Photoinduced Electronic and Spin Topological Phase Transitions in Monolayer Bismuth.

Ultrathin bismuth exhibits rich physics including strong spin-orbit coupling, ferroelectricity, nontrivial topology, and light-induced structural dynamics. We use ab initio calculations to show that light can induce structural transitions to four transient phases in bismuth monolayers. These light-induced phases exhibit nontrivial topological character, which we illustrate using the recently introduced concept of spin bands and spin-resolved Wilson loops. Specifically, we find that the topology changes via the closing of the electron and spin band gaps during photoinduced structural phase transitions, leading to distinct edge states. Our study provides strategies to tailor electronic and spin topology via ultrafast control of photoexcited carriers and associated structural dynamics.

[Progressive myoclonic epilepsy: a retrospective study of newly-diagnosed adult patients from a single center].

OBJECTIVE: To retrospectively analyze the clinical phenotype and pathogenic variants in patients with Progressive myoclonus epilepsy (PME). METHODS: Clinical data and results of genetic testing for 11 patients diagnosed with PME at the Department of Neurology, the First Affiliated Hospital of Zhejiang University School of Medicine from June 2017 to December 2022 were collected and analyzed. RESULTS: All of the patients, including 4 males and 7 females, had predominant action myoclonus. Three patients had myoclonus as the initial manifestation, whilst eight were diagnosed through genetic testing, including three cases with NEU1 gene variants, two with EPM2A gene variants (1 was novel), one with MT-TK gene variant, one with ATN1 gene variant, and one with CSTB gene variant. No pathogenic variant was identified in the remaining three cases. Among the eight patients with a genetic diagnosis, three were diagnosed with sialidosis, two with Lafora disease, one with Dentatorubral-pallidoluysian atrophy (DRPLA), one with Unverricht-Lundborg disease (ULD), and one with Myoclonic epilepsy with ragging red fibers (MERRF). CONCLUSION: Compared with pediatric patients, adult patients with PME represent a distinct subtype with slower progression and milder cognitive impairment.

Intrinsic exchange biased anomalous Hall effect in an uncompensated antiferromagnet MnBi2Te4.

Achieving spin-pinning at the interface of hetero-bilayer ferromagnet/antiferromagnet structures in conventional exchange bias systems can be challenging due to difficulties in interface control and the weakening of spin-pinning caused by poor interface quality. In this work, we propose an alternative approach to stabilize the exchange interaction at the interface of an uncompensated antiferromagnet by utilizing a gradient of interlayer exchange coupling. We demonstrate this exchange interaction through a designed field training protocol in the odd-layer topological antiferromagnet MnBi2Te4. Our results reveal a remarkable field-trained exchange bias of up to ~ 400 mT, which exhibits high repeatability and can be easily reset by a large training field. Notably, this field-trained exchange bias effect persists even with zero-field initialization, presenting a stark contrast to the traditional field-cooled exchange bias. The highly tunable exchange bias observed in this single antiferromagnet compound, without the need for an additional magnetic layer, provides valuable insight into the exchange interaction mechanism. These findings pave the way for the systematic design of topological antiferromagnetic spintronics.

Exchange-Driven Chern States in High-Mobility Intrinsic Magnetic Topological Insulators.

The layer-dependent Chern number (C) in MnBi_{2}Te_{4} is characterized by the presence of a Weyl semimetal state in the ferromagnetic coupling. However, the influence of a key factor, namely, the exchange coupling, remains unexplored. This study focuses on characterizing the C=2 state in MnBi_{2}Te_{4}, which is classified as a higher C state resulting from the anomalous n=0 Landau levels (LLs). Our findings demonstrate that the exchange coupling parameter strongly influences the formation of this Chern state, leading to a competition between the C=1 and 2 states. Moreover, the emergence of odd-even LL sequences, resulting from the breaking of LL degeneracy, provides compelling evidence for the strong exchange coupling strength. These findings highlight the significance of the exchange coupling in understanding the behavior of Chern states and LLs in magnetic quantum systems.

Clinical characteristics of neonatal and infant osteomyelitis and septic arthritis: a multicenter retrospective study.

OBJECTIVE: Signs and symptoms of osteomyelitis or septic arthritis in neonates and infants are often nonspecific and early-stage bone infections in infants may often go unnoticed. The objective of this study was to analyze the clinical characteristics of newborns and infants with osteomyelitis and septic arthritis to improve understanding of the disorder and to assist clinicians with diagnosis. METHODS: A retrospective multicenter study was conducted on neonates (0-28 days old, n = 94) and infants (1-12 months old, n = 415) with osteoarticular infections. Data consisting of clinical characteristics, complications, laboratory outcomes, and the pathogenic microorganisms causing osteomyelitis were tabulated. The statistics were further broken down into two regions and the significant differences between neonates and infants were evaluated and compared to the literature. RESULTS: Compared to infants, neonates had significantly lower incidences of fever (p < 0.0001), higher incidences of localized swelling (p = 0.0021), higher rate of infection at the humerus (p = 0.0016), higher percentage of Escherichia coli (p < 0.0001) and Klebsiella pneumoniae (p = 0.0039) infections, lower percentage of Staphylococcus aureus infections (p < 0.0001) and were more likely to develop septic arthritis (p < 0.0001). CONCLUSION: Distinct differences were found between neonatal and infants with osteoarticular infections. Future studies should focus on improving diagnosis and subsequent treatment regimens for younger age groups.

Terahertz-triggered ultrafast nonlinear optical activities in two-dimensional centrosymmetric PtSe2.

The nonlinear mechanisms of polarization and optical fields can induce extensive responses in materials. In this study, we report on two kinds of nonlinear mechanisms in the topological semimetal PtSe2 crystal under the excitation of intense terahertz (THz) pulses, which are manipulated by the real and imaginary parts of the nonlinear susceptibility of PtSe2. Regarding the real part, the broken inversion symmetry of PtSe2 is achieved through a THz-electric-field polarization approach, which is characterized by second harmonic generation (SHG) measurements. The transient THz-laser-induced SHG signal occurs within 100 fs and recombines to the equilibrium state within 1 ps, along with a high signal-to-noise ratio (∼51 dB) and a high on/off ratio (∼102). Regarding the imaginary part, a nonlinear absorption change can be generated in the media. We reveal a THz-induced absorption enhancement in PtSe2 via nonlinear transmittance measurements, and the sheet conductivity can be modulated up to 42% by THz electric fields in our experiment. Therefore, the THz-induced ultrafast nonlinear photoresponse reveals the application potential of PtSe2 in photonic and optoelectronic devices in the THz technology.

Reconfigurable origami hologram based on deep neural networks.

Reconfigurable and multifunctional metasurfaces are becoming indispensable in a variety of applications due to their capability to execute diverse functions across various states. However, many of these metasurfaces incorporate complex active components, thereby escalating structural complexity and bulk volume. In this research, we propose a reconfigurable passive hologram based solely on an origami structure, enabling the successful generation of holograms depicting the 'Z' and 'L' illuminated by a right-hand circular polarization (RHCP) wave in two distinct states: planar and zigzag configuration, respectively. The transformation between the 2D planar metasurface and the 3D zigzag structure with slant angles of 35 is achieved solely through mechanically stretching and compressing the origami metasurface. The phases on the origami metasurface are trained through a deep neural network which operates on the NVIDIA Tesla k80 GPU, with the total training process costing 11.88 s after 100 epochs. The reconfigurable scheme proposed in this research provides flexibility and ease of implementation in the fields of imaging and data processing.

Co-culture of RhoA-overexpressed Microtia Chondrocytes and Adipose-Derived Stem Cells in the Construction of Tissue-engineered Ear-shaped Cartilage.

Microtia is a congenital auricle dysplasia with a high incidence and tissue engineering technology provides a promising strategy to reconstruct auricles. We previously described that the engineered cartilage constructed from microtia chondrocytes exhibited inferior levels of biochemical and biomechanical properties, which was proposed to be resulted from the decreased migration ability of microtia chondrocytes. In the current study, we found that Rho GTPase members were deficient in microtia chondrocytes. By overexpressing RhoA, Rac1 and CDC42, respectively, we further demonstrated that RhoA took great responsibility for the decreased migration ability of microtia chondrocytes. Moreover, we constructed PGA/PLA scaffold-based cartilages to verify the chondrogenic ability of RhoA overexpressed microtia chondrocytes, and the results showed that overexpressing RhoA was of limited help to improve the quality of microtia chondrocyte engineered cartilage. However, co-culture of ADSCs significantly improved the biochemical and biomechanical property of engineered cartilage. Especially, co-culture of RhoA overexpressed microtia chondrocytes and ADSCs produced an excellent effect on the wet weight, cartilage-specific extracellular matrix and biomechanical property of engineered cartilage. Furthermore, we presented that co-culture of RhoA overexpressed microtia chondrocytes and ADSCs combined with human ear-shaped PGA/PLA scaffold and titanium alloy stent fabricated by CAD/CAM and 3D printing technology effectively constructed and maintained auricle structure in vivo. Collectively, our results provide evidence for the essential role of RhoA in microtia chondrocytes and a developed strategy for the construction of patient-specific tissue-engineered auricular cartilage.

Enhancing cancer therapy: The role of drug delivery systems in STAT3 inhibitor efficacy and safety.

The signal transducer and activator of transcription 3 (STAT3), a member of the STAT family, resides in the nucleus to regulate genes essential for vital cellular functions, including survival, proliferation, self-renewal, angiogenesis, and immune response. However, continuous STAT3 activation in tumor cells promotes their initiation, progression, and metastasis, rendering STAT3 pathway inhibitors a promising avenue for cancer therapy. Nonetheless, these inhibitors frequently encounter challenges such as cytotoxicity and suboptimal biocompatibility in clinical trials. A viable strategy to mitigate these issues involves delivering STAT3 inhibitors via drug delivery systems (DDSs). This review delineates the regulatory mechanisms of the STAT3 signaling pathway and its association with cancer. It offers a comprehensive overview of the current application of DDSs for anti-STAT3 inhibitors and investigates the role of DDSs in cancer treatment. The conclusion posits that DDSs for anti-STAT3 inhibitors exhibit enhanced efficacy and reduced adverse effects in tumor therapy compared to anti-STAT3 inhibitors alone. This paper aims to provide an outline of the ongoing research and future prospects of DDSs for STAT3 inhibitors. Additionally, it presents our insights on the merits and future outlook of DDSs in cancer treatment.

Evaluating remote delivery of cognitive remediation in people with psychosis.

BACKGROUND: Cognitive Remediation (CR) is an evidence-based therapy targeting cognitive difficulties in people with psychosis to promote functional recovery, but it is rarely implemented routinely. To reach more individuals, CR is beginning to be delivered remotely, but there is limited evidence to support the acceptability of this method. AIMS: To evaluate the acceptability and feasibility of remote therapist-supported CR in people with psychosis and estimate its cost and potential benefits. METHODS: A case-series with all participants assessed before and after therapy with measures of personal goal attainment (main outcome), cognition, functioning and symptoms. Acceptability was assessed with post-therapy interviews. Feasibility was assessed using proportions and confidence intervals on pre-specified parameters. Indication of benefits was assessed with exploratory analyses comparing baseline and post-therapy scores on the pre-specified outcomes. The cost of providing remote CR was assessed from both healthcare and societal perspectives. RESULTS: Twenty-nine participants started therapy with two dropping out; on average participants attended 25.5 sessions. Interviews suggested that remote CR had good acceptability and led to perceived benefits. Significant and large improvements were observed on goal attainment. Cost analyses suggest that remote CR has the same health care cost as face-to-face therapy but a lower societal cost. CONCLUSIONS: Our results support the use of remote CR in psychosis services as an alternative delivery modality. This method may improve adherence, attendance and be more convenient for service users. Possible barriers such as poor digital literacy or appropriate device ownership should be addressed before starting therapy.

Dual-space high-frequency learning for transformer-based MRI super-resolution.

BACKGROUND AND OBJECTIVE: Magnetic resonance imaging (MRI) can provide rich and detailed high-contrast information of soft tissues, while the scanning of MRI is time-consuming. To accelerate MR imaging, a variety of Transformer-based single image super-resolution methods are proposed in recent years, achieving promising results thanks to their superior capability of capturing long-range dependencies. Nevertheless, most existing works prioritize the design of transformer attention blocks to capture global information. The local high-frequency details, which are pivotal to faithful MRI restoration, are unfortunately neglected. METHODS: In this work, we propose a high-frequency enhanced learning scheme to effectively improve the awareness of high frequency information in current Transformer-based MRI single image super-resolution methods. Specifically, we present two entirely plug-and-play modules designed to equip Transformer-based networks with the ability to recover high-frequency details from dual spaces: 1) in the feature space, we design a high-frequency block (Hi-Fe block) paralleled with Transformer-based attention layers to extract rich high-frequency features; while 2) in the image intensity space, we tailor a high-frequency amplification module (HFA) to further refine the high-frequency details. By fully exploiting the merits of the two modules, our framework can recover abundant and diverse high-frequency information, rendering faithful MRI super-resolved results with fine details. RESULTS: We integrated our modules with six Transformer-based models and conducted experiments across three datasets. The results indicate that our plug-and-play modules can enhance the super-resolution performance of all foundational models to varying degrees, surpassing the capabilities of existing state-of-the-art single image super-resolution networks. CONCLUSION: Comprehensive comparison of super-resolution images and high-frequency maps from various methods, clearly demonstrating that our module possesses the capability to restore high-frequency information, showing huge potential in clinical practice for accelerated MRI reconstruction.

Tailored Local Electronic Environment of Co-N4 Sites in Cobalt Phthalocyanines for Enhanced CO2 Reduction Reaction.

Atomically dispersed Co-N4-based catalysts have been recently emerging as one of the most promising candidates for facilitating CO2 reduction reaction (CO2RR). The local electronic environment of Co-N4 sites in these catalysts is considered to play a critical role in adjusting the catalytic performance, the effort of which however is not yet clearly verified. Herein, a series of cobalt phthalocyanines with different peripheral substituents including unsubstituted phthalocyanine Co(II) (CoPc), 2,9,16,23-tetramethoxyphthalocyaninato Co(II) (CoPc-4OCH3), and 2,9,16,23-tetranitrophthalocyaninato Co(II) (CoPc-4NO2) are supported onto the surface of the multi-walled carbon nanotubes (CNTs), affording CoPc@CNTs, CoPc-4OCH3@CNTs, and CoPc-4NO2@CNTs. X-ray photoelectron spectroscopy and X-ray absorption near-edge structure measurements disclose the influence of the peripheral substituents on the local electronic structure of Co atoms in these three catalysts. Electrochemical tests indicate the higher CO2RR performance of CoPc-4OCH3@CNTs compared to CoPc@CNTs and CoPc-4NO2@CNTs as exemplified by the higher Faraday efficiency of CO, larger part current densities, and better stability displayed by CoPc-4OCH3@CNTs at the applied voltage range from -0.6 to -1.0 V versus RHE in both H-cell and flow cell. These results highlight the effect of the electron-donating -OCH3 substituent on the enhanced catalytic activity of CoPc-4OCH3@CNTs, which will help develop Co-N4-based catalysts with promising catalytic performance toward CO2RR.

Endothelial lincRNA-p21 alleviates cerebral ischemia/reperfusion injury by maintaining blood-brain barrier integrity.

Blood-brain barrier (BBB) disruption is increasingly recognized as an early contributor to the pathophysiology of cerebral ischemia/reperfusion (I/R) injury, and is also a key event in triggering secondary damage to the central nervous system. Recently, long non-coding RNA (lncRNA) have been found to be associated with ischemic stroke. However, the roles of lncRNA in BBB homeostasis remain largely unknown. Here, we report that long intergenic non-coding RNA-p21 (lincRNA-p21) was the most significantly down-regulated lncRNA in human brain microvascular endothelial cells (HBMECs) after oxygen and glucose deprivation/reoxygenation (OGD/R) treatment among candidate lncRNA, which were both sensitive to hypoxia and involved in atherosclerosis. Exogenous brain-endothelium-specific overexpression of lincRNA-p21 could alleviate BBB disruption, diminish infarction volume and attenuate motor function deficits in middle cerebral artery occlusion/reperfusion (MCAO/R) mice. Further results showed that lincRNA-p21 was critical to maintain BBB integrity by inhibiting the degradation of junction proteins under MCAO/R and OGD/R conditions. Specifically, lincRNA-p21 could inhibit autophagy-dependent degradation of occludin by activating PI3K/AKT/mTOR signaling pathway. Besides, lincRNA-p21 could inhibit VE-cadherin degradation by binding with miR-101-3p. Together, we identify that lincRNA-p21 is critical for BBB integrity maintenance, and endothelial lincRNA-p21 overexpression could alleviate cerebral I/R injury in mice, pointing to a potential strategy to treat cerebral I/R injury.

Breast Cancer Classification from Digital Pathology Images via Connectivity-aware Graph Transformer.

Automated classification of breast cancer subtypes from digital pathology images has been an extremely challenging task due to the complicated spatial patterns of cells in the tissue micro-environment. While newly proposed graph transformers are able to capture more long-range dependencies to enhance accuracy, they largely ignore the topological connectivity between graph nodes, which is nevertheless critical to extract more representative features to address this difficult task. In this paper, we propose a novel connectivity-aware graph transformer (CGT) for phenotyping the topology connectivity of the tissue graph constructed from digital pathology images for breast cancer classification. Our CGT seamlessly integrates connectivity embedding to node feature at every graph transformer layer by using local connectivity aggregation, in order to yield more comprehensive graph representations to distinguish different breast cancer subtypes. In light of the realistic intercellular communication mode, we then encode the spatial distance between two arbitrary nodes as connectivity bias in self-attention calculation, thereby allowing the CGT to distinctively harness the connectivity embedding based on the distance of two nodes. We extensively evaluate the proposed CGT on a large cohort of breast carcinoma digital pathology images stained by Haematoxylin & Eosin. Experimental results demonstrate the effectiveness of our CGT, which outperforms state-of-the-art methods by a large margin. Codes are released on https://github.com/wang-kang-6/CGT.

Ultralow-Friction at Cryogenic Temperature Induced by Hydrogen Correlated Quantum Effect.

Temperature is one of the governing factors affecting friction of solids. Undesired high friction state has been generally reported at cryogenic temperatures due to the prohibition of thermally activated processes, following conventional Arrhenius equation. This has brought huge difficulties to lubrication at extremely low temperatures in industry. Here, the study uncovers a hydrogen-correlated sub-Arrhenius friction behavior in hydrogenated amorphous carbon (a-C:H) film at cryogenic temperatures, and a stable ultralow-friction over a wide temperature range (103-348 K) is achieved. This is attributed to hydrogen-transfer-induced mild structural ordering transformation, confirmed by machine-learning-based molecular dynamics simulations. The anomalous sub-Arrhenius temperature dependence of structural ordering transformation rate is well-described by a quantum mechanical tunneling (QMT) modified Arrhenius model, which is correlated with quantum delocalization of hydrogen in tribochemical reactions. This work reveals a hydrogen-correlated friction mechanism overcoming the Arrhenius temperature dependence and provides a new pathway for achieving ultralow friction under cryogenic conditions.

Positive effect of microvascular proliferation on functional recovery in experimental cervical spondylotic myelopathy.

Background and purpose: Cervical Spondylotic Myelopathy (CSM), the most common cause of spinal cord dysfunction globally, is a degenerative disease that results in non-violent, gradual, and long-lasting compression of the cervical spinal cord. The objective of this study was to investigate whether microvascular proliferation could positively affect neural function recovery in experimental cervical spondylotic myelopathy (CSM). Methods: A total of 60 male adult Sprague-Dawley (SD) were randomly divided into four groups: Control (CON), Compression (COM), Angiostasis (AS), and Angiogenesis (A G),with 15 rats in each group. Rats in the AS group received SU5416 to inhibit angiogenesis, while rats in the AG group received Deferoxamine (DFO) to promote angiogenesis. Motor and sensory functions were assessed using the Basso Beattie Bresnahan (BBB) scale and somatosensory evoked potential (SEP) examination. Neuropathological degeneration was evaluated by the number of neurons, Nissl bodies (NB), and the de-myelination of white matter detected by Hematoxylin & Eosin(HE), Toluidine Blue (TB), and Luxol Fast Blue (LFB) staining. Immunohistochemical (IHC) staining was used to observe the Neurovascular Unit (NVU). Results: Rats in the CON group exhibited normal locomotor function with full BBB score, normal SEP latency and amplitude. Among the other three groups, the AG group had the highest BBB score and the shortest SEP latency, while the AS group had the lowest BBB score and the most prolonged SEP latency. The SEP amplitude showed an opposite performance to the latency. Compared to the COM and AS groups, the AG group demonstrated significant neuronal restoration in gray matter and axonal remyelination in white matter. DFO promoted microvascular proliferation, especially in gray matter, and improved the survival of neuroglial cells. In contrast, SU-5416 inhibited the viability of neuroglial cells by reducing micro vessels. Conclusion: The microvascular status was closely related to NVU remodeling an-d functional recovery. Therefore, proliferation of micro vessels contributed to function -al recovery in experimental CSM, which may be associated with NVU remodeling.

Synergistic Effects of Amine Functional Groups and Enriched-Atomic-Iron Sites in Carbon Dots for Industrial-Current-Density CO2 Electroreduction.

Metal phthalocyanine molecules with Me-N4 centers have shown promise in electrocatalytic CO2 reduction (eCO2R) for CO generation. However, iron phthalocyanine (FePc) is an exception, exhibiting negligible eCO2R activity due to a higher CO2 to *COOH conversion barrier and stronger *CO binding energy. Here, amine functional groups onto atomic-Fe-rich carbon dots (Af-Fe-CDs) are introduced via a one-step solvothermal molecule fusion approach. Af-Fe-CDs feature well-defined Fe-N4 active sites and an impressive Fe loading (up to 8.5 wt%). The synergistic effect between Fe-N4 active centers and electron-donating amine functional groups in Af-Fe-CDs yielded outstanding CO2-to-CO conversion performance. At industrial-relevant current densities exceeding 400 mA cm-2 in a flow cell, Af-Fe-CDs achieved >92% selectivity, surpassing state-of-the-art CO2-to-CO electrocatalysts. The in situ electrochemical FTIR characterization combined with theoretical calculations elucidated that Fe-N4 integration with amine functional groups in Af-Fe-CDs significantly reduced energy barriers for *COOH intermediate formation and *CO desorption, enhancing eCO2R efficiency. The proposed synergistic effect offers a promising avenue for high-efficiency catalysts with elevated atomic-metal loadings.

Revealing the Development Patterns of the Mandibular Glands of Apis mellifera carnica Based on Transcriptomics and Morphology.

The mandibular gland in worker bees synthesizes and secretes the organic acids present in royal jelly, and its development directly affects yield and quality. Therefore, we aimed to analyze the differences in morphology and gene expression in the mandibular glands of Apis mellifera carnica worker bees of different ages (3, 6, 9, 12, and 16 d). We dissected their mandibular glands and performed morphological and transcriptomic analyses to investigate the development of the mandibular gland and the molecular regulatory mechanisms involved in royal jelly secretion. Microscopy revealed that mandibular gland development is likely completed in the early stages. There were no significant differences in the structural morphology or organelles involved in the secretion of royal jelly at different ages. Transcriptomics revealed a total of 1554 differentially expressed genes, which were mainly involved in fat metabolism, lipid transport, and energy metabolism. The extracellular matrix-receptor interaction pathway was significantly enriched and contributed to the royal jelly secretion process. These results elucidate the genetic basis of the role of the mandibular gland in royal jelly secretion in A. mellifera and provide a reference for the genetic improvement of bees with high royal jelly production in the future.

Multi-Modal Temporal Hypergraph Neural Network for Flotation Condition Recognition.

Efficient flotation beneficiation heavily relies on accurate flotation condition recognition based on monitored froth video. However, the recognition accuracy is hindered by limitations of extracting temporal features from froth videos and establishing correlations between complex multi-modal high-order data. To address the difficulties of inadequate temporal feature extraction, inaccurate online condition detection, and inefficient flotation process operation, this paper proposes a novel flotation condition recognition method named the multi-modal temporal hypergraph neural network (MTHGNN) to extract and fuse multi-modal temporal features. To extract abundant dynamic texture features from froth images, the MTHGNN employs an enhanced version of the local binary pattern algorithm from three orthogonal planes (LBP-TOP) and incorporates additional features from the three-dimensional space as supplements. Furthermore, a novel multi-view temporal feature aggregation network (MVResNet) is introduced to extract temporal aggregation features from the froth image sequence. By constructing a temporal multi-modal hypergraph neural network, we encode complex high-order temporal features, establish robust associations between data structures, and flexibly model the features of froth image sequence, thus enabling accurate flotation condition identification through the fusion of multi-modal temporal features. The experimental results validate the effectiveness of the proposed method for flotation condition recognition, providing a foundation for optimizing flotation operations.