Real-space visualization of a defect-mediated charge density wave transition.

We study the coupled charge density wave (CDW) and insulator-to-metal transitions in the 2D quantum material 1T-TaS2. By applying in situ cryogenic 4D scanning transmission electron microscopy with in situ electrical resistance measurements, we directly visualize the CDW transition and establish that the transition is mediated by basal dislocations (stacking solitons). We find that dislocations can both nucleate and pin the transition and locally alter the transition temperature Tc by nearly ~75 K. This finding was enabled by the application of unsupervised machine learning to cluster five-dimensional, terabyte scale datasets, which demonstrate a one-to-one correlation between resistance-a global property-and local CDW domain-dislocation dynamics, thereby linking the material microstructure to device properties. This work represents a major step toward defect-engineering of quantum materials, which will become increasingly important as we aim to utilize such materials in real devices.

Machine learning in electronic-quantum-matter imaging experiments.

For centuries, the scientific discovery process has been based on systematic human observation and analysis of natural phenomena1. Today, however, automated instrumentation and large-scale data acquisition are generating datasets of such large volume and complexity as to defy conventional scientific methodology. Radically different scientific approaches are needed, and machine learning (ML) shows great promise for research fields such as materials science2-5. Given the success of ML in the analysis of synthetic data representing electronic quantum matter (EQM)6-16, the next challenge is to apply this approach to experimental data-for example, to the arrays of complex electronic-structure images17 obtained from atomic-scale visualization of EQM. Here we report the development and training of a suite of artificial neural networks (ANNs) designed to recognize different types of order hidden in such EQM image arrays. These ANNs are used to analyse an archive of experimentally derived EQM image arrays from carrier-doped copper oxide Mott insulators. In these noisy and complex data, the ANNs discover the existence of a lattice-commensurate, four-unit-cell periodic, translational-symmetry-breaking EQM state. Further, the ANNs determine that this state is unidirectional, revealing a coincident nematic EQM state. Strong-coupling theories of electronic liquid crystals18,19 are consistent with these observations.

Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffraction.

The information content of crystalline materials becomes astronomical when collective electronic behavior and their fluctuations are taken into account. In the past decade, improvements in source brightness and detector technology at modern X-ray facilities have allowed a dramatically increased fraction of this information to be captured. Now, the primary challenge is to understand and discover scientific principles from big datasets when a comprehensive analysis is beyond human reach. We report the development of an unsupervised machine learning approach, X-ray diffraction (XRD) temperature clustering (X-TEC), that can automatically extract charge density wave order parameters and detect intraunit cell ordering and its fluctuations from a series of high-volume X-ray diffraction measurements taken at multiple temperatures. We benchmark X-TEC with diffraction data on a quasi-skutterudite family of materials, (CaxSr[Formula: see text])3Rh4Sn13, where a quantum critical point is observed as a function of Ca concentration. We apply X-TEC to XRD data on the pyrochlore metal, Cd2Re2O7, to investigate its two much-debated structural phase transitions and uncover the Goldstone mode accompanying them. We demonstrate how unprecedented atomic-scale knowledge can be gained when human researchers connect the X-TEC results to physical principles. Specifically, we extract from the X-TEC-revealed selection rules that the Cd and Re displacements are approximately equal in amplitude but out of phase. This discovery reveals a previously unknown involvement of [Formula: see text] Re, supporting the idea of an electronic origin to the structural order. Our approach can radically transform XRD experiments by allowing in operando data analysis and enabling researchers to refine experiments by discovering interesting regions of phase space on the fly.

Emerging functions of circular RNA in aging.

Circular RNA (circRNA) is a closed, single-stranded transcript widely detected in eukaryotes. Recent studies indicate that the levels of circRNAs change with age in various tissues in multiple species, ranging from nematodes to mammals. Here we discuss the functional roles of circRNAs in animal aging and longevity. We review studies regarding the differential expression of circRNAs that contributes to cellular senescence and the pathogenesis of aging-associated diseases. We explore the features of aging-associated circRNAs by discussing their potential as biomarkers of aging, tissue specificity, physiological roles, action mechanisms, and evolutionarily conserved characteristics. Our review provides insights into current progress in circRNA research and their significant functions in the aging process.

Quantum Melting of Generalized Wigner Crystals in Transition Metal Dichalcogenide Moiré Systems.

The generalized Wigner crystal (GWC) is a novel quantum phase of matter driven by further-range interaction at fractional fillings of a lattice. The role of further-range interaction as the driver for the incompressible state is akin to the Wigner crystal. On the other hand, the significant role of commensurate filling is akin to the Mott insulator. Recent progress in simulator platforms presents unprecedented opportunities to investigate quantum melting in the strongly interacting regime through synergy between theory and experiments. However, the earlier theory literature presents diverging predictions. We study the quantum freezing of GWC through large-scale density matrix renormalization group simulations of a triangular lattice extended Hubbard model. We find a single first-order phase transition between the Fermi liquid and the sqrt[3]×sqrt[3] GWC state. The GWC state shows long-range antiferromagnetic 120° Néel order. Our results present the simplest answers to the question of the quantum phase transition into the GWC phase and the properties of the GWC phase.

Effect of topical bromfenac on intraretinal cystoid lesion in simultaneous cataract and idiopathic epiretinal membrane surgery.

PURPOSE: To investigate the effect of topical nonsteroidal anti-inflammatory drugs (NSAIDs,) bromfenac on the intraretinal cystic lesions (IRC) when performing simultaneous cataract and idiopathic epiretinal membrane (iERM) surgery. METHODS: This study included patients with iERM who had been followed up for 6 months after vitrectomy, membrane removal, and concurrent cataract surgery. Eyes were treated with topical bromfenac or not. The baseline fluorescein angiography (FA) was obtained to assess the microvascular leakage (ML). Structural changes of macula, including IRC and central macular thickness (CMT) were assessed using optical coherence tomography (OCT). The main outcome measures were changes in IRCs and best-corrected visual acuity (BCVA) regarding FA findings. RESULTS: One hundred eighteen eyes were included. IRC and ML were observed in 51 eyes (43.2%) and 63 eyes (53.4%), respectively. The IRC did not show any association with the ML. Of total, 29 eyes (24.6%) were treated with topical bromfenac (Group A). Compared to Group B, topical bromfenac did not show beneficial effects in aspect of preventions for the newly developed IRC and treatment for pre-existed IRC. Whether the ML existed or not, topical bromfenac did not show any different effect on the changes in BCVA and IRC. CONCLUSION: When performing simultaneous cataract and ERM surgery, topical NSAIDs, bromfenac did not show beneficial effects on the preventions and treatment of IRC in both eyes with and without the ML.

Spatially clustered patterns of suicide mortality rates in South Korea: a geographically weighted regression analysis.

BACKGROUND: Suicide mortality remains a global health concern, and community characteristics affect regional variations in suicide. This study investigated spatially clustered patterns of suicide mortality rates in South Korea and evaluated the impact of community factors on suicide. METHODS: Suicide mortality rates were estimated by sex, age group, and district, using the 2021 Cause of Death Statistics in South Korea from the MicroData Integrated Service. Community-determinant data for 2021 or the nearest year were collected from the Korean Statistical Information Service. The spatial autocorrelation of suicide by sex and age was examined based on Global Moran's I index. Geographically weighted regression (GWR) was used to discern the influence of community determinants on suicide. RESULTS: Suicide mortality rates were significantly higher among men (40.64 per 100,000) and adults over the age of 65 years (43.18 per 100,000). The male suicide mortality rates exhibited strong spatial dependence, as indicated by a high global Moran's I with p < 0.001, highlighting the importance of conducting spatial analysis. In the GWR model calibration, a subset of the community's age structure, single-person household composition, access to mental healthcare centers, and unmet medical needs were selected to explain male suicide mortality. These determinants disproportionately increased the risk of male suicide, varying by region. The GWR coefficients of each variable vary widely across 249 districts: aging index (Q1:0.06-Q3:0.46), single-person households (Q1:0.22-Q3:0.35), psychiatric clinics (Q1:-0.20-Q3:-0.01), and unmet medical needs (Q1:0.09-Q3:0.14). CONCLUSIONS: Community cultural and structural factors exacerbate regional disparities in suicide among men. The influencing factors exhibit differential effects and significance depending on the community, highlighting the need for efficient resource allocation for suicide. A regionally tailored approach is crucial for the effective control of the community's mental health management system.

Domain-Dependent Surface Adhesion in Twisted Few-Layer Graphene: Platform for Moiré-Assisted Chemistry.

Twisted van der Waals multilayers are widely regarded as a rich platform to access novel electronic phases thanks to the multiple degrees of freedom available for controlling their electronic and chemical properties. Here, we propose that the stacking domains that form naturally due to the relative twist between successive layers act as an additional "knob" for controlling the behavior of these systems and report the emergence and engineering of stacking domain-dependent surface chemistry in twisted few-layer graphene. Using mid-infrared near-field optical microscopy and atomic force microscopy, we observe a selective adhesion of metallic nanoparticles and liquid water at the domains with rhombohedral stacking configurations of minimally twisted double bi- and trilayer graphene. Furthermore, we demonstrate that the manipulation of nanoparticles located at certain stacking domains can locally reconfigure the moiré superlattice in their vicinity at the micrometer scale. Our findings establish a new approach to controlling moiré-assisted chemistry and nanoengineering.

Fractionalization in Fractional Correlated Insulating States at n±1/3 Filled Twisted Bilayer Graphene.

Fractionalization without time-reversal symmetry breaking is a long-sought-after goal in the study of correlated phenomena. The earlier proposal of correlated insulating states at n±1/3 filling in twisted bilayer graphene and recent experimental observations of insulating states at those fillings strongly suggest that moiré graphene systems provide a new platform to realize time-reversal symmetric fractionalized states. However, the nature of fractional excitations and the effect of quantum fluctuation on the fractional correlated insulating states are unknown. We show that excitations of the fractional correlated insulator phases in the strong coupling limit carry fractional charges and exhibit fractonic restricted mobility. Upon introduction of quantum fluctuations, the resonance of "lemniscate" structured operators drives the system into quantum lemniscate liquid (QLL) or quantum lemniscate solid (QLS). We find an emergent U(1)×U(1) 1-form symmetry unifies distinct motions of the fractionally charged excitations in the strong coupling limit and in the QLL phase, while providing a new mechanism for fractional excitations in two dimensions. We predict emergent Luttinger liquid behavior upon dilute doping in the strong coupling limit due to restricted mobility and discuss implications at a general n±1/3 filling.

Linear resistivity and Sachdev-Ye-Kitaev (SYK) spin liquid behavior in a quantum critical metal with spin-1/2 fermions.

"Strange metals" with resistivity depending linearly on temperature T down to low T have been a long-standing puzzle in condensed matter physics. Here, we consider a lattice model of itinerant spin-[Formula: see text] fermions interacting via onsite Hubbard interaction and random infinite-ranged spin-spin interaction. We show that the quantum critical point associated with the melting of the spin-glass phase by charge fluctuations displays non-Fermi liquid behavior, with local spin dynamics identical to that of the Sachdev-Ye-Kitaev family of models. This extends the quantum spin liquid dynamics previously established in the large-M limit of [Formula: see text] symmetric models to models with physical [Formula: see text] spin-[Formula: see text] electrons. Remarkably, the quantum critical regime also features a Planckian linear-T resistivity associated with a T-linear scattering rate and a frequency dependence of the electronic self-energy consistent with the marginal Fermi liquid phenomenology.

O-GlcNAcylation on LATS2 disrupts the Hippo pathway by inhibiting its activity.

The Hippo pathway controls organ size and tissue homeostasis by regulating cell proliferation and apoptosis. The LATS-mediated negative feedback loop prevents excessive activation of the effectors YAP/TAZ, maintaining homeostasis of the Hippo pathway. YAP and TAZ are hyperactivated in various cancer cells which lead to tumor growth. Aberrantly increased O-GlcNAcylation has recently emerged as a cause of hyperactivation of YAP in cancer cells. However, the mechanism, which induces hyperactivation of TAZ and blocks LATS-mediated negative feedback, remains to be elucidated in cancer cells. This study found that in breast cancer cells, abnormally increased O-GlcNAcylation hyperactivates YAP/TAZ and inhibits LATS2, a direct negative regulator of YAP/TAZ. LATS2 is one of the newly identified O-GlcNAcylated components in the MST-LATS kinase cascade. Here, we found that O-GlcNAcylation at LATS2 Thr436 interrupted its interaction with the MOB1 adaptor protein, which connects MST to LATS2, leading to activation of YAP/TAZ by suppressing LATS2 kinase activity. LATS2 is a core component in the LATS-mediated negative feedback loop. Thus, this study suggests that LATS2 O-GlcNAcylation is deeply involved in tumor growth by playing a critical role in dysregulation of the Hippo pathway in cancer cells.

Quantum Phases of Transition Metal Dichalcogenide Moiré Systems.

Moiré systems provide a rich platform for studies of strong correlation physics. Recent experiments on heterobilayer transition metal dichalcogenide Moiré systems are exciting in that they manifest a relatively simple model system of an extended Hubbard model on a triangular lattice. Inspired by the prospect of the hetero-transition metal dichalcogenide Moiré system's potential as a solid-state-based quantum simulator, we explore the extended Hubbard model on the triangular lattice using the density matrix renormalization group. Specifically, we explore the two-dimensional phase space spanned by the key tuning parameters in the extended Hubbard model, namely, the kinetic energy strength and the further-range Coulomb interaction strengths. We find competition between Fermi fluid, chiral spin liquid, spin density wave, and charge order. In particular, our finding of the optimal further-range interaction for the chiral correlation presents a tantalizing possibility.

Evidence for a vestigial nematic state in the cuprate pseudogap phase.

The CuO2 antiferromagnetic insulator is transformed by hole-doping into an exotic quantum fluid usually referred to as the pseudogap (PG) phase. Its defining characteristic is a strong suppression of the electronic density-of-states D(E) for energies |E| < [Formula: see text], where [Formula: see text] is the PG energy. Unanticipated broken-symmetry phases have been detected by a wide variety of techniques in the PG regime, most significantly a finite-Q density-wave (DW) state and a Q = 0 nematic (NE) state. Sublattice-phase-resolved imaging of electronic structure allows the doping and energy dependence of these distinct broken-symmetry states to be visualized simultaneously. Using this approach, we show that even though their reported ordering temperatures T DW and T NE are unrelated to each other, both the DW and NE states always exhibit their maximum spectral intensity at the same energy, and using independent measurements that this is the PG energy [Formula: see text] Moreover, no new energy-gap opening coincides with the appearance of the DW state (which should theoretically open an energy gap on the Fermi surface), while the observed PG opening coincides with the appearance of the NE state (which should theoretically be incapable of opening a Fermi-surface gap). We demonstrate how this perplexing phenomenology of thermal transitions and energy-gap opening at the breaking of two highly distinct symmetries may be understood as the natural consequence of a vestigial nematic state within the pseudogap phase of Bi2Sr2CaCu2O8.

Upf1 regulates neurite outgrowth and branching by transcriptional and post-transcriptional modulation of Arc.

A large number of neuronal proteins must show correct spatiotemporal localization in order to carry out their critical functions. The mRNA transcript for the somatodendritic protein activity-regulated cytoskeleton-associated protein (Arc; also known as Arg3.1) contains two conserved introns in the 3' untranslated region (UTR), and was proposed to be a natural target for nonsense-mediated mRNA decay (NMD). However, a well-known NMD component Upf1 has differential roles in transcriptional and translational regulation of Arc gene expression. Specifically, Upf1 suppresses Arc transcription by enhancing destabilization of mRNAs encoding various transcription factors, including Mef2a. Upf1 also binds to the Arc 3'UTR, resulting in suppression of translation. Surprisingly, the Arc transcript escapes from Upf1-mediated NMD by binding to Ago2 (also known as miRISC), which blocks NMD and further suppresses Arc mRNA translation. Upf1 knockdown triggered sustained Arc expression, which contributes to Cofilin (also known as Cfl1) hyperphosphorylation and abnormal neuronal outgrowth and branching. Collectively, these data reveal that multiple levels of Upf1-mediated inhibition of Arc gene expression may allow neurons to more effectively respond to changes in neuronal activity.

Strange Metals from Melting Correlated Insulators in Twisted Bilayer Graphene.

Even as the understanding of the mechanism behind correlated insulating states in magic-angle twisted bilayer graphene converges toward various kinds of spontaneous symmetry breaking, the metallic "normal state" above the insulating transition temperature remains mysterious, with its excessively high entropy and linear-in-temperature resistivity. In this Letter, we focus on the effects of fluctuations of the order parameters describing correlated insulating states at integer fillings of the low-energy flat bands on charge transport. Motivated by the observation of heterogeneity in the order-parameter landscape at zero magnetic field in certain samples, we conjecture the existence of frustrating extended-range interactions in an effective Ising model of the order parameters on a triangular lattice. The competition between short-distance ferromagnetic interactions and frustrating extended-range antiferromagnetic interactions leads to an emergent length scale that forms stripy mesoscale domains above the ordering transition. The gapless fluctuations of these heterogeneous configurations are found to be responsible for the linear-in-temperature resistivity as well as the enhanced low-temperature entropy. Our insights link experimentally observed linear-in-temperature resistivity and enhanced entropy to the strength of frustration or, equivalently, to the emergence of mesoscopic length scales characterizing order-parameter domains.

Identification of Non-Fermi Liquid Physics in a Quantum Critical Metal via Quantum Loop Topography.

Non-Fermi liquid physics is ubiquitous in strongly correlated metals, manifesting itself in anomalous transport properties, such as a T-linear resistivity in experiments. However, its theoretical understanding in terms of microscopic models is lacking, despite decades of conceptual work and attempted numerical simulations. Here we demonstrate that a combination of sign-problem-free quantum Monte Carlo sampling and quantum loop topography, a physics-inspired machine-learning approach, can map out the emergence of non-Fermi liquid physics in the vicinity of a quantum critical point (QCP) with little prior knowledge. Using only three parameter points for training the underlying neural network, we are able to robustly identify a stable non-Fermi liquid regime tracing the fans of metallic QCPs at the onset of both spin-density wave and nematic order. In particular, we establish for the first time that a spin-density wave QCP commands a wide fan of non-Fermi liquid region that funnels into the quantum critical point. Our study thereby provides an important proof-of-principle example that new physics can be detected via unbiased machine-learning approaches.

Modulation Doping via a Two-Dimensional Atomic Crystalline Acceptor.

Two-dimensional nanoelectronics, plasmonics, and emergent phases require clean and local charge control, calling for layered, crystalline acceptors or donors. Our Raman, photovoltage, and electrical conductance measurements combined with ab initio calculations establish the large work function and narrow bands of α-RuCl3 enable modulation doping of exfoliated single and bilayer graphene, chemical vapor deposition grown graphene and WSe2, and molecular beam epitaxy grown EuS. We further demonstrate proof of principle photovoltage devices, control via twist angle, and charge transfer through hexagonal boron nitride. Short-ranged lateral doping (≤65 nm) and high homogeneity are achieved in proximate materials with a single layer of α-RuCl3. This leads to the best-reported monolayer graphene mobilities (4900 cm2/(V s)) at these high hole densities (3 × 1013 cm-2) and yields larger charge transfer to bilayer graphene (6 × 1013 cm-2).

Ab Initio Mismatched Interface Theory of Graphene on α-RuCl_{3}: Doping and Magnetism.

Recent developments in twisted and lattice-mismatched bilayers have revealed a rich phase space of van der Waals systems and generated excitement. Among these systems are heterobilayers, which can offer new opportunities to control van der Waals systems with strong in plane correlations such as spin-orbit-assisted Mott insulator α-RuCl_{3}. Nevertheless, a theoretical ab initio framework for mismatched heterobilayers without even approximate periodicity is sorely lacking. We propose a general strategy for calculating electronic properties of such systems, mismatched interface theory (MINT), and apply it to the graphene/α-RuCl_{3} (GR/α-RuCl_{3}) heterostructure. Using MINT, we predict uniform doping of 4.77% from graphene to α-RuCl_{3} and magnetic interactions in α-RuCl_{3} to shift the system toward the Kitaev point. Hence, we demonstrate that MINT can guide targeted materialization of desired model systems and discuss recent experiments on GR/α-RuCl_{3} heterostructures.

Transient activation of AMPK preceding left ventricular pressure overload reduces adverse remodeling and preserves left ventricular function.

Coordinated changes in signaling pathways and gene expression in hearts subjected to prolonged stress maintain cardiac function. Loss of steroid receptor coactivator-2 (SRC-2) results in a reversal to the fetal gene program and disrupts the response to pressure overload, accompanied by prominent effects on metabolism and growth signaling, including increased AMPK activation. We proposed that early metabolic stress driven by AMPK activation induces contractile dysfunction in mice lacking SRC-2. We used 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to activate AMPK transiently before transverse aortic constriction (TAC) in wild-type and cardiomyocyte-specific SRC-2 knockout (CKO) animals. In contrast to AMPK activities during stress, in unstressed hearts, AICAR induced a mild activation of Akt signaling, and, in SRC-2-CKO mice, partially relieved an NAD+ deficiency and increased antioxidant signaling. These molecular changes translated to a mild hypertrophic response to TAC with decreased maladaptive remodeling, including markedly decreased fibrosis. Additionally, preactivation of AMPK in SRC-2-CKO mice was accompanied by a dramatic improvement in cardiac function compared with saline-treated SRC-2-CKO mice. Our results show that altered molecular signaling before stress onset has extended effects on sustained cardiac stress responses, and prestress modulation of transient growth and metabolism pathways may control those effects.-Nam, D. H., Kim, E., Benham, A., Park, H.-K., Soibam, B., Taffet, G. E., Kaelber, J. T., Suh, J. H., Taegtmeyer, H., Entman, M. L., Reineke, E. L. Transient activation of AMPK preceding left ventricular pressure overload reduces adverse remodeling and preserves left ventricular function.

Cationic amino acid transporter PQLC2 is a potential therapeutic target in gastric cancer.

Tumor cells overexpress amino acid transporters to meet the increased demand for amino acids. PQ loop repeat-containing (PQLC)2 is a cationic amino acid transporter that might be involved in cancer progression. Here, we show that upregulation of PQLC2 is critical to gastric cancer (GC) development in vitro and in vivo. Both PQLC2 mRNA and protein were overexpressed in GC tissues, especially of the diffuse type. Overexpression of PQLC2 promoted cell growth, anchorage independence, and tumor formation in nude mice. This was due to activation of MEK/ERK1/2 and PI3K/AKT signaling. Conversely, PQLC2 knockdown caused growth arrest and cell death of cancer cells and suppressed tumor growth in a mouse xenograft model. These results suggest that targeting PQLC2 is an effective strategy for GC treatment.