Structural insights into the DNA-binding mechanism of BCL11A: The integral role of ZnF6.

The transcription factor BCL11A is a critical regulator of the switch from fetal hemoglobin (HbF: α2γ2) to adult hemoglobin (HbA: α2ß2) during development. BCL11A binds at a cognate recognition site (TGACCA) in the γ-globin gene promoter and represses its expression. DNA-binding is mediated by a triple zinc finger domain, designated ZnF456. Here, we report comprehensive investigation of ZnF456, leveraging X-ray crystallography and NMR to determine the structures in both the presence and absence of DNA. We delve into the dynamics and mode of interaction with DNA. Moreover, we discovered that the last zinc finger of BCL11A (ZnF6) plays a different role compared to ZnF4 and 5, providing a positive entropic contribution to DNA binding and γ-globin gene repression. Comprehending the DNA binding mechanism of BCL11A opens avenues for the strategic, structure-based design of novel therapeutics targeting sickle cell disease and ß-thalassemia.

Soil moisture inversion based on multiple drought indices and RBFNN: A case study of northern Hebei Province.

Drought has a significant impact on crop growth and productivity, highlighting the critical need for precise and timely soil moisture estimation to mitigate agricultural losses. This study focuses on soil moisture retrieval in northern Hebei Province during July 2012, utilizing eight widely employed remote sensing drought indices derived from MODIS satellite data. These indices were cross-referenced with measured soil moisture levels for analysis. Based on their correlation coefficients, a composite remote sensing drought index set comprising six indices was identified. Furthermore, a radial basis function neural network (RBFNN) was employed to estimate soil relative humidity. The accuracy evaluation of the soil moisture estimation model, which integrates multiple remote sensing drought indices and the RBFNN, demonstrated clear superiority over models relying on single drought indices. The model achieved an average estimation accuracy of 87.54 % for soil relative humidity at a depth of 10 cm (SM10) and 87.36 % for a 20 cm depth (SM20). The root mean square errors (RMSE) for the test sets were 0.093 and 0.092, respectively. Validation results for July 2013 indicated that the inversion accurately reflected the actual soil moisture conditions, effectively capturing dynamic moisture changes. These results fully verify the reliability and practicability of the model. These findings introduce a novel approach to local agricultural soil moisture estimation, with significant implications for enhancing agricultural water resource management and decision-making processes.

A Universal Synthesis of Single-Atom Catalysts via Operando Bond Formation Driven by Electricity.

Single-atom catalysts (SACs), featuring highly uniform active sites, tunable coordination environments, and synergistic effects with support, have emerged as one of the most efficient catalysts for various reactions, particularly for electrochemical CO2 reduction (ECR). However, the scalability of SACs is restricted due to the limited choice of available support and problems that emerge when preparing SACs by thermal deposition. Here, an in situ reconstruction method for preparing SACs is developed with a variety of atomic sites, including nickel, cadmium, cobalt, and magnesium. Driven by electricity, different oxygen-containing metal precursors, such as MOF-74 and metal oxides, are directly atomized onto nitrogen-doped carbon (NC) supports, yielding SACs with variable metal active sites and coordination structures. The electrochemical force facilitates the in situ generation of bonds between the metal and the supports without the need for additional complex steps. A series of MNxOy (M denotes metal) SACs on NC have been synthesized and utilized for ECR. Among these, NiNxOy SACs using Ni-MOF-74 as a metal precursor exhibit excellent ECR performance. This universal and general SAC synthesis strategy at room temperature is simpler than most reported synthesis methods to date, providing practical guidance for the design of the next generation of high-performance SACs.

Protein NMR assignment by isotope pattern recognition.

The current standard method for amino acid signal identification in protein NMR spectra is sequential assignment using triple-resonance experiments. Good software and elaborate heuristics exist, but the process remains laboriously manual. Machine learning does help, but its training databases need millions of samples that cover all relevant physics and every kind of instrumental artifact. In this communication, we offer a solution to this problem. We propose polyadic decompositions to store millions of simulated three-dimensional NMR spectra, on-the-fly generation of artifacts during training, a probabilistic way to incorporate prior and posterior information, and integration with the industry standard CcpNmr software framework. The resulting neural nets take [1H,13C] slices of mixed pyruvate-labeled HNCA spectra (different CA signal shapes for different residue types) and return an amino acid probability table. In combination with primary sequence information, backbones of common proteins (GB1, MBP, and INMT) are rapidly assigned from just the HNCA spectrum.

Identification of wheat stripe rust inoculum sources and dispersal routes responsible for initial rust establishment in southern Henan of China.

Wheat stripe rust (yellow rust), caused by Puccinia striiformis f. sp. tritici (Pst), is an important airborne disease worldwide. Pst inoculum strength in southern Henan in winter or early spring is important for spring epidemic in the main autumn-sown wheat-growing regions of China. However, there is limited knowledge about the source and time of initial infection on winter wheat in southern Henan. The first occurrence of wheat stripe rust in southern Henan was recorded annually from 2011-2022, from which we used the backward trajectory approach to infer the likely source of Pst inoculum responsible for the initial disease occurrence. The results suggested that the Pst inoculum responsible for initial rust established in the winter in southern Henan originated from the Gansu Pst oversummering area in China, whereas it originated from the adjacent winter Pst sporulation regions in southern Shaanxi and northwestern Hubei if Pst symptoms were first observed in early spring in southern Henan. Another possible Pst source is southern Hubei where Pst can also sporulate in the winter. Thus, early Pst development in winter in the main wheat production in China (Henan) is likely to be caused by Pst inoculum spread from the oversummering inocula or Pst epidemics in autumn seedlings in Gansu.

Enhancing therapeutic potential: Human adipose-derived mesenchymal stem cells modified with recombinant adeno-associated virus expressing VEGF165 gene for peripheral nerve injury.

This study aimed to investigate the therapeutic potential of human adipose-derived mesenchymal stem cells (hADSCs) modified with recombinant adeno-associated virus (rAAV) carrying the vascular endothelial growth factor 165 (VEGF165) gene in peripheral nerve injury (PNI). The hADSCs were categorized into blank, control (transduced with rAAV control vector), and VEGF165 (transduced with rAAV VEGF165 vector) groups. Subsequently, Schwann cell differentiation was induced, and Schwann cell markers were assessed. The sciatic nerve injury mouse model received injections of phosphate-buffered saline (PBS group), PBS containing hADSCs (hADSCs group), rAAV control vector (control-hADSCs group), or rAAV VEGF165 vector (VEGF165-hADSCs group) into the nerve defect site. Motor function recovery, evaluated through the sciatic function index (SFI), and nerve regeneration, assessed via toluidine blue staining along with scrutiny of Schwann cell markers and neurotrophic factors, were conducted. Modified hADSCs exhibited enhanced Schwann cell differentiation and elevated expression of Schwann cell markers [S100 calcium-binding protein B (S100B), NGF receptor (NGFR), and glial fibrillary acidic protein (GFAP)]. Mice in the VEGF165-hADSCs group demonstrated improved motor function recovery compared to those in the other three groups, accompanied by increased fiber diameter, axon diameter, and myelin thickness, as well as elevated expression of Schwann cell markers (S100B, NGFR, and GFAP) and neurotrophic factors [mature brain-derived neurotrophic factor (BDNF) and glial cell-derived neurotrophic factor (GDNF)] in the distal nerve segment. rAAV-VEGF165 modification enhances hADSC potential in PNI, promoting motor recovery and nerve regeneration. Elevated Schwann cell markers and neurotrophic factors underscore therapy benefits, providing insights for nerve injury strategies.

Finger-Individuating Exoskeleton System with Non-Contact Leader-Follower Control Strategy.

This paper proposes a novel finger-individuating exoskeleton system with a non-contact leader-follower control strategy that effectively combines motion functionality and individual adaptability. Our solution comprises the following two interactive components: the leader side and the follower side. The leader side processes joint angle information from the healthy hand during motion via a Leap Motion Controller as the system input, providing more flexible and active operations owing to the non-contact manner. Then, as the follower side, the exoskeleton is driven to assist the user's hand for rehabilitation training according to the input. The exoskeleton mechanism is designed as a universal module that can adapt to various digit sizes and weighs only 40 g. Additionally, the current motion of the exoskeleton is fed back to the system in real time, forming a closed loop to ensure control accuracy. Finally, four experiments validate the design effectiveness and motion performance of the proposed exoskeleton system. The experimental results indicate that our prototype can provide an average force of about 16.5 N for the whole hand during flexing, and the success rate reaches 82.03% in grasping tasks. Importantly, the proposed prototype holds promise for improving rehabilitation outcomes, offering diverse options for different stroke stages or application scenarios.

High-stable all-iron redox flow battery with innovative anolyte based on steric hindrance regulation.

All-soluble all-iron redox flow batteries (AIRFBs) are an innovative energy storage technology that offer significant financial benefits. Stable and affordable redox-active materials are essential for the commercialization of AIRFBs, yet the battery stability must be significantly improved to achieve practical value. Herein, ferrous complexes combined with the triisopropanolamine (TIPA) ligand are identified as promising anolytes to extend battery life by reducing cross-contamination due to a pronounced steric hindrance effect. The coordination structure and failure mechanism of our Fe-TIPA complexes were determined by molecular dynamics simulation and spectroscopic experiments. By coupling with [Fe(CN)6]4 -/3- , Fe-TIPA/Fe-CN AIRFBs retained excellent stability exceeding 1831 cycles at 80 mA·cm -2 , yielding an energy efficiency of ~80% and maintaining a steady discharge capacity. Moreover, the all-soluble electrolyte was tested in an industrial-scale Fe-TIPA/Fe-CN AIRFB prototype energy storage system, where an energy efficiency of 81.3% was attained. Given the abundance of iron resources, we model the TIPA AIRFB electrolyte cost to be as low as 32.37 $/kWh, which is significantly cheaper than the current commercial level. This work demonstrates that steric hindrance is an effective measure to extended battery life, facilitating the commercial development of affordable flow batteries.

Evidence for Two-Dimensional Weyl Fermions in Air-Stable Monolayer PtTe1.75.

The Weyl semimetals represent a distinct category of topological materials wherein the low-energy excitations appear as the long-sought Weyl Fermions. Exotic transport and optical properties are expected because of the chiral anomaly and linear energy-momentum dispersion. While three-dimensional Weyl semimetals have been successfully realized, the quest for their two-dimensional (2D) counterparts is ongoing. Here, we report the realization of 2D Weyl Fermions in monolayer PtTe1.75, which has strong spin-orbit coupling and lacks inversion symmetry, by combined angle-resolved photoemission spectroscopy, scanning tunneling microscopy, second harmonic generation, X-ray photoelectron spectroscopy measurements, and first-principles calculations. The giant Rashba splitting and band inversion lead to the emergence of three pairs of critical Weyl cones. Moreover, monolayer PtTe1.75 exhibits excellent chemical stability in ambient conditions, which is critical for future device applications. The discovery of 2D Weyl Fermions in monolayer PtTe1.75 opens up new possibilities for designing and fabricating novel spintronic devices.

Wheat Stripe Rust Inoculum from the Southwest Dispersed to the East Huang-Huai-Hai Region through Southern Anhui in China.

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a continuous threat to global wheat production. In 2021, the epidemic of wheat stripe rust in China affected approximately 4.5 million hectares, resulting in severe yield losses. When confronted with the epidemic, tracing the sources of the pathogen can offer valuable insights for disease prevention and control. This study was conducted to analyze the genetic structure, aerodynamics, geographical features, and cultivation practices of the pathogen population in various wheat-producing regions, and to further reveal the spread patterns of the stripe rust pathogens in China. The findings indicated an overall trend of the pathogen dissemination from the west to the east. The pathogen was primarily spread from the northwestern region to the Huang-Huai-Hai region through the Guanzhong Plain and the NanXiang Plain. Meanwhile, the pathogen was also spread eastward from the southwestern region to the lower reaches of the Yangtze River, utilizing the Jianghan Plain as a bridge and the Yangtze River Valley in southwestern Anhui as the main pathway. Furthermore, the pathogen spread northward into Shandong under the driving force of the southeast winds. The findings of this study may provide valuable insights for the integrated management of wheat stripe rust in China.

Multi-omic profiling of intraductal papillary neoplasms of the pancreas reveals distinct expression patterns and potential markers of progression.

In order to advance our understanding of precancers in the pancreas, 69 pancreatic intraductal papillary neoplasms (IPNs), including 64 intraductal papillary mucinous neoplasms (IPMNs) and 5 intraductal oncocytic papillary neoplasms (IOPNs), 32 pancreatic cyst fluid samples, 104 invasive pancreatic ductal adenocarcinomas (PDACs), 43 normal adjacent tissues (NATs), and 76 macro-dissected normal pancreatic ducts (NDs) were analyzed by mass spectrometry. A total of 10,246 proteins and 22,284 glycopeptides were identified in all tissue samples, and 756 proteins with more than 1.5-fold increase in abundance in IPMNs relative to NDs were identified, 45% of which were also identified in cyst fluids. The over-expression of selected proteins was validated by immunolabeling. Proteins and glycoproteins overexpressed in IPMNs included those involved in glycan biosynthesis and the immune system. In addition, multiomics clustering identified two subtypes of IPMNs. This study provides a foundation for understanding tumor progression and targets for earlier detection and therapies. Significance: This multilevel characterization of intraductal papillary neoplasms of the pancreas provides a foundation for understanding the changes in protein and glycoprotein expression during the progression from normal duct to intraductal papillary neoplasm, and to invasive pancreatic carcinoma, providing a foundation for informed approaches to earlier detection and treatment.

Glyco-signatures in patients with advanced lung cancer during anti-PD-1/PD-L1 immunotherapy.

Immune checkpoint inhibitors (ICIs) targeting programmed cell death 1/programmed cell death ligand-1 (PD-1/PD-L1) have significantly prolonged the survival of advanced/metastatic patients with lung cancer. However, only a small proportion of patients can benefit from ICIs, and clinical management of the treatment process remains challenging. Glycosylation has added a new dimension to advance our understanding of tumor immunity and immunotherapy. To systematically characterize anti-PD-1/PD-L1 immunotherapy-related changes in serum glycoproteins, a series of serum samples from 12 patients with metastatic lung squamous cell carcinoma (SCC) and lung adenocarcinoma (ADC), collected before and during ICIs treatment, are firstly analyzed with mass-spectrometry-based label-free quantification method. Second, a stratification analysis is performed among anti-PD-1/PD-L1 responders and non-responders, with serum levels of glycopeptides correlated with treatment response. In addition, in an independent validation cohort, a large-scale site-specific profiling strategy based on chemical labeling is employed to confirm the unusual characteristics of IgG N-glycosylation associated with anti-PD-1/PD-L1 treatment. Unbiased label-free quantitative glycoproteomics reveals serum levels' alterations related to anti-PD-1/PD-L1 treatment in 27 out of 337 quantified glycopeptides. The intact glycopeptide EEQFN 177STYR (H3N4) corresponding to IgG4 is significantly increased during anti-PD-1/PD-L1 treatment (FC=2.65, P=0.0083) and has the highest increase in anti-PD-1/PD-L1 responders (FC=5.84, P=0.0190). Quantitative glycoproteomics based on protein purification and chemical labeling confirms this observation. Furthermore, obvious associations between the two intact glycopeptides (EEQFN 177STYR (H3N4) of IgG4, EEQYN 227STFR (H3N4F1) of IgG3) and response to treatment are observed, which may play a guiding role in cancer immunotherapy. Our findings could benefit future clinical disease management.

Mitochondrial Quality Control in Ovarian Function: From Mechanisms to Therapeutic Strategies.

Mitochondrial quality control plays a critical role in cytogenetic development by regulating various cell-death pathways and modulating the release of reactive oxygen species (ROS). Dysregulated mitochondrial quality control can lead to a broad spectrum of diseases, including reproductive disorders, particularly female infertility. Ovarian insufficiency is a significant contributor to female infertility, given its high prevalence, complex pathogenesis, and profound impact on women's health. Understanding the pathogenesis of ovarian insufficiency and devising treatment strategies based on this understanding are crucial. Oocytes and granulosa cells (GCs) are the primary ovarian cell types, with GCs regulated by oocytes, fulfilling their specific energy requirements prior to ovulation. Dysregulation of mitochondrial quality control through gene knockout or external stimuli can precipitate apoptosis, inflammatory responses, or ferroptosis in both oocytes and GCs, exacerbating ovarian insufficiency. This review aimed to delineate the regulatory mechanisms of mitochondrial quality control in GCs and oocytes during ovarian development. This study highlights the adverse consequences of dysregulated mitochondrial quality control on GCs and oocyte development and proposes therapeutic interventions for ovarian insufficiency based on mitochondrial quality control. These insights provide a foundation for future clinical approaches for treating ovarian insufficiency.

Ginsenoside Rh4 prevents endothelial dysfunction as a novel AMPK activator.

BACKGROUND AND PURPOSE: The AMP-activated protein kinase (AMPK) signalling pathway is a desirable target for various cardiovascular diseases (CVD), while the involvement of AMPK-mediated specific downstream pathways and effective interventions in hyperlipidaemia-induced endothelial dysfunction remain largely unknown. Herein, we aim to identify an effective AMPK activator and to explore its efficacy and mechanism against endothelial dysfunction. EXPERIMENTAL APPROACH: Molecular docking technique was adopted to screen for the potent AMPK activator among 11 most common rare ginsenosides. In vivo, poloxamer 407 (P407) was used to induce acute hyperlipidaemia in C57BL/6J mice. In vitro, palmitic acid (PA) was used to induce lipid toxicity in HAEC cells. KEY RESULTS: We discovered the strongest binding of ginsenoside Rh4 to AMPKα1 and confirmed the action of Rh4 on AMPK activation. Rh4 effectively attenuated hyperlipidaemia-related endothelial injury and oxidative stress both in vivo and in vitro and restored cell viability, mitochondrial membrane potential and mitochondrial oxygen consumption rate in HAEC cells. Mechanistically, Rh4 bound to AMPKα1 and simultaneously up-regulated AKT/eNOS-mediated NO release, promoted PGC-1α-mediated mitochondrial biogenesis and inhibited P38 MAPK/NFκB-mediated inflammatory responses in both P407-treated mice and PA-treated HAEC cells. The AMPK inhibitor Compound C treatment completely abrogated the regulation of Rh4 on the above pathways and weakened the lowering effect of Rh4 on endothelial impairment markers, suggesting that the beneficial effects of Rh4 are AMPK dependent. CONCLUSION AND IMPLICATIONS: Rh4 may serve as a novel AMPK activator to protect against hyperlipidaemia-induced endothelial dysfunction, providing new insights into the prevention and treatment of endothelial injury-associated CVD.

Evidence for multiferroicity in single-layer CuCrSe2.

Multiferroic materials, which simultaneously exhibit ferroelectricity and magnetism, have attracted substantial attention due to their fascinating physical properties and potential technological applications. With the trends towards device miniaturization, there is an increasing demand for the persistence of multiferroicity in single-layer materials at elevated temperatures. Here, we report high-temperature multiferroicity in single-layer CuCrSe2, which hosts room-temperature ferroelectricity and 120 K ferromagnetism. Notably, the ferromagnetic coupling in single-layer CuCrSe2 is enhanced by the ferroelectricity-induced orbital shift of Cr atoms, which is distinct from both types I and II multiferroicity. These findings are supported by a combination of second-harmonic generation, piezo-response force microscopy, scanning transmission electron microscopy, magnetic, and Hall measurements. Our research provides not only an exemplary platform for delving into intrinsic magnetoelectric interactions at the single-layer limit but also sheds light on potential development of electronic and spintronic devices utilizing two-dimensional multiferroics.

Gold-Template-Assisted Mechanical Exfoliation of Large-Area 2D Layers Enables Efficient and Precise Construction of Moiré Superlattices.

Moiré superlattices, consisting of rotationally aligned 2D atomically thin layers, provide a highly novel platform for the study of correlated quantum phenomena. However, reliable and efficient construction of moiré superlattices is challenging because of difficulties to accurately angle-align small exfoliated 2D layers and the need to shun wet-transfer processes. Here, efficient and precise construction of various moiré superlattices is demonstrated by picking up and stacking large-area 2D mono- or few-layer crystals with predetermined crystal axes, made possible by a gold-template-assisted mechanical exfoliation method. The exfoliated 2D layers are semiconductors, superconductors, or magnets and their high quality is confirmed by photoluminescence and Raman spectra and by electrical transport measurements of fabricated field-effect transistors and Hall devices. Twisted homobilayers with angle-twisting accuracy of ≈0.3°, twisted heterobilayers with sub-degree angle-alignment accuracy, and multilayer superlattices are precisely constructed and characterized by their moiré patterns, interlayer excitons, and second harmonic generation. The present study paves the way for exploring emergent phenomena in moiré superlattices.

Unidirectional gene delivery electrospun fibrous membrane via charge repulsion for tendon repair.

Gene therapy is capable of efficiently regulating the expression of abnormal genes in diseased tissues and expected to be a therapeutic option for refractory diseases. However, unidirectional targeting gene therapy is always desired at the tissue interface. In this study, inspired by the principle that like charges repulse each other, a positively charged micro-nano electrospun fibrous membrane with dual-layer structure was developed by electrospinning technology to achieve unidirectional delivery of siRNA-loaded cationic nanocarriers, thus realizing unidirectional gene therapy at the tendon-paratenon interface. Under the charge repulsion of positively charged layer, more cationic COX-2 siRNA nanocarriers were enriched in peritendinous tissue, which not only improved the bioavailability of the gene drug to prevent the peritendinous adhesion formation, but also avoided adverse effects on the fragile endogenous healing of tendon itself. In summary, this study provides an innovative strategy for unidirectional targeting gene therapy of tissue interface diseases by utilizing charge repulsion to facilitate unidirectional delivery of gene drugs.

Machine-learning-assisted and real-time-feedback-controlled growth of InAs/GaAs quantum dots.

The applications of self-assembled InAs/GaAs quantum dots (QDs) for lasers and single photon sources strongly rely on their density and quality. Establishing the process parameters in molecular beam epitaxy (MBE) for a specific density of QDs is a multidimensional optimization challenge, usually addressed through time-consuming and iterative trial-and-error. Here, we report a real-time feedback control method to realize the growth of QDs with arbitrary density, which is fully automated and intelligent. We develop a machine learning (ML) model named 3D ResNet 50 trained using reflection high-energy electron diffraction (RHEED) videos as input instead of static images and providing real-time feedback on surface morphologies for process control. As a result, we demonstrate that ML from previous growth could predict the post-growth density of QDs, by successfully tuning the QD densities in near-real time from 1.5 × 1010 cm-2 down to 3.8 × 108 cm-2 or up to 1.4 × 1011 cm-2. Compared to traditional methods, our approach can dramatically expedite the optimization process and improve the reproducibility of MBE. The concepts and methodologies proved feasible in this work are promising to be applied to a variety of material growth processes, which will revolutionize semiconductor manufacturing for optoelectronic and microelectronic industries.

SUGAR: Spherical ultrafast graph attention framework for cortical surface registration.

Cortical surface registration plays a crucial role in aligning cortical functional and anatomical features across individuals. However, conventional registration algorithms are computationally inefficient. Recently, learning-based registration algorithms have emerged as a promising solution, significantly improving processing efficiency. Nonetheless, there remains a gap in the development of a learning-based method that exceeds the state-of-the-art conventional methods simultaneously in computational efficiency, registration accuracy, and distortion control, despite the theoretically greater representational capabilities of deep learning approaches. To address the challenge, we present SUGAR, a unified unsupervised deep-learning framework for both rigid and non-rigid registration. SUGAR incorporates a U-Net-based spherical graph attention network and leverages the Euler angle representation for deformation. In addition to the similarity loss, we introduce fold and multiple distortion losses to preserve topology and minimize various types of distortions. Furthermore, we propose a data augmentation strategy specifically tailored for spherical surface registration to enhance the registration performance. Through extensive evaluation involving over 10,000 scans from 7 diverse datasets, we showed that our framework exhibits comparable or superior registration performance in accuracy, distortion, and test-retest reliability compared to conventional and learning-based methods. Additionally, SUGAR achieves remarkable sub-second processing times, offering a notable speed-up of approximately 12,000 times in registering 9,000 subjects from the UK Biobank dataset in just 32 min. This combination of high registration performance and accelerated processing time may greatly benefit large-scale neuroimaging studies.