Search

Using industry standard TSMC 90 nm CMOS technology, a broadband and high-isolation active quasi-circulator MMIC was fabricated to meet the needs of future communication system integration. An active balun and phase inverter stage made of a common-source (CS) field-effect transistor (FET) comprised the quasi-circulator that was suggested. A cascade CS stage was used to produce the active balun, which increased the isolation of |S12| and |S23| through the unilateral characteristic of the FET and allowed for transmission of |S21| and |S32|. Further, a CS FET connected in parallel to ports 1 and 3 for phase cancellation can effectively increase the quasi-circulator’s isolation |S31|. Theoretical analysis for the detailed circuit was shown in the main paper. The results show that all isolations are better than 20 dB over 5–33 GHz, and the measured findings reveal that the suggested quasi-circulator has an insertion loss of less than 10 dB. It is possible to reach an isolation level of 55 dB between ports 1 and 3, which is greater than present research.

Bacterial wilt triggered by the soil-borne pathogenic bacterium Ralstonia solanacearum is one of the most serious diseases in tomato plants, leading to huge economic losses worldwide. Biological control is considered an environmentally friendly and sustainable way to manage soil-borne diseases. In this study, Streptomyces sp. STD57 isolated from the rhizosphere of Adenophora stricta showed strong antibacterial activity against R. solanacearum. Pot experiments showed that strain STD57 exhibited a significant biocontrol effect (81.7%) on tomato bacterial wilt in the greenhouse environment. Furthermore, strain STD57 could inhibit the growth of weeds (Amaranthus retroflexus, Portulaca oleracea, and Echinochloa crusgalli) but promote the growth of crops (wheat, rice, and tomato). The plant growth-promoting substance was identified as indoleacetic acid (IAA) by high-pressure liquid chromatography–mass spectrometry and genome analysis. Coarse separation of the fermented extracts revealed that the antibacterial and herbicidal substances were mainly in the fermentation supernatant and belonged to different products. These findings suggested that strain STD57 may be a potential biocontrol and bioherbicide agent useful in agriculture.

This study presents an innovative approach to utilize coal gasification coarse slag (CGCS) for efficient and low-cost gallium extraction. Using a one-step acid leaching process, mesoporous silica with a surface area of 258 m2/g and a pore volume of 0.15 cm3/g was synthesized. The properties of CGCS before and after acid leaching were characterized through SEM, FTIR, XRD, and BET analyses, with optimal conditions identified for maximizing specific surface area and generating saturated silanol groups. The prepared mesoporous silica demonstrated a 99% Ga(III) adsorption efficiency. Adsorption conditions were optimized, and adsorption kinetics, isotherms, and competitive adsorption behaviors were evaluated. Competitive adsorption with vanadium suggests potential application in Ga(III) extraction from vanadium-rich waste solutions. Furthermore, the recyclability of both the acid and adsorbent was explored, with the adsorbent maintaining over 85% adsorption efficiency after five cycles. The adsorption mechanism was further elucidated through SEM-EDS, XPS, and FTIR analyses. This work not only advances resource recovery from industrial waste but also offers a sustainable method for gallium extraction with industrial applications.

Coastal aquaculture plays a crucial role in global food security and the economic development of coastal regions, but it also causes environmental degradation in coastal ecosystems. Therefore, the automation, accurate extraction, and monitoring of coastal aquaculture areas are crucial for the scientific management of coastal ecological zones. This study proposes a novel deep learning- and attention-based median adaptive fusion U-Net (MAFU-Net) procedure aimed at precisely extracting individually separable aquaculture ponds (ISAPs) from medium-resolution remote sensing imagery. Initially, this study analyzes the spectral differences between aquaculture ponds and interfering objects such as saltwater fields in four typical aquaculture areas along the coast of Liaoning Province, China. It innovatively introduces a difference index for saltwater field aquaculture zones (DIAS) and integrates this index as a new band into remote sensing imagery to increase the expressiveness of features. A median augmented adaptive fusion module (MEA-FM), which adaptively selects channel receptive fields at various scales, integrates the information between channels, and captures multiscale spatial information to achieve improved extraction accuracy, is subsequently designed. Experimental and comparative results reveal that the proposed MAFU-Net method achieves an F1 score of 90.67% and an intersection over union (IoU) of 83.93% on the CHN-LN4-ISAPS-9 dataset, outperforming advanced methods such as U-Net, DeepLabV3+, SegNet, PSPNet, SKNet, UPS-Net, and SegFormer. This study’s results provide accurate data support for the scientific management of aquaculture areas, and the proposed MAFU-Net method provides an effective method for semantic segmentation tasks based on medium-resolution remote sensing images.

To address the issue of efficiently reusing the massive amount of unstructured knowledge generated during the handling of track circuit equipment faults and to automate the construction of knowledge graphs in the railway maintenance domain, it is crucial to leverage knowledge extraction techniques to efficiently extract relational triplets from fault maintenance text data. Given the current lag in joint extraction technology within the railway domain and the inefficiency in resource utilization, this paper proposes a joint extraction model for track circuit entities and relations, integrating Global Pointer and tensor learning. Taking into account the associative characteristics of semantic relations, the nesting of domain-specific terms in the railway sector, and semantic diversity, this research views the relation extraction task as a tensor learning process and the entity recognition task as a span-based Global Pointer search process. First, a multi-layer dilate gated convolutional neural network with residual connections is used to extract key features and fuse the weighted information from the 12 different semantic layers of the RoBERTa-wwm-ext model, fully exploiting the performance of each encoding layer. Next, the Tucker decomposition method is utilized to capture the semantic correlations between relations, and an Efficient Global Pointer is employed to globally predict the start and end positions of subject and object entities, incorporating relative position information through rotary position embedding (RoPE). Finally, comparative experiments with existing mainstream joint extraction models were conducted, and the proposed model’s excellent performance was validated on the English public datasets NYT and WebNLG, the Chinese public dataset DuIE, and a private track circuit dataset. The F1 scores on the NYT, WebNLG, and DuIE public datasets reached 92.1%, 92.7%, and 78.2%, respectively.

Ship image classification identifies the type of ships in an input image, which plays a significant role in the marine field. To enhance the ship classification performance, various research focuses on studying multi-modal ship classification, which aims at combining the advantages of visible images and infrared images to capture complementary information. However, the current methods simply concatenate features of different modalities to learn complementary information, which neglects the multi-level correlation between different modalities. Moreover, the existing methods require a large amount of labeled ship images to train the model. How to capture the multi-level cross-modal correlation between unlabeled and labeled data is still a challenge. In this paper, a novel semi-supervised multi-modal ship classification approach is proposed to solve these issues, which consists of two components, i.e., multi-level cross-modal interactive network and semi-supervised contrastive learning strategy. To learn comprehensive complementary information for classification, the multi-level cross-modal interactive network is designed to build local-level and global-level cross-modal feature correlation. Then, the semi-supervised contrastive learning strategy is employed to drive the optimization of the network with the intra-class consistency constraint based on supervision signals of unlabeled samples and prior label information. Extensive experiments on the public datasets demonstrate that our approach achieves state-of-the-art semi-supervised classification effectiveness.

Beach erosion and shoreline dynamics are strongly affected by alterations in nearshore wave intensity and energy, especially in the context of global climate change. However, existing works do not thoroughly study the evolution of the sandy coasts of eastern Hainan Island, China, nor their responses to wave climate change driven by climate variability. This study focuses on the open sandy coast and assesses shoreline evolutionary dynamics in response to wave climate variability over a 30-year period from 1994 to 2023, using an open-source software toolkit that semi-automatically identify the shorelines (CoastSat v2.4) and reanalysis wave datasets (ERA5). The shorelines of the study area were extracted from CoastSat, and then tidal correction and outlier correction were performed for clearer shorelines. Combining the shoreline changes and wave conditions derived from ERA5, the dynamics of the shorelines and their response to wave climate change were further studied. The findings reveal that the average long-term shoreline change rate along the eastern coast of Hainan Island is 0.03 m/year, with 44.8% of transects experiencing erosion and 55.2% showing long-term accretion. And distinct evolutionary patterns emerge across different sections. Interannual variability is marked by alternating erosion and siltation cycles, while most sections of the coast experiences clear seasonal fluctuations, with accretion typically occurring during summer and erosion occurring in winter. El Niño–Southern Oscillation (ENSO) cycles drive changes in parameters including significant wave height, mean wave period, wave energy flux, and mean wave direction, leading to long-term changes in wave climate. The multi-scale behavior of the sandy shoreline responds distinctly to the ongoing changes in wave climate triggered by ENSO viability, with El Niño events typically resulting in accretion and La Niña periods causing erosion. Notably, mean wave direction is the metric most closely linked to changes in the shoreline among all the others. In conclusion, the interplay of escalating anthropogenic activities, natural processes, and climate change contributes to the long-term evolution of sandy shorelines. We believe this study can offer a scientific reference for erosion prevention and management strategies of sandy beaches, based on the analysis presented above.

The A* algorithm is an effective method for path planning; however, it has certain drawbacks, such as a high number of turns, low planning efficiency, and redundant searches. To address these issues, this paper proposes an improved bidirectional A* global path planning algorithm based on a variable neighborhood search strategy, named VNS-BA*. The new algorithm first employs an 8-11-13 neighborhood search method for node expansion. Then, the bidirectional search strategy is optimized by using the current nodes of the opposite path and the global target point, enabling the two paths to meet in the middle of the map. Finally, redundant turns are removed from the path, and cubic spline interpolation is applied to achieve local smoothing at the turns. The effectiveness of the improved algorithm was validated on different maps and compared with A* and its three derived improved versions. The simulation results indicate that VNS-BA* shows significant improvements in terms of the number of path turns, turn angles, and planning efficiency.

Salt cavern flow batteries (SCFBs) are an energy storage technology that utilize salt caverns to store electrolytes of flow batteries with a saturated NaCl solution as the supporting electrolyte. However, the geological characteristics of salt caverns differ significantly from above-ground storage tanks, leading to complex issues in storing electrolytes within salt caverns. Therefore, investigating and summarizing these issues is crucial for the advancement of SCFB technology. This paper’s innovation lies in its comprehensive review of the current state and development trends in SCFBs both domestically and internationally. First, the current development status of SCFB energy storage technology both domestically and internationally is summarized. Then, eight main issues are proposed from the perspectives of salt cavern geological characteristics (tightness, conductivity, ions, and temperature) and electrolyte properties (selection, permeability, corrosion, and concentration). Finally, a novel SCFB system is proposed to address the most critical issue, which is the low concentration and uneven distribution of active materials in the current SCFB system. The review in this paper not only comprehensively summarizes the development status of SCFBs both domestically and internationally, but also points out the direction for the future research focussing on SCFBs.

Due to the impact of global warming, drought has caused serious damage to China’s ecological environment and social status. This article selects Laibin City in the Guangxi Zhuang Autonomous Region as the research area, utilizing multispectral remote sensing data as the data source and Landsat series image data for relevant preprocessing. It calculates the monthly normalized vegetation index (NDVI) and surface temperature (LST) data for Laibin City. Based on the ecological environment and surface coverage conditions of the research area, the ratio vegetation index (RVI), normalized vegetation moisture index (NDWI), temperature vegetation drought index (TVDI), and conditional vegetation temperature drought index (VTCI) were selected to calculate and invert the drought monitoring results of Laibin City. The drought monitoring results were obtained and overlaid with the vegetation area map to generate the vegetation drought monitoring results of Laibin City. Based on the climate, geography, and ecological characteristics of the monitored area in Laibin City, a specific analysis will be conducted to develop an appropriate TVDI index drought level, and generate vegetation drought level result maps for Laibin City in 2021, 2022, and 2023. Then, a detailed analysis of the vegetation drought situation in Laibin City is conducted according to time and space. Among them, in the past three years, the vegetation areas in Laibin City have experienced drought seasons mostly in summer and autumn. The interannual drought is mainly mild drought, and the proportion of areas with mild drought shows a relatively stable trend. In conclusion, TVDI proves to be a valuable tool for monitoring vegetation drought in Laibin City, offering insights for efficient water resource management strategies.

Chimeric antigen receptor (CAR) T cell therapy has demonstrated robust efficacy against hematological malignancies, but there are still some challenges regarding treating solid tumors, including tumor heterogeneity, antigen escape, and an immunosuppressive microenvironment. Here, we found that SNU398, a hepatocellular carcinoma (HCC) cell line, exhibited high expression levels of fibroblast activation protein (FAP) and Glypican 3 (GPC3), which were negatively correlated with patient prognosis. The HepG2 HCC cell line highly expressed GPC3, while the SNU387 cell line exhibited high expression of FAP. Thus, we developed bispecific CAR-T cells to simultaneously target FAP and GPC3 to address tumor heterogeneity in HCC. The anti-FAP-GPC3 bispecific CAR-T cells could recognize and be activated by FAP or GPC3 expressed by tumor cells. Compared with anti-FAP CAR-T cells or anti-GPC3 CAR-T cells, bispecific CAR-T cells achieved more robust activity against tumor cells expressing FAP and GPC3 in vitro. The anti-FAP-GPC3 bispecific CAR-T cells also exhibited superior antitumor efficacy and significantly prolonged the survival of mice compared with single-target CAR-T cells in vivo. Overall, the use of anti-FAP-GPC3 bispecific CAR-T cells is a promising treatment approach to reduce tumor recurrence caused by tumor antigen heterogeneity.

Abstract In recent years, increased species extinction and habitat loss have significantly reduced biodiversity, posing a serious threat to both nature and human survival. Environmental factors strongly influence bird distribution and diversity. The potential distribution patterns and species richness offer a conservation modeling framework for policymakers to assess the effectiveness of natural protected areas (PAs) and optimize their existing ones. Very few such studies have been published that cover a large and complete taxonomic group with fine resolution at regional scale. Here, using birds as a study group, the maximum entropy model (MaxEnt) was used to analyze the pattern of bird species richness in Jiangsu Province. Using an unparalleled amount of occurrence data, we created species distribution models (SDMs) for 312 bird species to explore emerging diversity patterns at a resolution of 1 km2. The gradient of species richness is steep, decreasing sharply away from water bodies, particularly in the northern part of Jiangsu Province. The migratory status and feeding habits of birds also significantly influence the spatial distribution of avian species richness. This study reveals that the regions with high potential bird species richness are primarily distributed in three areas: the eastern coastal region, the surrounding area of the lower reaches of the Yangtze River, and the surrounding area of Taihu Lake. Compared with species richness hotspots and existing PAs, we found that the majority of hotspots are well‐protected. However, only a small portion of the regions, such as coastal areas of Sheyang County in Yancheng City, as well as some regions along the Yangtze River in Nanjing and Zhenjiang, currently have relatively weak protection. Using stacked SDMs, our study reveals effective insights into diversity patterns, directly informing conservation policies and contributing to macroecological research advancements.

Inner Mongolia’s grassland is one of the most complete natural grasslands for ecological diversity and biodiversity conservation in the world. However, its degradation has seriously affected the plateau’s sustainable development and grassland restoration and reconstruction. To reveal the response of soil-plant synergistic relationship to different degrees of degradation, we selected three degrees of degradation (total coverage of vegetation:20%–30%, LD), moderate degradation (total coverage of vegetation:10%–20%, MD) and severe degradation (total coverage of vegetation:

In neural circuits, recurrent connectivity plays a crucial role in network function and stability. However, existing recurrent spiking neural networks (RSNNs) are often constructed by random connections without optimization. While RSNNs can produce rich dynamics that are critical for memory formation and learning, systemic architectural optimization of RSNNs is still an open challenge. We aim to enable systematic design of large RSNNs via a new scalable RSNN architecture and automated architectural optimization. We compose RSNNs based on a layer architecture called Sparsely-Connected Recurrent Motif Layer (SC-ML) that consists of multiple small recurrent motifs wired together by sparse lateral connections. The small size of the motifs and sparse inter-motif connectivity leads to an RSNN architecture scalable to large network sizes. We further propose a method called Hybrid Risk-Mitigating Architectural Search (HRMAS) to systematically optimize the topology of the proposed recurrent motifs and SC-ML layer architecture. HRMAS is an alternating two-step optimization process by which we mitigate the risk of network instability and performance degradation caused by architectural change by introducing a novel biologically-inspired “self-repairing” mechanism through intrinsic plasticity. The intrinsic plasticity is introduced to the second step of each HRMAS iteration and acts as unsupervised fast self-adaptation to structural and synaptic weight modifications introduced by the first step during the RSNN architectural “evolution.” We demonstrate that the proposed automatic architecture optimization leads to significant performance gains over existing manually designed RSNNs: we achieve 96.44% on TI46-Alpha, 94.66% on N-TIDIGITS, 90.28% on DVS-Gesture, and 98.72% on N-MNIST. To the best of the authors' knowledge, this is the first work to perform systematic architecture optimization on RSNNs.

Abstract As one of the major causes of antimicrobial resistance, β‐lactamase develops rapidly among bacteria. Detection of β‐lactamase in an efficient and low‐cost point‐of‐care testing (POCT) way is urgently needed. However, due to the volatile environmental factors, the quantitative measurement of current POCT is often inaccurate. Herein, we demonstrate an artificial intelligence (AI)‐assisted mobile health system that consists of a paper‐based β‐lactamase fluorogenic probe analytical device and a smartphone‐based AI cloud. An ultrafast broad‐spectrum fluorogenic probe (B1) that could respond to β‐lactamase within 20 s was first synthesized, and the detection limit was determined to be 0.13 nmol/L. Meanwhile, a three‐dimensional microfluidic paper‐based analytical device was fabricated for integration of B1. Also, a smartphone‐based AI cloud was developed to correct errors automatically and output results intelligently. This smart system could calibrate the temperature and pH in the β‐lactamase level detection in complex samples and mice infected with various bacteria, which shows the problem‐solving ability in interdisciplinary research, and demonstrates potential clinical benefits.

A metal-free and solvent-free method for the synthesis of quinazolin-4(3H)-ones is proposed by condensation cyclization of 2-aminobenzamides and aldehydes using 1-butyl-3-methylimida-zolium tetrafluoride ([Bmim]BF4) as ionic liquid catalyst. In this reaction, [Bmim]BF4 acts as both a catalyst and a solvent without need for additional catalysts and solvents. This method exhibits favorable functional group tolerance in substrates and affords a series of desired products in moderate to excellent yields. In addition, it is noteworthy that the reaction yield is still as high as 87% after [Bmim]BF4 is recycled at least four times.

Abstract This paper investigates the design of transmit beamforming in an integrated sensing and communication system, where an unmanned aerial vehicle (UAV) equipped with a uniform linear array (ULA) transmits combined information‐carrying and dedicated sensing signals to perform multi‐user communication and simultaneously sense potential targets. First, the transmit beamforming design is formulated as a series of non‐convex optimisation problems, and then jointly design the information and sensing beamforming to maximise the minimum communication rate under an optimised UAV deployment location, subject to the sensing beampattern gain requirements and the limited transmit power of the UAV. However, due to the application of ULA on the UAV, the formulated problems are highly non‐convex and difficult to solve optimally. To address the aforementioned issue, an efficient algorithm is proposed to find suboptimal yet high‐quality solutions. This is achieved by adopting the successive convex approximation and semidefinite relaxation. The numerical results confirm the effectiveness of the proposed algorithm and demonstrate that the transmit beamforming design achieves a balance between communication and sensing performance.

Abstract In this work, 2D ferromagnetic M3GeTe2 (MGT, M = Ni/Fe) nanosheets with rich atomic Te vacancies (2D‐MGTv) are demonstrated as efficient OER electrocatalyst via a general mechanical exfoliation strategy. X‐ray absorption spectra (XAS) and scanning transmission electron microscope (STEM) results validate the dominant presence of metal‐O moieties and rich Te vacancies, respectively. The formed Te vacancies are active for the adsorption of OH* and O* species while the metal‐O moieties promote the O* and OOH* adsorption, contributing synergistically to the faster oxygen evolution kinetics. Consequently, 2D‐Ni3GeTe2v exhibits superior OER activity with only 370 mV overpotential to reach the current density of 100 mA cm−2 and turnover frequency (TOF) value of 101.6 s−1 at the overpotential of 200 mV in alkaline media. Furthermore, a 2D‐Ni3GeTe2v‐based anion‐exchange membrane (AEM) water electrolysis cell (1 cm2) delivers a current density of 1.02 and 1.32 A cm−2 at the voltage of 3 V feeding with 0.1 and 1 m KOH solution, respectively. The demonstrated metal‐O coordination with abundant atomic vacancies for ferromagnetic M3GeTe2 and the easily extended preparation strategy would enlighten the rational design and fabrication of other ferromagnetic materials for wider electrocatalytic applications.

This paper proposes an improved TD3 (Twin Delayed Deep Deterministic Policy Gradient) algorithm to address the flaws of low success rate and slow training speed, when using the original TD3 algorithm in mobile robot path planning in dynamic environment. Firstly, prioritized experience replay and transfer learning are introduced to enhance the learning efficiency, where the probability of beneficial experiences being sampled in the experience pool is increased, and the pre-trained model is applied in an obstacle-free environment as the initial model for training in a dynamic environment. Secondly, dynamic delay update strategy is devised and OU noise is added to improve the success rate of path planning, where the probability of missing high-quality value estimate is reduced through changing the delay update interval dynamically, and the correlated exploration of the mobile robot inertial navigation system in the dynamic environment is temporally improved. The algorithm is tested by simulation where the Turtlebot3 robot model as a training object, the ROS melodic operating system and Gazebo simulation software as an experimental environment. Meanwhile, the result shows that the improved TD3 algorithm has a 16.6 % increase in success rate and a 23.5 % reduction in algorithm training time. A generalization experiment was designed finally, and it indicates that superior generation performance has been acquired in mobile robot path planning with continuous action spaces through the improved TD3 algorithm.

Post-stroke cognitive impairment (PSCI) is a clinical syndrome characterized by cognitive deficits that manifest following a stroke and persist for up to 6 months post-event. This condition is grave, severely compromising patient quality of life and longevity, while also imposing substantial economic burdens on societies worldwide. Despite significant advancements in identifying risk factors for PSCI, research into its underlying mechanisms and therapeutic interventions remains inadequate. Microglia, the brain’s primary immune effector cells, are pivotal in maintaining, nurturing, defending, and repairing neuronal function, a process intrinsically linked to PSCI’s progression. Thus, investigating microglial activation and mechanisms in PSCI is crucial. This paper aims to foster new preventive and therapeutic approaches for PSCI by elucidating the roles, mechanisms, and characteristics of microglia in the condition.

ObjectiveGastric cancer (GC) is the world’s third-leading cause of cancer-related mortality; the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers for early diagnosis and immune therapy response prediction. Here, we aim to discover the connection between chemokine ligand 14 (CCL14) expression in the gastric tumor microenvironment (TME) and its clinical significance and investigate its correlation with immune cell infiltration.MethodsWe assessed CCL14 mRNA expression and its interrelation with tumor-infiltrating immune cells (TILs) using bioinformatics analysis in gastric cancer. CCL14 protein expression, TILs, and immune checkpoints were detected by multiple immunohistochemistry analyses in gastric cancer tissue microarrays. Then, we conducted statistics analysis to determine the association between CCL14-related patient survival and immune cell infiltration (p < 0.05).ResultsWe found that the CCL14 protein was separately expressed in the carcinoma cells and TILs in stomach cancer tissues. The CCL14 protein was related to tumor differentiation and tumor depth and positively correlated with the presentation of LAG3 and PD-L1 in gastric cancer cells. In addition, the CCL14 protein in the TILs of gastric cancer tissues was related to Lauren’s type cells, T cells (CD4+ and CD8+), and CD68+ macrophages in the TME. Kaplan–Meier survival and multivariate analyses showed that the CCL14 expression in gastric cancer cells was an independent prognostic factor.ConclusionOur study illustrated that CCL14 is a poor prognosis biomarker in gastric cancer, which may be associated with the potential for immunotherapy.

Hypertrophic cardiomyopathy (HCM) is a very prevalent inherited disease with a wide global distribution and a prevalence rate of approximately 0.2% in the general population. Left ventricular hypertrophy (LVH) caused by sarcomere mutation is the primary reason of HCM. The histopathology feature is that cardiomyocyte hypertrophy, myocyte disorder and myocardial fibrosis lead to diminished diastolic function, left ventricular outflow tract obstruction (LVOTO) and arrhythmia, all of which result in serious cardiac complications. Previously, HCM was considered a malignant disease that was almost untreatable. With the improvement of medical standards and increasing awareness of HCM, it has become a highly treatable disease in contemporary times, with a significant decrease in mortality rates. However, there are still significant unmet requirements in the therapy of HCM. This paper draws on more than 100 references from the past four decades and summarizes current advances in the treatment of HCM. The article will review the pathogenesis and types, recent development in pharmacotherapy, invasive treatments and gene therapies, as well as dilemma and future development of HCM.

Perfect vector beams with radius independent of topological charges have garnered significant interest owing to their unique capabilities in optical manipulation, microscopy imaging, and laser micro-machining. However, their polarization state is limited to four modes, restricting their information capacity and re-usability. To address this, we introduce double-ring perfect vectorial vortex beams that leverage the axicon phase to theoretically generate double-ring structures through a Fourier transform. By applying a transformation matrix and introducing a cross phase, we can manipulate the beam distribution. This approach is expected to enhance for development of particle capture and optical communications.

Summary: Background: A variety of symptoms, particularly cognitive, psychiatric and neurological symptoms, may persist for a long time among individuals recovering from COVID-19. However, the underlying mechanism of these brain abnormalities remains unclear. This study aimed to investigate the long-term neuroimaging effects of COVID-19 infection on brain functional activities using resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Fifty-two survivors 27 months after infection (mild-moderate group: 25 participants, severe-critical: 27 participants), from our previous community participants, along with 35 healthy controls, were recruited to undergo fMRI scans and comprehensive cognitive function measurements. Participants were evaluated by subjective assessment of Cognitive Failures Questionnaire-14 (CFQ-14) and Fatigue Scale-14 (FS-14), and objective assessment of Montreal Cognitive Assessment (MoCA), N-back, and Simple Reaction Time (SRT). Each had rs-fMRI at 3T. Measures such as the amplitude of low-frequency fluctuation (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) were calculated. Findings: Compared with healthy controls, survivors of mild-moderate acute symptoms group and severe-critical group had a significantly higher score of cognitive complains involving cognitive failure and mental fatigue. However, there was no difference of cognitive complaints between two groups of COVID-19 survivors. The performance of three groups was similar on the score of MoCA, N-back and SRT. The rs-fMRI results showed that COVID-19 survivors exhibited significantly increased ALFF values in the left putamen (PUT.L), right inferior temporal gyrus (ITG.R) and right pallidum (PAL.R), while decreased ALFF values were observed in the right superior parietal gyrus (SPG.R) and left superior temporal gyrus (STG.L). Additionally, decreased ReHo values in the right precentral gyrus (PreCG.R), left postcentral gyrus (PoCG.L), left calcarine fissure and surrounding cortex (CAL.L) and left superior temporal gyrus (STG.L). Furthermore, significant negative correlations between the ReHo values in the STG.L, and CFQ-14 and mental fatigue were found. Interpretation: This long-term study suggests that individuals recovering from COVID-19 continue to experience cognitive complaints, psychiatric and neurological symptoms, and brain functional alteration. The rs-fMRI results indicated that the changes in brain function in regions such as the putamen, temporal lobe, and superior parietal gyrus may contribute to cognitive complaints in individuals with long COVID even after 2-year infection. Funding: The National Programs for Brain Science and Brain-like Intelligence Technology of China, the National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality of China, and the National Key Research and Development Program of China.

Microorganisms have a significant role in regulating the absorption and transportation of Cd in the soil-plant system. However, the mechanism by which key microbial taxa play a part in response to the absorption and transportation of Cd in rice under Cd stress requires further exploration. In this study, the cadmium-tolerant endophytic bacterium Herbaspirillum sp. R3 (R3) and Fe-Mn-modified biochar (Fe-Mn) were, respectively, applied to cadmium-contaminated rice paddies to investigate the effects of key bacterial taxa in the soil-rice system on the absorption and transportation of Cd in rice under different treatments. The results showed that both R3 and Fe-Mn treatments considerably decreased the content of cadmium in roots, stems and leaves of rice at the peak tillering stage by 17.24–49.28% in comparison to the control (CK). The cadmium content reduction effect of R3 treatment is better than that of Fe-Mn treatment. Further analysis revealed that the key bacterial taxa in rice roots under R3 treatment were Sideroxydans and Actinobacteria, and that their abundance showed a substantial positive correlation and a significant negative correlation with the capacity of rice roots to assimilate Cd from the surroundings, respectively. The significant increase in soil pH under Fe-Mn treatment, significant reduction in the relative abundances of Acidobacteria, Verrucomicrobia, Subdivision3 genera incertae sedis, Sideroxydans, Geobacter, Gp1, and Gp3, and the significant increase in the relative abundance of Thiobacillus among the soil bacterial taxa may be the main reasons for the decrease in available Cd content of the soil. In addition, both the R3 and Fe-Mn treatments showed some growth-promoting effects on rice, which may be related to their promotion of transformations of soil available nutrients. This paper describes the possible microbial mechanisms by which strain R3 and Fe-Mn biochar reduce Cd uptake in rice, providing a theoretical basis for the remediation of Cd contamination in rice and soil by utilizing key microbial taxa.

Study region: The Upper and Middle Reaches of the Yellow River Basin Study focus: Taking the upper and middle reaches of the Yellow River as the research area, 15 types of models developed by the fusion of four multi-source products of GLDAS-Noah V2.1, ERA5-Land, GLEAM v3.6a and GLEAM v3.6b were assessed. Based on the fusion results of actual evapotranspiration(ET), the key factors that drive the spatial variation in actual evapotranspiration was explored, the land surface parameters of Fu formula in different watersheds were estimated, the relationship between land surface parameters and ecological construction measures was established, and the contribution rate of precipitation, potential evapotranspiration, NDVI and check-dam control area to ET change was quantified. New hydrological insights for the region: The multi-year average actual evapotranspiration from 2003 to 2018 in the watersheds controlled by Tangnaihai, Lanzhou, Toudaoguai, Longmen and Tongguan is 378, 368, 346, 368 and 410 mm/year, respectively. The optimal fusion of the actual evapotranspiration is employing the Extreme Learning Machine to fuse the GLDAS-Noah V2.1 and GLEAM v3.6b products. The long-term actual evapotranspiration estimated from the Fu formula incorporating the ecological construction measures have high agreement with the fusion results. The impact of soil moisture on the spatial variation of actual evapotranspiration is significant. The contribution rate of precipitation to ET change is the highest, followed by NDVI, potential evapotranspiration and check-dam control area.

Enhancing the valorization of fruit processing by-products is pivotal for advancing the industry. Black mulberry wine residues, a by-product, contains some bioactive compounds, yet its antioxidant and anticancer potentials remain unverified. In this study, ultrasound-assisted enzymatic extraction was optimized by response surface methodology to obtain the flavonoids extracts from black mulberry wine residues, whose antioxidant capacity and anti-cancer activity in vitro was investigated. The results showed that under the optimal extraction conditions (enzyme ratio at pectinase:cellulose = 2:1, mixed enzyme concentration 0.31 mg/mL, enzymatic hydrolysis temperature 55.35 °C, enzymatic hydrolysis time 79.03 min, and ultrasonic time 22.71 min), the extracts from black mulberry wine residues (BMWR-E) reached 5.672 mg/g. At a concentration of 1.2 mg/mL, BMWR-E exhibited strong DPPH and hydroxyl radical scavenging activities. At a concentration of 2.5 mg/mL, BMWR-E showed a strong superoxide anion radical scavenging capacity, with no significant distinction compared to the positive control group (Vitamin C) (p > 0.05). Cell viability assay results showed that BMWR-E was non-toxic to normal BRL-3A cells when applied at concentrations of 0.1–0.3 mg/mL for an incubation period of 24 h, but BMWR-E exhibited the ability to inhibit the proliferation of HepG2 cells. At concentrations of 0.2 mg/mL and above, BMWR-E could induce late apoptosis of HepG2 cells by increasing the protein expression levels of Bax, caspase-3, and caspase-12, reducing the protein expression levels of Bcl-2, inducing cell cycle arrest at G0/G1 phase, thereby inhibiting the proliferation of HepG2 cells. The bioactive properties make BMWR-E possess potential in developing new antioxidants and anti-cancer agents, which would significantly enhance the economic worth of agricultural by-products in product processing. This research can improve the utilization rate of agricultural product processing by-products and protect the environment.

BackgroundThe association between birth weight and childhood body mass index (BMI) and frailty has been extensively studied, but it is currently unclear whether this relationship is causal.MethodsWe utilized a two-sample Mendelian randomization (MR) methodology to investigate the causal effects of birth weight and childhood BMI on the risk of frailty. Instrumental variables (p 0.05).ConclusionThis MR study provides evidence supporting a causal relationship between lower birth weight, higher childhood BMI, and an increased risk of frailty.

Objective A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy. Methods Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years. Results The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential. Conclusions For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.

Objective: Preeclampsia is a serious pregnancy complication that jeopardizes the health of both the mother and the fetus. Platelet parameters are closely linked to the severity of preeclampsia. This study aimed to assess the diagnostic potential of platelet parameters in the early second trimester for the detection of preeclampsia. Methods: A total of 840 participants from the Affiliated Hospital of Jining Medical College were included in the study, consisting of 327 healthy pregnant women, 209 with mild preeclampsia, and 304 with severe preeclampsia. General clinical data and platelet parameters for these three groups of pregnant women were collected, and differences among them were compared. In addition, univariate analysis and logistic regression were used to identify preeclampsia risk factors, and receiver operating characteristic curve analysis was conducted to assess the predictive value of platelet parameters. Results: Platelet count was not found to significantly differ between the healthy and preeclampsia groups. However, mean platelet volume, platelet distribution width (PDW), and platelet?large cell ratios (P-LCR) were observed to be significantly higher in the preeclampsia group than the healthy group. After adjusting for confounding factors (such as age, gestational week at blood sampling, systolic and diastolic blood pressure, and body mass index during the second trimester), it was determined that PDW and P-LCR could be considered effective predictors of preeclampsia. Conclusion: In clinical practice, P-LCR and PDW hold potential predictive value for preeclampsia.

BackgroundFood waste remains a major problem for the world and food security. Despite the fact that consumers are significant producers of food waste, little research attention has been paid to college students. The present study aimed to assess food waste and the influence factors among college students. Additionally, the goal was to improve college students’ food waste attitudes and behaviors through labor education.MethodsThrough an online questionnaire survey, 407 college students from three universities were asked about food waste; 27 students of them were randomly selected as the research object, and labor practice was carried out in groups in the student cafeteria. Mann–Whitney U test was performed to show food waste behavior of college students and logistical regression analysis was used to analyze the factors affecting food waste behavior.ResultsThe results indicated that the food waste is more serious among college students in East China, senior or female students, BMI plays a positive role in food waste among college students, while monthly consumption and peers waste play a negative role in food waste. After participating in the labor education, the students’ views and practices toward their peer’s food waste have improved.ConclusionThe implementation of labor education in college canteens is conducive to the establishment of a correct outlook on labor as well as saving consciousness among college students, and to the formation of a social consciousness of saving.

BackgroundThe relationship between 24-hour rest-activity rhythms (RARs) and risk for dementia or mild cognitive impairment (MCI) remains an area of growing interest. Previous studies were often limited by small sample sizes, short follow-ups, and older participants. More studies are required to fully explore the link between disrupted RARs and dementia or MCI in middle-aged and older adults. ObjectiveWe leveraged the UK Biobank data to examine how RAR disturbances correlate with the risk of developing dementia and MCI in middle-aged and older adults. MethodsWe analyzed the data of 91,517 UK Biobank participants aged between 43 and 79 years. Wrist actigraphy recordings were used to derive nonparametric RAR metrics, including the activity level of the most active 10-hour period (M10) and its midpoint, the activity level of the least active 5-hour period (L5) and its midpoint, relative amplitude (RA) of the 24-hour cycle [RA=(M10-L5)/(M10+L5)], interdaily stability, and intradaily variability, as well as the amplitude and acrophase of 24-hour rhythms (cosinor analysis). We used Cox proportional hazards models to examine the associations between baseline RAR and subsequent incidence of dementia or MCI, adjusting for demographic characteristics, comorbidities, lifestyle factors, shiftwork status, and genetic risk for Alzheimer's disease. ResultsDuring the follow-up of up to 7.5 years, 555 participants developed MCI or dementia. The dementia or MCI risk increased for those with lower M10 activity (hazard ratio [HR] 1.28, 95% CI 1.14-1.44, per 1-SD decrease), higher L5 activity (HR 1.15, 95% CI 1.10-1.21, per 1-SD increase), lower RA (HR 1.23, 95% CI 1.16-1.29, per 1-SD decrease), lower amplitude (HR 1.32, 95% CI 1.17-1.49, per 1-SD decrease), and higher intradaily variability (HR 1.14, 95% CI 1.05-1.24, per 1-SD increase) as well as advanced L5 midpoint (HR 0.92, 95% CI 0.85-0.99, per 1-SD advance). These associations were similar in people aged 70 years, and in non–shift workers, and they were independent of genetic and cardiovascular risk factors. No significant associations were observed for M10 midpoint, interdaily stability, or acrophase. ConclusionsBased on findings from a large sample of middle-to-older adults with objective RAR assessment and almost 8-years of follow-up, we suggest that suppressed and fragmented daily activity rhythms precede the onset of dementia or MCI and may serve as risk biomarkers for preclinical dementia in middle-aged and older adults.

How to assess the effect of ecosystem restoration is a trending topic with all the restoration projects and ecosystem function studies in recent years. Although many studies have used different indicators and methods to evaluate ecosystem restoration effects, it needs a lot of site works to acquire the data. Low-function Platycladus orientalis forest restoration program in Beijing mountainous area has been started since 2002, in this study, the understory species of 92 plots were investigated and recorded. We assumed that the effect of ecosystem restoration would improve site conditions, especially for the soil conditions which might lead to the appearance of new species. The relationship between understory species and eleven site condition factors was elucidated by means of canonical correspondence analysis (CCA), further, specific species were chosen to represent the improvement and possible growth areas of specific species was predicted by Maximum Entropy model. Results shown that Spiraea pubescens, Deutzia parviflora, Chrysanthemum chanetii, Themeda triandra, Oplismenus undulatifolius were the main understory species which were sensitive to environmental factors, and their distribution were related to soil factors closely. The species of Spiraea pubescens, Chrysanthemum chanetii, Oplismenus undulatifolius had strong indication to soil nutrient, the appearances would happen when the comprehensive index of soil nutrient was above 81,64 and 61 respectively. The appearance of Chrysanthemum chanetii and Oplismenus undulatifolius would indicate that the soil nutrient level was in or above the range of medium, and the appearance of Spiraea pubescens would mean that the soil nutrient level was in or above the range of high in low-function Platycladus orientalis forest of Beijing mountainous area. Our study indicates that the specific species could as an indicator to reflect or evaluate the ecosystem restoration effect.

Abstract Quality controlling for capsule endoscopic images can be completed with the assistance of artificial intelligence, but the labeling process is time‐consuming. Domain adaption is a robust tool for cross‐domain learning to reach a consistent target. Current research aims to study the feasibility and effectiveness of domain adaption from ordinary endoscopic images to capsule endoscopic images in quality controlling. Dynamic adversarial adaptation network (DAAN) was trained to identify low‐quality images using ordinary endoscopic images with corresponding labels (source domain with supervision) and capsule endoscopic images without corresponding labels (target domain without supervision) so that image quality controlling can be transferred from ordinary to capsule endoscopic images. 62,850 images from capsule endoscopy and 17,434 images from ordinary endoscopy were included in developing deep learning models. In internal cross‐validation, DAAN achieved an average area under receiver operating characteristic curve (AUROC) of 0.8638 (95% confidence interval [CI] 0.6753–1.0000) in filtering low‐quality images for capsule endoscopic images, compared with CNN B/16 and L/32, which were also trained with ordinary endoscopic images with corresponding labels. 18,636 images from 355 patients who received capsule endoscopy were prospectively collected. The AUROC of DAAN reached 0.9471 (95% CI 0.9428–0.9511), which surpassed CNN (0.8570 and 95% CI [0.8529–0.8608]) and ViT (L/32: 0.8183 and 95% CI [0.8143–0.8220] and B/16: 0.7779 and 95% CI [0.7960–0.8036]). Domain adaption can complete image quality controlling task in capsule endoscopic images with the supervision of ordinary endoscopic images, whose quantity is smaller so that the annotation workload can be alleviated.

Gut dysbiosis is closely associated with the burden of chronic kidney disease (CKD), and strategies such as prebiotic supplementation have been suggested to ameliorate CKD and related complications. We hypothesized that prebiotic-soluble dietary fiber (SDF) complexes could ameliorate biochemical parameters, gut microbiota and microbial metabolites of CKD. Here, forty non-dialyzed CKD patients in stage 3 to 5 were randomized to receive either SDF or placebo for 30 days. As expected, SDF intervention reduced serum total cholesterol levels (P＜0.05) and plasma interleukin (IL)-8 levels (P＜0.05). No profound changes in the diversity or community structure of the gut microbiota were observed in SDF group, but the composition of the gut microbiota was altered. Moreover, the concentration of propionate of short-chain fatty acids (SCFAs) increased significantly following SDF intervention (P＜0.05). SDF supplementation seems to be a promising strategy to improve inflammation, gut microbiology and derived metabolites.

Net primary productivity (NPP) of terrestrial ecosystems serves as a crucial carbon sink, playing a significant role in mitigating climate change. This study, focusing on the Yangtze River Economic Belt (YREB), a key area for both economic development and ecological conservation in China, evaluates the temporal and spatial changes in regional NPP and its responses to climatic factors against the backdrop of global change. Utilizing long-term NPP and meteorological grid data from 1981 to 2017, we analyzed the annual change patterns of NPP and its linear and nonlinear responses to climatic factors using copula functions. Our findings indicate that 57.00 % of the YREB has experienced a significant increase in NPP, with the most substantial decreases observed in Shanghai and its surrounding areas (P

The understanding of the function of perivascular adipose tissue (PVAT) in vascular aging has significantly changed due to the increasing amount of information regarding its biology. Adipose tissue surrounding blood vessels is increasingly recognized as a key regulator of vascular disorders. It has significant endocrine and paracrine effects on the vasculature and is mediated by the production of a variety of bioactive chemicals. It also participates in a number of pathological regulatory processes, including oxidative stress, immunological inflammation, lipid metabolism, vasoconstriction, and dilation. Mechanisms of homeostasis and interactions between cells at the local level tightly regulate the function and secretory repertoire of PVAT, which can become dysregulated during vascular aging. The PVAT secretion group changes from being reducing inflammation and lowering cholesterol to increasing inflammation and increasing cholesterol in response to systemic or local inflammation and insulin resistance. In addition, the interaction between the PVAT and the vasculature is reciprocal, and the biological processes of PVAT are directly influenced by the pertinent indicators of vascular aging. The architectural and biological traits of PVAT, the molecular mechanism of crosstalk between PVAT and vascular aging, and the clinical correlation of vascular age-related disorders are all summarized in this review. In addition, this paper aims to elucidate and evaluate the potential benefits of therapeutically targeting PVAT in the context of mitigating vascular aging. Furthermore, it will discuss the latest advancements in technology used for targeting PVAT.

The Chinese mitten crab is an important aquaculture product in China. Currently, rice-crab co-culture is a novel model that can realize positive interactions. The feed for Chinese mitten crabs cultured in rice fields should be distinguished from other modes, since their culture environment is unique. Therefore, this study designed three experimental groups that were fed 15% (RC1), 25% (RC2), and 35% (RC3) protein, with a natural bait group (RC0) without artificial feeding as the control. The protein nutritional requirements of Chinese mitten crabs in a rice-crab co-culture model were investigated by exploring the indicators of growth performance, nutrient composition, immunity, antioxidant capacity, and economic benefits of different groups. Through a comprehensive discussion of one-way analysis of variance and regression analysis of the data, we obtained the following results: feeds with high-level protein improved the growth performance, quality, and economic benefits of Chinese mitten crabs and reduced their exposure to oxidative stress. Specifically, the contents of major nutrients and flavor-presenting substances, such as free amino acids (FAA), nucleotides, and essential amino acids (EAA), in the edible parts of female crabs in the 35% protein group were significantly higher than those in all other groups. Male crabs fed 25% − 28.08% protein diets showed higher production performance and FAA content. In conclusion, the optimal dietary protein levels for male and female crabs reared in rice fields are different: they are 35% for females, and at least 25% for males. Therefore, for actual crab production, male and female crabs could be cultured separately using different protein baits to reduce bait costs and achieve green and sustainable development.

Soil hydraulic properties are essential for understanding soil hydrological and erosion processes. The importance of roots on soil hydraulic parameters has been widely recognized, but current studies have focused mainly on the root effect of a single plant species. However, few studies have been carried out to investigate the effect of mixed plant roots on soil hydraulic parameters. Undisturbed soil samples were collected from three natural sampling sites with single plant types and four sites with mixed plant types. Both soil hydraulic parameters were measured: soil saturated hydraulic conductivity (Ks) and soil saturated water content (SW). Then the root effects on Ks and SW were subsequently evaluated. The results showed that the Ks and SW at the sites with mixed plants were higher than those at the sites with a single plant species. At all the sites, Ks and SW both exhibited a decreasing-increasing-decreasing trend with increasing root density. The critical root density for the above change was quantified. When fibrous roots were mixed with tap roots, Ks was mainly affected by tap roots, while SW was mainly affected by fibrous roots. The influence of roots on Ks and SW was mainly achieved by affecting soil organic matter, not by directly affecting Ks and SW. Based on the root density, the herbaceous coverage with optimal saturated hydraulic conductivity and water content was estimated to be 66.71%.

ObjectiveThe baseline urinary albumin/creatinine ratio (uACR) has been proven to be significantly associated with the risk of major adverse cardiac events (MACE). However, data on the association between the longitudinal trajectory patterns of uACR, changes in glycated hemoglobin A1c (HbA1c), and the subsequent risk of MACE in patients with diabetes are sparse.MethodsThis is a retrospective cohort study including 601 patients with type 2 diabetes mellitus (T2DM; uACR < 300 mg/g) admitted to The First Hospital of Shanxi Medical University and The Second Hospital of Shanxi Medical University from January 2015 to December 2018. The uACR index was calculated as urinary albumin (in milligrams)/creatinine (in grams), and latent mixed modeling was used to identify the longitudinal trajectory of uACR during the exposure period (2016–2020). The deadline for follow-up was December 31, 2021. The primary outcome was the MACE [a composite outcome of cardiogenic death, hospitalization related to heart failure (HHF), non-fatal acute myocardial infarction, non-fatal stroke, and acute renal injury/dialysis indications]. The Kaplan–Meier survival analysis curve was used to compare the risk of MACE among four groups, while univariate and multivariate Cox proportional hazards models were employed to calculate the hazard ratio (HR) and 95% confidence interval (CI) for MACE risk among different uACR or HbA1c trajectory groups. The predictive performance of the model, both before and after the inclusion of changes in the uACR and HbA1c, was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC).ResultsFour distinct uACR trajectories were identified, namely, the low-stable group (uACR = 5.2–38.3 mg/g, n = 112), the moderate-stable group (uACR = 40.4–78.6 mg/g, n = 229), the high-stable group (uACR = 86.1–153.7 mg/g, n = 178), and the elevated-increasing group (uACR = 54.8–289.4 mg/g, n = 82). In addition, five distinct HbA1c trajectories were also identified: the low-stable group (HbA1c = 5.5%–6.8%, n = 113), the moderate-stable group (HbA1c = 6.0%–7.9%, n = 169), the moderate-decreasing group (HbA1c = 7.4%–6.1%, n = 67), the high-stable group (HbA1c = 7.7%–8.9%, n = 158), and the elevated-increasing group (HbA1c = 8.4%–10.3%, n = 94). Compared with the low-stable uACR group, patients in the high-stable and elevated-increasing uACR groups were more likely to be older, current smokers, and have a longer DM course, higher levels of 2-h plasma glucose (PG), HbA1c, N-terminal pro-B-type natriuretic peptide (NT-proBNP), uACR, and left ventricular mass index (LVMI), while featuring a higher prevalence of hypertension and a lower proportion of β-receptor blocker treatment (p < 0.05). During a median follow-up of 45 months (range, 24–57 months), 118 cases (19.6%) of MACE were identified, including 10 cases (1.7%) of cardiogenic death, 31 cases (5.2%) of HHF, 35 cases (5.8%) of non-fatal acute myocardial infarction (AMI), 18 cases (3.0%) of non-fatal stroke, and 24 cases (4.0%) of acute renal failure/dialysis. The Kaplan–Meier survival curve showed that, compared with that in the low-stable uACR group, the incidence of MACE in the high-stable (HR = 1.337, 95% CI = 1.083–1.652, p = 0.007) and elevated-increasing (HR = 1.648, 95% CI = 1.139–2.387, p = 0.009) uACR groups significantly increased. Similar results were observed for HHF, non-fatal AMI, and acute renal injury/dialysis indications (p < 0.05). The multivariate Cox proportional hazards models indicated that, after adjusting for potential confounders, the HRs for the risk of MACE were 1.145 (p = 0.132), 1.337 (p = 0.007), and 1.648 (p = 0.009) in the moderate-stable, high-stable, and elevated-increasing uACR groups, respectively. In addition, the HRs for the risk of MACE were 1.203 (p = 0.028), 0.872 (p = 0.024), 1.562 (p = 0.033), and 2.218 (p = 0.002) in the moderate-stable, moderate-decreasing, high-stable, and elevated-increasing groups, respectively. The ROC curve showed that, after adding uACR, HbA1c, or both, the AUCs were 0.773, 0.792, and 0.826, which all signified statistically significant improvements (p = 0.021, 0.035, and 0.019, respectively).ConclusionA long-term elevated uACR is associated with a significantly increased risk of MACE in patients with diabetes. This study implies that regular monitoring of uACR could be helpful in identifying diabetic patients with a higher risk of MACE.

Introduction Surgical patients over 70 experience postoperative delirium (POD) complications in up to 50% of procedures. Sleep/circadian disruption has emerged as a potential risk factor for POD in epidemiological studies. This protocol presents a single-site, prospective observational study designed to examine the relationship between sleep/circadian regulation and POD and how this association could be moderated or mediated by Alzheimer’s disease (AD) pathology and genetic risk for AD.Methods and analysis Study staff members will screen for eligible patients (age ≥70) seeking joint replacement or spinal surgery at Massachusetts General Hospital (MGH). At the inclusion visit, patients will be asked a series of questionnaires related to sleep and cognition, conduct a four-lead ECG recording and be fitted for an actigraphy watch to wear for 7 days before surgery. Blood samples will be collected preoperatively and postoperatively and will be used to gather information about AD variant genes (APOE-ε4) and AD-related pathology (total and phosphorylated tau). Confusion Assessment Method-Scale and Montreal Cognitive Assessment will be completed twice daily for 3 days after surgery. Seven-day actigraphy assessments and Patient-Reported Outcomes Measurement Information System questionnaires will be performed 1, 3 and 12 months after surgery. Relevant patient clinical data will be monitored and recorded throughout the study.Ethics and dissemination This study is approved by the IRB at MGH, Boston, and it is registered with the US National Institutes of Health on ClinicalTrials.gov (NCT06052397). Plans for dissemination include conference presentations at a variety of scientific institutions. Results from this study are intended to be published in peer-reviewed journals. Relevant updates will be made available on ClinicalTrials.gov.Trial registration number NCT06052397.

Bretschneidera sinensis is a monotypic species of rare and tertiary relic trees mainly distributed in China. B. sinensis is a potentially valuable horticultural plant, which has significant ornamental and research value, and is a crucial tool for the study of phylogeography. The artificial cultivation of B. sinensis is of great scientific value and practical significance. In this study, we developed a direct organogenesis process of B. sinensis using mature zygotic embryos as initial materials. The highest sterile germination induction (54.5%) from the mature zygotic embryo was obtained in a Murashige and Skoog (MS) medium with 2.0 mg·L−1 6-benzylaminopurine (6-BA) and 0.2 mg·L−1 α-naphthaleneacetic acid (NAA). The highest percentage of shoot regeneration (90.37%) was attained using 1.0 mg·L−1 6-BA and 0.01 mg·L−1 NAA in the MS medium. The Woody Plant Medium (WPM) had the greatest adventitious shoot elongation rate of 93.33%. The most optimized rooting rate was 88.89% in a half-strength MS medium containing 2.0 mg·L−1 indole-3-butyric acid (IBA) and 1.0 mg·L−1 NAA. The genetic fidelity of in vitro regenerated plantlets was assessed using inter-simple sequence repeats and random amplified polymorphic DNA molecular markers, confirming the genetic uniformity and stability of regenerated B. sinensis plantlets. Our research presents an effective in vitro propagation system for B. sinensis, laying the groundwork for its germplasm conservation and large-scale production while maintaining high genetic integrity.

Low-emittance photoinjector-enabled cutting-edge scientific instruments, such as free-electron lasers, inverse Compton scattering light sources, and ultrafast electron diffraction, will greatly benefit from the improved repetition rate. In this paper, we proposed a specifically designed S-band radio frequency (RF) photoinjector to obtain low emittance and kilohertz (kHz) high-repetition rates simultaneously. By lowering the gradient, much lower RF power is needed to feed the electron gun, and then the heat problem is much easier to handle. Meanwhile, by optimizing the length of the gun’s first cell from the normal case of 0.6-cell to 0.4-cell, the launch phase and the extraction field are significantly improved, thus ensuring the generation of low-emittance electron beams. In our design, the proposed 1.4-cell RF gun can work effectively under different field gradients ranging from 30 MV/m to 100 MV/m. For a standard case of 60 MV/m, 2.5 MW peak RF power with μs level pulse width is sufficient, thus offering the feasibility of improving the repetition rate to kHz level with a standard 5 MW irradiation klystron. In addition, simulated electron beams with a low emittance of 0.29 mm.mrad@200 pC can be generated by this proposed photoinjector, showing that this high-repetition rate injector holds the potential to deliver high-quality beams comparable to those of state-of-the-art S-band photoinjectors. Combining the merits of low emittance and high-repetition rate, this proposed photoinjector will provide a new possibility for future free-electron laser facilities operating at repetition rates ranging from kHz to tens of kHz.

The ‘diabetic bone paradox’ suggested that type 2 diabetes (T2D) patients would have higher areal bone mineral density (BMD) but higher fracture risk than individuals without T2D. In this study, we found that the genetically predicted T2D was associated with higher BMD and lower risk of fracture in both weighted genetic risk score (wGRS) and two-sample Mendelian randomization (MR) analyses. We also identified ten genomic loci shared between T2D and fracture, with the top signal at SNP rs4580892 in the intron of gene RSPO3. And the higher expression in adipose subcutaneous and higher protein level in plasma of RSPO3 were associated with increased risk of T2D, but decreased risk of fracture. In the prospective study, T2D was observed to be associated with higher risk of fracture, but BMI mediated 30.2% of the protective effect. However, when stratified by the T2D-related risk factors for fracture, we observed that the effect of T2D on the risk of fracture decreased when the number of T2D-related risk factors decreased, and the association became non-significant if the T2D patients carried none of the risk factors. In conclusion, the genetically determined T2D might not be associated with higher risk of fracture. And the shared genetic architecture between T2D and fracture suggested a top signal around RSPO3 gene. The observed effect size of T2D on fracture risk decreased if the T2D-related risk factors could be eliminated. Therefore, it is important to manage the complications of T2D to prevent the risk of fracture.

The dissolved organic matter (DOM) in forest ecosystems significantly impacts soil carbon cycling due to its active turnover characteristics. However, whether different plantation forest soil profiles exhibit distinct DOM characteristics remains unclear. Hence, utilizing fluorescence spectroscopy and the parallel factor analysis (PARAFAC) method, a 1-meter soil profile analysis was carried out on three distinct artificial forests (Pinus tabuliformis (PT), Quercus crispula (QC), and a mixed forest of PT and QC (MF)), concurrently assessing the impact of soil chemical properties and enzyme activity on dissolved organic matter (DOM). The findings indicated that the mean concentration of dissolved organic carbon (DOC) was greatest in the MF and lowest in PT, exhibiting considerable variation with soil depth, suggesting that mixed tree species may promote the discharge of organic matter. The fluorescence spectra revealed two distinct peaks: humic-like fluorescence peaks (Peaks A and C) and a protein-like fluorescence peak (Peak T), with the most intense fluorescence observed in MF soil. As the soil depth increased, the fluorescence intensity of Peaks A and C steadily declined, while the intensity of Peak T rose. Four DOM components were identified in three types of plantations forests: surface soil was dominated by humic acid-like fluorescent components (C1 and C2), while the deep soil was primarily characterized by protein-like fluorescence components (C3 and C4). Different soil profile fluorescence parameter indices indicated that the source of DOM in the surface soil (i.e., 0–20 cm) was mainly allochthonous inputs, whereas, in the deep soil (i.e., 60–100 cm), it was mainly autochthonous, such as microbial activity. The findings from the partial least squares path modeling (PLS-PM) revealed that TP, aP, NH4+-N, and the combined impact of soil enzymes were influential in shaping the diversity of DOM attributes. Put differently, alterations in DOM concentration were concomitantly influenced by forest classification, soil characteristics, and depth. It has been demonstrated that, in contrast to monoculture forests, the establishment of mixed forest models has been more advantageous in enhancing the soil dissolved organic matter (DOM). These discoveries offer innovative perspectives on the dynamic characteristics of DOM in soil profiles and its influencing factors under different plantations forest planting patterns.

Background: Epidemiological characteristics of human brucellosis (HB) have changed over the last decade. In this study, we depicted the spatiotemporal features of HB in Shenyang, China, from 2013 to 2022 and the objective was to visualise spatiotemporal patterns and identify high-risk regions with the purpose to provide evidence for HB prevention and control. Methods: We performed an observational epidemiological study using HB data obtained from the National Notifiable Disease Reporting System (NNDRS). Joinpoint regression analysis was employed to determine the changing trends in the annual incidence. A vector boundary map of Shenyang was used to visualise spatial distribution. Spatial autocorrelation was identified using both global and local Moran's autocorrelation coefficients, while hotspot areas were determined using the Getis-Ord statistic. Results: A combined sum of 4103 HB cases were analysed, and the average level of annual incidence of HB was 5.52 per 100,000. The incidence of HB showed obvious seasonality, with a notable peak observed from April to July (summer peak). The annual incidence in Shenyang has been on the rise since 2013, with an annual percentage change (APC) of 6.39% (95%CI 1.29%, 12.39%). Xinmin County exhibited the most elevated average annual incidence rate, with Faku County ranking second. The average annual incidence in rural areas exhibited a significantly greater disparity compared to suburban areas (P

BackgroundIncreasing research has implicated the possible effect of gut microbiota (GM) on the prognosis of ischemic stroke (IS). However, the precise causal relationship between GM and functional outcomes after IS remains unestablished.MethodsData on 211 GM taxa from the MiBioGen consortium and data on prognosis of IS from the Genetics of Ischemic Stroke Functional Outcome (GISCOME) network were utilized as summary-level data of exposure and outcome. Four kinds of Mendelian randomization (MR) methods were carried out to ascertain the causal effect of GM on functional outcomes following IS. A reverse MR analysis was performed on the positive taxa identified in the forward MR analysis to determine the direction of causation. In addition, we conducted a comparative MR analysis without adjusting the baseline National Institute of Health Stroke Scale (NIHSS) of post-stroke functional outcomes to enhance confidence of the results obtained in the main analysis.ResultsFour taxa were identified to be related to stroke prognosis in both main and comparative analyses. Specifically, genus Ruminococcaceae UCG005 and the Eubacterium oxidoreducens group showed significantly negative effects on stroke prognosis, while the genus Lachnospiraceae NK4A136 group and Lachnospiraceae UCG004 showed protective effects against stroke prognosis. The reverse MR analysis did not support a causal role of stroke prognosis in GM. No evidence of heterogeneity, horizontal pleiotropy, and outliers was found.ConclusionThis MR study provided evidence that genetically predicted GM had a causal link with post-stroke outcomes. Specific gut microbiota taxa associated with IS prognosis were identified, which may be helpful to clarify the pathogenesis of ischemic stroke and making treatment strategies.

Biologically derived hierarchical structural materials not only boast energy‐efficient processing but also exhibit impressive mechanical performance. Silk stands as the gold standard in hierarchical fiber production, leveraging a unique combination of advantages. Nevertheless, the artificial replication of silk poses technical challenges related to precision processing and comprehensive molecular control. To address such issues, this study investigates the hierarchical assembly of solid regenerated silk in an air atmosphere, facilitated by the incorporation of carbon nanotube (CNT) seeding. Results obtained highlight that this CNT seeding facilitates multiscale structure development in response to post‐spin tensile stress. Such CNT bridged structure assembly bypasses some natural processing control variables (pH, ions) and the necessary solvent immersed state for conventional silk post‐drawing. Combining secondary electron hyperspectral imaging and 3D synchrotron X‐ray ptychotomography, this study reports silk protein conversion from a disordered as‐spun state to a longitudinal orientated semi‐crystalline nano structure during drawing. The development of microscale structure during the drawing process is attributed to the presence of CNTs, yielding mechanical properties comparable to, and frequently surpassing, those exhibited by native fibers. These findings collectively propose a framework for exploring novel processing routes and offer a practical means controlling self‐assembly in silk materials.

In the era of advancing digital transformation, the impact of the digital divide on residents’ financial behavior has garnered considerable attention, yet there exists a gap in understanding its implications for financial advisors. Employing the analytical framework of “access gap-usage gap-utility gap” and utilizing a Probit model with sample selectivity, this paper systematically explores the impacts, heterogeneity, and mechanisms of the three levels of the digital divide on the demand for and engagement with financial advisors among residents in six eastern provinces of China in 2022. Key findings are as follows: (1) The impact of the access gap isn't significantly, whereas the effects of the usage gap and utility gap are significantly negative. This implies that residents’ internet usage itself does not affect the likelihood of seeking and engaging financial advisors, but lower frequency and perceived importance of internet usage decrease the likelihood of seeking and engaging financial advisors. (2) Heterogeneity analysis reveals that the inhibitory effects of the usage gap and utility gap are more pronounced in rural households, those with debt, and householders lacking financial education. (3) Mechanism studies uncover that both the usage gap and utility gap diminish residents’ demand for and engagement with financial advisors by weakening social networks and reducing information attention. This study contributes to a deeper understanding of the profound impact of digital transformation on financial markets, offering policy suggestions and practical guidance to enhance financial services.