The effect of sleep on memory consolidation depends on the precise interaction of slow oscillations (SOs), theta bursts, and spindles. Disruption in coupling of these sleep rhythms has been reported for individuals with Alzheimer's disease (AD). However, it is unknown how the sleep rhythms evolve during AD progression and whether disrupted sleep rhythms facilitate cognitive decline in AD. Here, we analyze data of 93 individuals from sleep electroencephalography (EEG), MRI, cerebrospinal fluid (CSF) AD biomarkers, and two-year cognitive assessments among three populations: AD dementia (n = 33), mild cognitive impairment (MCI) due to AD (n = 38), and cognitively normal (CN, n = 22). Our study identifies the evolving pattern of coupled sleep rhythm disruption with advancing cognitive stages in AD. Specifically, the frequency of SO-theta burst coupling and SO-spindle coupling decreases from CN to MCI; SO-theta burst coupling and SO-spindle coupling further misalign from MCI to AD dementia. The APOE ε4 allele and elevated amyloid and tau burden are associated with coupled sleep rhythm disruption. Hippocampal and medial prefrontal cortex atrophy are respectively linked to disruption of SO-theta burst coupling and SO-spindle coupling. Notably, coupled sleep rhythm disruption predicts accelerated cognitive decline over a two-year follow-up period. Our study presents that integrating sleep EEG with CSF and MRI biomarkers enhances the predictive ability for AD progression, which unravels the potential of sleep rhythms as monitoring and interventional targets for AD.

Reducing nonradiative recombination is a main challenge in manufacturing highly efficient optoelectronic devices. Perovskite solar cells (PSCs) typically feature significant nonradiative recombination originating from energetic mismatch at the charge-extracting contact. Here, we widely manipulate the energy offset between the perovskite conduction band minimum (CBM) and the electron transporting state of the fullerene cathode interface layer in p-i-n PSCs by modifying the perovskite surface work function with defect-passivating self-assembled monolayers (SAMs) inducing surface dipoles. It is found that reducing the energy offset for electron extraction at such perovskite/fullerene electron-selective heterointerface from 0.98 to -0.02 eV yields a clear linear improvement in PSC built-in potential, with fill factor, photovoltage and power conversion efficiency all increasing as well. We further demonstrate that the improved photovoltaic performance is attributed to reduced energy offsets between the perovskite CBM and the fullerene electron accepting state, which accelerates electron extraction from perovskite and thus effectively suppresses nonradiative recombination. Moreover, the models of corresponding energy level alignment are proposed to discuss the impacts on PSC performance. Our work highlights the importance of tuning the work function even for defect-passivated perovskite surfaces to achieve barrier-less charge extraction and thus boost PSC performance.

Two-dimensional (2D) phase-transition memristors have demonstrated transformative potential for neuromorphic computing, yet challenges like high power consumption, limited endurance, and crystal damage from external ion intercalation persist. Here, we introduce a novel 2D phase-transition memristor leveraging a paradigm-shifting mechanism by exploiting the ultrafast intrinsic Cu ion migration within CuS. This approach eliminates the need for external ion insertion, significantly reducing crystal damage and enabling exceptional cycling stability with over 400 DC cycles and 500 pulse cycles. The susceptible monoclinic-tetragonal phase-transition induced by intrinsic Cu migration achieves an unprecedented SET power consumption of 1 μW at 100 mV, significantly lower in currently reported phase-transition memristors. To further demonstrate the potential of intrinsic ion migration-induced (IIM) memristor, we simulated an IIM memristor crossbar array for image preprocessing in gesture recognition with a high SSIM value of 0.94, showcasing its potential for scalable neuromorphic hardware. This work establishes a new paradigm in low-power, high-performance phase-transition memristors, advancing their practical application in next-generation computing.

The world has experienced a rapid expansion of human settlements in both urban and rural areas in recent decades, yet the unequal impacts of this construction on global food security remain unclear. In this study, we delineated the global-scale expansion of urban-rural settlements at a fine resolution from 1985 to 2020 and quantified their uneven impacts on food security, focusing on the relationships between settlement types, cropland categories, and disparities in crop production. Our results showed that despite dramatic urbanization, rural settlements still constituted the majority of human settlement areas in 2020. Globally, cropland loss due to the expansion of rural settlements was 1.2 times greater than that caused by urbanization, while the associated yield loss was 1.5 times higher. Notably, urban-rural settlement expansion in Asia accounted for 61% of cropland loss and 64% of yield loss. Moreover, future scenarios predicted that Asia's urban-rural settlement expansion will continue to have the most significant impacts on the loss of cropland and yield throughout the 2030s. These results provide systematic evidence of the unequal impacts of urban-rural settlement construction on global cropland and food security.

The fusion of topology and nonlinearity has led to groundbreaking advancements in complex systems, paving the way for new discoveries and innovative device development. However, the interaction between topological states and self-defocusing nonlinearities in complex systems with multiple topological gaps has not yet been explored. Here we demonstrate two distinct topological edge solitons tuned by photovoltaic nonlinearity in Fe-doped lithium niobate waveguide arrays. By establishing a photonic nontrivial decorated Su-Schrieffer-Heeger lattice with two topological gaps, we reveal the emergence of multiple topological edge solitons derived from linear square-root edge states within these gaps. Interestingly, the bulk photovoltaic effect in Fe-doped lithium niobate crystals can generate an internal electric field that drives the electro-optical effect, enabling real-time dynamic manipulation of topological states. As a result, we experimentally observe the complete self-defocusing nonlinear tuning process of topological states within a system with multiple topological gaps, demonstrating the transitions between localization and delocalization. Our research establishes a novel platform for exploring nonlinear topology and sets the stage for further investigation into other intriguing nonlinear phenomena, offering both theoretical insights and practical applications.

T cells have various subtypes and states with different functions. However, a reference list and automated annotation tool for T cell subtypes and states are lacking, which is critical for analyzing and comparing T cells under various conditions. We constructed the largest human T cell reference, containing 1,348,268 T cells from 35 conditions and 16 tissues. We classified T cells into 33 subtypes and further stratified them into 68 categories according to subtype and state. Based on this reference, we developed a tool named STCAT to automatically annotate T cells from scRNA-seq data by hierarchical models and marker correction. The accuracy of STCAT was 28% higher than that of existing tools validated on six independent datasets, including cancer and healthy samples. Using STCAT, we consistently discovered that CD4 Th17 cells were enriched in late-stage lung cancer patients in multiple datasets, whereas MAIT cells were prevalent in milder-stage COVID-19 patients. We also confirmed a decrease in Treg cytotoxicity in post-treatment ovarian cancer. Systematic landscape analyses of CD4 and CD8 T cell references revealed that CD4 Treg cells were enriched in tumor samples and that CD8 naive-related cells were abundant in healthy individuals. Finally, we deposited all the T cell references and annotations into a TCellAtlas (https://guolab.wchscu.cn/TCellAtlas) database, which allows users to browse T cell expression profiles and analyze customized scRNA-seq data by STCAT. In conclusion, comprehensive human T cell subtypes and states reference, automated annotation tool, and database will greatly facilitate research on T cell immunity and tumor immunology.

An amplitude analysis of the D(2460)→Dππ transition is performed simultaneously in B→DDππ, B→D¯Dππ, and B→DDππ decays. The study is based on a data sample of proton-proton collisions recorded with the LHCb detector at centre-of-mass energies of s=7,8, and 13TeV, corresponding to a total integrated luminosity of 9fb. A clear double-peak structure is observed in the m(ππ) spectrum of the D(2460)→Dππ decay. The data can be described either with a model including f500,f980, and f(1270) resonances, in which the contributions of f(980) and f(1270) are unexpectedly large, or with a model including f(500), a doubly charged open-charm tetraquark state T and its isospin partner T. If the former is considered implausible, the T states are observed with high significance, and the data are consistent with isospin symmetry. When imposing isospin constraints between the two T states, their mass and width are determined to be (2327±13±13) MeV and (96±16) MeV, respectively, where the first uncertainty is statistical and the second is systematic. The mass is slightly below the DK threshold, and a spin-parity of 0 is favoured with high significance.