cancer cells, and the results were contrasted with those of free VCR sulfate. Then We labeled markers (CD44+/CD24−) in the cell line to assess the targeting effectiveness of VCR sulfate-Exo using flow cytometry. Our results showed that the cytotoxicity of VCR sulfate-Exo was nearly the same as that of VCR sulfate. Flow cytometry analysis revealed that VRC sulfate-Exo was more effectively targeted to MSCs than free VCR sulfate. Our study shows that loading VCR sulfate to MSCs-derived exosomes can improve their targeted delivery and lessen their side effects. Additional research is required to determine VCR sulfate-Exo’s in vivo effectiveness and safety and improve the loading and delivery strategies.
A brain machine interface framework for exploring proactive control of smart environments
Authors: Braun Jan-Matthias , Fauth Michael , Berger Michael , Huang Nan-Sheng , Simeoni Ezequiel , Gaeta Eugenio , Rodrigues do Carmo Ricardo , García-Betances Rebeca I. , Arredondo Waldmeyer María Teresa , Gail Alexander , Larsen Jørgen C. , Manoonpong Poramate , Tetzlaff Christian , Wörgötter Florentin
Published: May 2024

Brain machine interfaces (BMIs) can substantially improve the quality of life of elderly or disabled people. However, performing complex action sequences with a BMI system is onerous because it requires issuing commands sequentially. Fundamentally different from this, we have designed a BMI system that reads out mental planning activity and issues commands in a proactive manner. To demonstrate this, we recorded brain activity from freely-moving monkeys performing an instructed task and decoded it with an energy-efficient, small and mobile field-programmable gate array hardware decoder triggering real-time action execution on smart devices. Core of this is an adaptive decoding algorithm that can compensate for the day-by-day neuronal signal fluctuations with minimal re-calibration effort. We show that open-loop planning-ahead control is possible using signals from primary and pre-motor areas leading to significant time-gain in the execution of action sequences. This novel approach provides, thus, a stepping stone towards improved and more humane control of different smart environments with mobile brain machine interfaces.
Production study of Fr, Ra and Ac radioactive ion beams at ISOLDE, CERN
Authors: Jajčišinová E. , Dockx K. , Au M. , Bara S. , Cocolios T. E. , Chrysalidis K. , Farooq-Smith G. J. , Fedorov D. V. , Fedosseev V. N. , Flanagan K. T. , Heines M. , Houngbo D. , Johnson J. D. , Kellerbauer A. , Kraemer S. , Marsh B. A. , Popescu L. , Ramos J. P. , Rothe S. , Seliverstov M. D. , Sels S. , Stegemann S. , Stryjczyk M. , Verelst V.
Published: May 2024

The presented paper discusses the production of radioactive ion beams of francium, radium, and actinium from thick uranium carbide (UC$$_{x}$$

x

) targets at ISOLDE, CERN. This study focuses on the release curves and extractable yields of francium, radium and actinium isotopes. The ion source temperature was varied in order to study the relative contributions of surface and laser ionization to the production of the actinium ion beams. The experimental results are presented in the form of release parameters. Representative extractable yields per $$\mu$$
μ
C are presented for $$^{222-231}$$

222
-
231

Ac, several Ra and Fr isotopes in the mass ranges 214$$\le$$
≤
A$$\le$$
≤
233 and 205$$\le$$
≤
A$$\le$$
≤
231 respectively. The release efficiency for several isotopes of each of the studied elements was calculated by comparing their yields to the estimated in-target production rates modeled by CERN-FLUKA. The maximal extraction efficiency of actinium was calculated to be 2.1(6)% for a combination of surface ionization using a Ta ion source and resonant laser ionization using the two-step 438.58 nm, and 424.69 nm scheme.
Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure
Authors: Chen Junbo , Bayanagari Vara Lakshmi , Chung Sohae , Wang Yao , Lui Yvonne W.
Published: May 2024

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22–37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92–0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.
AI-based predictive approach via FFB propagation in a driven-cavity of Ostwald de-Waele fluid using CFD-ANN and Levenberg–Marquardt
Authors: Refaie Ali Ahmed , Mahmood Rashid , Asghar Atif , Majeed Afraz Hussain , Behiry Mohamed H.
Published: May 2024

The integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques into computational science has ushered in a new era of innovation and efficiency in various fields, with particular significance in computational fluid dynamics (CFD). Several methods based on AI and Machine Learning (ML) have been standardized in many fields of computational science, including computational fluid dynamics (CFD). This study aims to couple CFD with artificial neural networks (ANNs) to predict the fluid forces that arise when a flowing fluid interacts with obstacles installed in the flow domain. The momentum equation elucidating the flow has been simulated by adopting the finite element method (FEM) for a range of rheological and kinematic conditions. Hydrodynamic forces, including pressure drop between the back and front of the obstacle, surface drag, and lift variations, are measured on the outer surface of the cylinder via CFD simulations. This data has subsequently been fed into a Feed-Forward Back (FFB) propagation neural network for the prediction of such forces with completely unknown data. For all cases, higher predictivity is achieved for the drag coefficient (CD) and lift coefficient (CL) since the mean square error (MSE) is within ± 2% and the coefficient of determination (R) is approximately 99% for all the cases. The influence of pertinent parameters like the power law index (n) and Reynolds number (Re) on velocity, pressure, and drag and lift coefficients is also presented for limited cases. Moreover, a significant reduction in computing time has been noticed while applying hybrid CFD-ANN approach as compared with CFD simulations only.
Magnesium implantation as a continuous hydrogen production generator for the treatment of myocardial infarction in rats
Authors: Wang Bin , Pan Shuang , Nie Chaoqun , Zou Rentong , Liu Jiaren , Han Xue , Dong Li , Zhang Jiawen , Yang Xinrui , Yu Mengshu , Fan Bowei , Hong Xiaojian , Yang Wei
Published: May 2024

Molecular hydrogen is an emerging broad-spectrum antioxidant molecule that can be used to treat myocardial infarction (MI). However, with hydrogen inhalation, the concentration that can be reached within target organs is low and the duration of action is short, which makes it difficult to achieve high dose targeted delivery of hydrogen to the heart, seriously limiting the therapeutic potential of hydrogen for MI. As a result of reactions with the internal environment of the body, subcutaneous implantation of magnesium slices leads to continuous endogenous hydrogen production, leading to a higher hydrogen concentration and a longer duration of action in target organs. In this study, we propose magnesium implant-based hydrogen therapy for MI. After subcutaneous implantation of magnesium slices in the dorsum of rats, we measured hydrogen production and efficiency, and evaluated the safety of this approach. Compared with hydrogen inhalation, it significantly improved cardiac function in rats with MI. Magnesium implantation also cleared free radicals that were released as a result of mitochondrial dysfunction, as well as suppressing cardiomyocyte apoptosis.
Mechanisms upholding the persistence of stigma across 100 years of historical text
Authors: Charlesworth Tessa E. S. , Hatzenbuehler Mark L.
Published: May 2024

Today, many social groups face negative stereotypes. Is such negativity a stable feature of society and, if so, what mechanisms maintain stability both within and across group targets? Answering these theoretically and practically important questions requires data on dozens of group stereotypes examined simultaneously over historical and societal scales, which is only possible through recent advances in Natural Language Processing. Across two studies, we use word embeddings from millions of English-language books over 100 years (1900–2000) and extract stereotypes for 58 stigmatized groups. Study 1 examines aggregate, societal-level trends in stereotype negativity by averaging across these groups. Results reveal striking persistence in aggregate negativity (no meaningful slope), suggesting that society maintains a stable level of negative stereotypes. Study 2 introduces and tests a new framework identifying potential mechanisms upholding stereotype negativity over time. We find evidence of two key sources of this aggregate persistence: within-group “reproducibility” (e.g., stereotype negativity can be maintained by using different traits with the same underlying meaning) and across-group “replacement” (e.g., negativity from one group is transferred to other related groups). These findings provide novel historical evidence of mechanisms upholding stigmatization in society and raise new questions regarding the possibility of future stigma change.