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Abstract The challenge of ensuring reliability for high‐efficiency technology, multiple‐input‐multiple‐output orthogonal‐frequency‐division‐multiplexing (MIMO‐OFDM), in wireless frequency‐selective fading environments persists. In this article, the concept of spreading a symbol's energy is proposed as a viable solution to enhance transmission reliability for MIMO‐OFDM systems. And an energy‐spreading‐transform (EST)‐based MIMO‐OFDM transceiver is developed. Following the Inverse Fast Fourier Transform (IFFT) performed by the conventional MIMO‐OFDM transmitter, an orthogonal transformation called the EST is introduced. This transform spreads the energy of a symbol across the entire frequency domain and all time slots. The EST is coupled with the improved iterative detection algorithm named EST‐partial decision (PD)‐iterative‐interference‐cancellation (EST‐PD‐IIC) to maximize and leverage the potential diversity gain. Numerical simulation results demonstrate that the proposed scheme approaches the performance bound when signal‐to‐noise ratio (SNR) is about 21dB for 16‐ary quadrature amplitude modulation (16‐QAM). Complexity analysis illustrates that the computational complexity of the evolved EST‐PD‐IIC algorithm is lower than that of the famous vertically Bell laboratory layered space‐time detector (V‐BLAST) when the antenna array size is greater than 3×3. In summary, the proposed scheme is practical for providing high‐quality communication in multi‐path fading environments and can even enable a reliable communication without channel encoding when Eb/N0 exceeds a threshold in 5G‐Advanced.

Abstract Typical weak signal search experiments rely on resonant effects, where the resonance frequency is scanned over a broad range, resulting in significant time consumption. In this study, we demonstrate an accelerated strategy that surpasses the typical resonance-bandwidth limited scan step without compromising sensitivity. We apply this method to an alkali-noble-gas spin system, achieving an approximately 30-fold increase in scanning step size. Additionally, we obtain an ultrahigh sensitivity of 1.29 fT ⋅ Hz−1/2 at around 5 Hz, corresponding to an energy resolution of approximately 1.8 × 10−23eV ⋅ Hz−1/2, which is among the highest quantum energy resolutions reported. Furthermore, we use this sensor to search for axion-like particles, setting stringent constraints on axion-like particles (ALPs) in the 4.5–15.5 Hz Compton-frequency range coupling to neutrons and protons, improving on previous limits by several-fold. This accelerated strategy has potential applications in other resonant search experiments.

Abstract People procrastinate, but why? One long-standing hypothesis is that temporal discounting drives procrastination: in a task with a distant future reward, the discounted future reward fails to provide sufficient motivation to initiate work early. However, empirical evidence for this hypothesis has been lacking. Here, we used a long-term real-world task and a novel measure of procrastination to examine the association between temporal discounting and real-world procrastination. To measure procrastination, we critically measured the entire time course of the work progress instead of a single endpoint, such as task completion day. This approach allowed us to compute a fine-grained metric of procrastination. We found a positive correlation between individuals’ degree of future reward discounting and their level of procrastination, suggesting that temporal discounting is a cognitive mechanism underlying procrastination. We found no evidence of a correlation when we, instead, measured procrastination by task completion day or by survey. This association between temporal discounting and procrastination offers empirical support for targeted interventions that could mitigate procrastination, such as modifying incentive systems to reduce the delay to a reward and lowering discount rates.

Abstract Gut microbiota can regulate the metabolic and immunological aspects of ischemic stroke and modulate the treatment effects. The present study aimed to identify specific changes in gut microbiota in patients with large vessel occlusion (LVO) ischemic stroke and assess the potential association between gut microbiota and clinical features of ischemic stroke. A total of 63 CSVD patients, 64 cerebral small vessel disease (CSVD) patients, and 36 matching normal controls (NCs) were included in this study. The fecal samples were collected for all participants and analyzed for gut microbiota using 16S rRNA gene sequencing technology. The abundances of five gut microbiota, including genera Bifidobacterium, Butyricimonas, Blautia, and Dorea and species Bifidobacterium_longum, showed significant changes with high specificity in the LVO patients as compared to the NCs and CSVD patients. In LVO patients, the genera Bifidobacterium and Blautia and species Bifidobacterium_longum were significantly correlated with the National Institutes of Health Stroke Scale (NIHSS) scores at the admission and discharge of the patients. Serum triglyceride levels could significantly affect the association of the abundance of genus Bifidobacterium and species Bifidobacterium_longum with the NIHSS scores at admission and modified Rankin Scale (mRS) at discharge in LVO patients. The identification of five gut microbiota with high specificity were identified in the early stage of LVO stroke, which contributed to performed an effective clinical management for LVO ischemic stroke.

Abstract To explore the impacts of continuous Ganoderma lucidum cultivation on soil physicochemical factors, soil enzyme activity, and the metabolome of Ganoderma lucidum fruiting bodies, this study conducted two consecutive years of cultivation on the same plot of land. Soil physicochemical factors and enzyme activity were assessed, alongside non-targeted metabolomic analysis of the Ganoderma lucidum fruiting bodies under continuous cultivation. The findings unveiled that in the surface soil layer (0–15 cm), there was a declining trend in organic matter, ammonium nitrogen, available phosphorus, available potassium, pH, polyphenol oxidase, peroxidase, alkaline phosphatase, and sucrase, whereas nitrate nitrogen, electrical conductivity (EC), and salt content exhibited an upward trend. Conversely, in the deeper soil layer (15–30 cm), organic matter, ammonium nitrogen, available potassium, alkaline phosphatase, and sucrase demonstrated a decreasing trend, while nitrate nitrogen, available phosphorus, pH, EC, salt content, polyphenol oxidase, and soil peroxidase showed an increasing trend. Metabolomic analysis of Ganoderma lucidum fruiting bodies distinguished 64 significantly different metabolites between the GCK and GT groups, with 39 components having markedly higher relative contents in GCK and 25 components having significantly lower relative contents in GCK compared to GT. Moreover, among these metabolites, there were more types with higher contents in the fruiting bodies harvested in the first year (GCK) compared to those harvested in the second year (GT), with pronounced differences. KEGG pathway analysis revealed that GCK exhibited more complex metabolic pathways compared to GT. The metabolites of Ganoderma lucidum fruiting bodies were predominantly influenced by soil physicochemical factors and soil enzyme activity. In the surface soil layer (0–15 cm), the metabolome was significantly affected by soil pH, soil organic matter, available phosphorus, and soil alkaline phosphatase, while in the deeper soil layer (15–30 cm), differences in the Ganoderma lucidum metabolome were more influenced by soil alkaline phosphatase, soil catalase, pH, nitrate nitrogen, and soil sucrase.

The presence of high-density defects is rarely observed in bulk 3 mol% yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) ceramics obtained through conventional pressureless sintering. In the present work, fine-grained dense 147 nm 3Y-TZP ceramics were prepared by pressureless sintering of commercial 0.25 wt% alumina-doped zirconia powders at 1300 ℃. A novel discovery was reported in which large amounts of defects were present in the grain interiors of the sample. The phenomenon was further examined using three types of powder samples, and the reasons for defect formation were investigated by microstructural characterization using high-resolution transmission electron microscopy (HRTEM) analysis and Rietveld refinement. The results confirmed the essential dependence of the defect formation on the alumina addition. The authors attributed the defect formation to the significant difference in ionic radii of the solvent and solute during the dissolution of alumina into the zirconia lattice. The sintering kinetics were proposed to be enhanced by the presence of substantial defects, which consequently favored the low-temperature sintering of the alumina-doped zirconia ceramics.

Abstract Introduction Surgery for gliomas involving eloquent areas is a very challenging microsurgical procedure. Maximizing both the extent of resection (EOR) and preservation of neurological function have always been the focus of attention. Intraoperative neurophysiological monitoring (IONM) is widely used in this kind of surgery. The purpose of this study was to evaluate the efficacy of IONM in eloquent area glioma surgery. Methods Sixty-eight glioma patients who underwent surgical treatment from 2014 to 2019 were included in this retrospective cohort study, which focused on eloquent areas. Clinical indicators and IONM data were analysed preoperatively, two weeks after surgery, and at the final follow-up. Logistic regression, Cox regression, and Kaplan‒Meier analyses were performed, and nomograms were then established for predicting prognosis. The diagnostic value of the IONM indicator was evaluated by the receiver operating characteristic (ROC) curve. Results IONM had no effect on the postoperative outcomes, including EOR, intraoperative bleeding volume, duration of surgery, length of hospital stay, and neurological function status. However, at the three-month follow-up, the percentage of patients who had deteriorated function in the monitored group was significantly lower than that in the unmonitored group (23.3% vs. 52.6%; P

BackgroundThe identification of compound-protein interactions (CPIs) is crucial for drug discovery and understanding mechanisms of action. Accurate CPI prediction can elucidate drug-target-disease interactions, aiding in the discovery of candidate compounds and effective synergistic drugs, particularly from traditional Chinese medicine (TCM). Existing in silico methods face challenges in prediction accuracy and generalization due to compound and target diversity and the lack of largescale interaction datasets and negative datasets for model learning.MethodsTo address these issues, we developed a computational model for CPI prediction by integrating the constructed large-scale bioactivity benchmark dataset with a deep learning (DL) algorithm. To verify the accuracy of our CPI model, we applied it to predict the targets of compounds in TCM. An herb pair of Astragalus membranaceus and Hedyotis diffusaas was used as a model, and the active compounds in this herb pair were collected from various public databases and the literature. The complete targets of these active compounds were predicted by the CPI model, resulting in an expanded target dataset. This dataset was next used for the prediction of synergistic antitumor compound combinations. The predicted multi-compound combinations were subsequently examined through in vitro cellular experiments.ResultsOur CPI model demonstrated superior performance over other machine learning models, achieving an area under the Receiver Operating Characteristic curve (AUROC) of 0.98, an area under the precision-recall curve (AUPR) of 0.98, and an accuracy (ACC) of 93.31% on the test set. The model’s generalization capability and applicability were further confirmed using external databases. Utilizing this model, we predicted the targets of compounds in the herb pair of Astragalus membranaceus and Hedyotis diffusaas, yielding an expanded target dataset. Then, we integrated this expanded target dataset to predict effective drug combinations using our drug synergy prediction model DeepMDS. Experimental assay on breast cancer cell line MDA-MB-231 proved the efficacy of the best predicted multi-compound combinations: Combination I (Epicatechin, Ursolic acid, Quercetin, Aesculetin and Astragaloside IV) exhibited a half-maximal inhibitory concentration (IC50) value of 19.41 μM, and a combination index (CI) value of 0.682; and Combination II (Epicatechin, Ursolic acid, Quercetin, Vanillic acid and Astragaloside IV) displayed a IC50 value of 23.83 μM and a CI value of 0.805. These results validated the ability of our model to make accurate predictions for novel CPI data outside the training dataset and evaluated the reliability of the predictions, showing good applicability potential in drug discovery and in the elucidation of the bioactive compounds in TCM.ConclusionOur CPI prediction model can serve as a useful tool for accurately identifying potential CPI for a wide range of proteins, and is expected to facilitate drug research, repurposing and support the understanding of TCM.

IntroductionMesenchymal stem cells (MSCs) have long been postulated as an important source cell in regenerative medicine. During subculture expansion, mesenchymal stem cell (MSC) senescence diminishes their multi-differentiation capabilities, leading to a loss of therapeutic potential. Up to date, the extrachromosomal circular DNAs (eccDNAs) have been demonstrated to be involved in senescence but the roles of eccDNAs during MSC.MethodsHere we explored eccDNA profiles in human bone marrow MSCs (BM-MSCs). EccDNA and mRNA was purified and sequenced, followed by quantification and functional annotation. Moreover, we mapped our datasets with the downloading enhancer and transcription factor-regulated genes to explore the potential role of eccDNAs.ResultsSequentially, gene annotation analysis revealed that the majority of eccDNA were mapped in the intron regions with limited BM-MSC enhancer overlaps. We discovered that these eccDNA motifs in senescent BMSCs acted as motifs for binding transcription factors (TFs) of senescence-related genes.DiscussionThese findings are highly significant for identifying biomarkers of senescence and therapeutic targets in mesenchymal stem cells (MSCs) for future clinical applications. The potential of eccDNA as a stable therapeutic target for senescence-related disorders warrants further investigation, particularly exploring chemically synthesized eccDNAs as transcription factor regulatory elements to reverse cellular senescence.

BackgroundWe describe a rare case of giant adrenal calcification as the main cause of sudden onset epigastric pain in a 57-year-old female patient.Case descriptionComputed tomography (CT) of the whole abdomen in this patient showed calcified foci measuring approximately 7.8 × 5.4 × 7.1 cm in the hepatorenal recess, and no enhancement effect was seen. Secondary causes of adrenal calcification in this patient were ruled out, and a rare diagnosis of a primary giant adrenal calcification was made. Subsequently, the right adrenal gland and calcified mass were completely resected. The calcification did not recur during 6 months of follow up.ConclusionsAlthough other cases of adrenal calcification of unknown origin have been reported, cases of giant idiopathic adrenal calcification are rare. In this case, huge calcification of the right adrenal gland caused abdominal pain, which disappeared after the mass was excised. The etiology, pathogenesis, clinical symptoms, and prognosis of idiopathic adrenal calcification are still unclear. Additional case reports are needed to gain a better understanding of the diagnosis and treatment of this condition.

Miniaturized fiber-optic magnetic field sensors have attracted considerable interest owing to their superiorities in anti-electromagnetic interference and compactness. However, the intrinsic thermodynamic properties of the material make temperature cross-sensitivity a challenging problem in terms of sensing accuracy and reliability. In this study, an ultracompact multicore fiber (MCF) tip sensor was designed to discriminatively measure the magnetic field and temperature, which was subsequently evaluated experimentally. The novel 3D printed sensing component consists of a bowl-shaped microcantilever and a polymer microfluid-infiltrated microcavity on the end-facet of an MCF, acting as two miniaturized Fabry-Perot interferometers. The magnetic sensitivity of the microcantilever was implemented by incorporating an iron micro ball into the microcantilever, and the microfluid-infiltrated microcavity enhanced the capability of highly sensitive temperature sensing. Using this tiny fiber-facet device in the two channels of an MCF allows discriminative measurements of the magnetic field and temperature by determining the sensitivity coefficient matrix of two parameters. The device exhibited a high magnetic field intensity sensitivity, approximately 1805.6 pm/mT with a fast response time of ~ 213 ms and a high temperature sensitivity of 160.3 pm/℃. Moreover, the sensor had a low condition number of 11.28, indicating high reliability in two-parameter measurements. The proposed 3D printed MCF-tip probes, which detect multiple signals through multiple channels within a single fiber, can provide an ultracompact, sensitive, and reliable scheme for discriminative measurements. The bowl-shaped microcantilever also provides a useful platform for incorporating microstructures with functional materials, extending multi-parameter sensing scenarios and promoting the application of MCFs.

Emodin was one of the hydrophobic active molecules, the solubility bioavailability of which was improved by loading in a certain matrix. In this study, the microcapsules of emodin-casein complexes were prepared with casein as matrix with ultrasound treatment. The structural properties of the complexes were analyzed by fluorescence spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy. The thermal properties, DPPH and ABTS+ free radical scavenging activities of the complexes were measured. In addition, the release profiles of emodin from the complexes were evaluated by simulated gastrointestinal digestion experiment. The results showed that the ultrasound treatment within 1~3 min duration had not significant effect on the fluorescence properties of the complexes with the addition of emodin at 8~10 μg/mg. Furthermore, there were no significant effect of ultrasound treatment on the FTIR spectra and morphology of emodin-casein complexes. In addition, the DPPH free radical scavenging activity of the complexes had the lowest value with 1 min-ultrasound treatment, but the highest value of ABTS+ free radical scavenging activity among other samples with the same emodin addition. The release rate of emodin from the emodin-casein complexes during simulated gastrointestinal digestion was improved by 1 min-ultrasound treatment, but retarded by 5 min-ultrasound treatment. The results would provide references for the application of ultrasound treatment in the properties' regulation of emodin-casein complexes.

The extraction of buildings from synthetic aperture radar (SAR) images poses a challenging task in the realm of remote sensing (RS). In recent years, convolutional neural networks (CNNs) have rapidly advanced and found application in the field of RS. Researchers have investigated the potential of CNNs for the semantic segmentation of SAR images, bringing excellent improvements. However, the semantic segmentation of buildings in SAR images still encounters challenges due to the high similarity between features of ground objects and buildings in SAR images, as well as the variability in building structures. In this article, we propose the local–global multiscale fusion network (LGMFNet), based on a dual encoder–decoder structure, for the semantic segmentation of buildings in SAR images. The proposed LGMFNet introduces an auxiliary encoder with a transformer structure to address the limitation of using the main encoder with a CNN structure for global modeling. To embed global dependencies hierarchically into the CNN, we designed the global–local semantic aggregation module (GLSM). The GLSM serves as a bridge between the dual encoders to achieve semantic guidance and coupling from the local to the global level. Furthermore, to bridge the semantic gap between different scales, we designed the multiscale feature fusion network (MSFN) as the decoder. MSFN achieves the interactive fusion of semantic information between various scales by constructing the multiscale feature fusion module. Experimental results demonstrate that the proposed LGMFNet achieves the mIoU of 91.17% on the BIGSARDATA 2023 AISAR competition dataset, outperforming the second-best method by a margin of 0.78%. This evidences the superiority of LGMFNet in comparison to other state-of-the-art methods.

High-quality porous ceramics are extremely attractive in terms of energy conservation and consumption reduction, and thus are one of the research hotspots pursued in recent years. For this purpose, porous MgO-based ceramics with outstanding thermal shock resistance and thermal insulation performance were designed and prepared by using the direct firing method and introducing alumina with different paticle sizes as additives. The results reveal that the in-situ formed MgAl2O4 phase by alumina additives simultaneously improves the apparent porosity, thermal insulation, and thermal shock resistance of the prepared MgO-based ceramics. Specifically, the increase in the apparent porosity can be attributed to the volume expansion effect of MgAl2O4 phase, so the industrial alumina with larger particle size is more effective (20 wt% addition: the apparent porosity from 43.5 % to 55.4 %, the thermal conductivity from 0.977 to 0.389 W m−1 K−1 at 800 °C); moreover, the enhancement in thermal shock resistance can be ascribed to the residual stress effect caused by the MgAl2O4 particles, so the micron alumina with smaller particle size is more efficient (10 wt% addition: the residual strength ratio from 93.48 % to 65.13 %–113.92 % and 94.47 % after one and five air-quenching). Therefore, this work demonstrates a novel synthetic strategy for porous ceramics with great potential in the field of high-temperature thermal insulation.

In the human body, non-centrosymmetric biological structures exhibit piezoelectric effect across from microscopic biomolecular building blocks to macroscopic tissues and organs. However, the fabrication of piezoelectric devices from discarded natural tissues and organs has rarely been exploited for energy harvesting applications. Herein, the extracted human teeth were recycled as an active layer in a piezoelectric nanogenerator for power generation. Due to the piezoelectric effect of enamel and dentin, a human teeth-based sandwiched piezoelectric nanogenerator was fabricated, producing high and stable power outputs with an open-circuit voltage of approximately 0.9 V under an external force at 60 N. Furthermore, the high mechanical durability of the piezoelectric nanogenerator was also verified after 1600 pressing-and-releasing cycles without noticeable output degradation. Notably, for the first time, a light-emitting diode (LED) was illuminated by the human teeth-based piezoelectric device. This work exemplifies a sustainable strategy to recycle the extracted human teeth by fabricating a piezoelectric nanogenerator for energy harvesting, providing inspiration for converting waste into wealth toward green energy in bionanotechnology.

Saline and alkaline stress is one of the major abiotic stresses facing agricultural production, which severely inhibits the growth and yield of plant. The application of plant growth regulators can effectively prevent crop yield reduction caused by saline and alkaline stress. Exogenous melatonin (MT) can act as a signaling molecule involved in the regulation of a variety of physiological processes in plants, has been found to play a key role in enhancing the improvement of plant tolerance to abiotic stresses. However, the effects of exogenous MT on saline and alkaline tolerance of table grape seedlings and its mechanism have not been clarified. The aim of this study was to investigate the role of exogenous MT on morphological and physiological growth of table grape seedlings (Vitis vinifera L.) under saline and alkaline stress. The results showed that saline and alkaline stress resulted in yellowing and wilting of grape leaves and a decrease in chlorophyll content, whereas the application of exogenous MT alleviated the degradation of chlorophyll in grape seedling leaves caused by saline and alkaline stress and promoted the accumulation of soluble sugars and proline content. In addition, exogenous MT increased the activity of antioxidant enzymes, which resulted in the scavenging of reactive oxygen species (ROS) generated by saline and alkaline stress. In conclusion, exogenous MT was involved in the tolerance of grape seedlings to saline and alkaline stress, and enhanced the saline and alkaline resistance of grape seedlings to promote the growth and development of the grape industry in saline and alkaline areas.

ABSTRACTDouble minutes (DMs), extrachromosomal gene fragments found within certain tumors, have been noted to carry onco- and drug resistance genes contributing to tumor pathogenesis and progression. After screening for SUMO-related molecule expression within various tumor sample and cell line databases, we found that SUMO-conjugating enzyme UBC9 has been associated with genome instability and tumor cell DM counts, which was confirmed both in vitro and in vivo. Karyotyping determined DM counts post-UBC9 knockdown or SUMOylation inhibitor 2-D08, while RT-qPCR and Western blot were used to measure DM-carried gene expression in vitro. In vivo, fluorescence in situ hybridization (FISH) identified micronucleus (MN) expulsion. Western blot and immunofluorescence staining were then used to determine DNA damage extent, and a reporter plasmid system was constructed to detect changes in homologous recombination (HR) and non-homologous end joining (NHEJ) pathways. Our research has shown that UBC9 inhibition is able to attenuate DM formation and lower DM-carried gene expression, in turn reducing tumor growth and malignant phenotype, via MN efflux of DMs and lowering NHEJ activity to increase DNA damage. These findings thus reveal a relationship between heightened UBC9 activity, increased DM counts, and tumor progression, providing a potential approach for targeted therapies, via UBC9 inhibition.

BackgroundIn recent years, diseases caused by abnormal immune-inflammatory responses have become increasingly severe. Dietary intervention involving omega-3 polyunsaturated fatty acids (ω-3 PUFAs) has emerged as a potential treatment. However, research investigating the relationship between ω-3, ω-6 PUFAs, and ω-6 to ω-3 ratio with inflammatory biomarkers remains controversial.MethodsTo investigate the correlation between the intake of ω-3 and ω-6 PUFAs and the ratio of ω-6: ω-3 with biomarkers of inflammation, the National Health and Nutrition Examination Survey (NHANES) data (1999 to 2020) was utilized. The systemic immune-inflammation index (SII), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and white blood cell (WBC) were selected as study subjects. Dietary data for ω-3 and ω-6 PUFAs were collected via two 24-h dietary recall interviews. SII index and other indicators were obtained from the blood routine data. The multiple linear regression and restricted cubic spline models were utilized to evaluate the association of ω-3, ω-6 PUFAs intake, and ω-6: ω-3 ratio to SII and secondary measures.ResultsThis study involved a total of 43,155 American adults. ω-3 and ω-6 PUFAs exhibited negative correlations with SII, PLR, NLR, and WBC. The correlation between ω-6: ω-3 ratio and SII, PLR, NLR, and WBC was not significant. Furthermore, the dose–response relationship showed that the relationship between the intake of ω-3 and ω-6 PUFAs and SII was an “L” pattern.ConclusionIntake of dietary ω-3 and ω-6 PUFAs reduces the levels of several inflammatory biomarkers in the body and exerts immunomodulatory effects.

As a characteristic representative of the new generation of vehicles, autonomous driving is expected to improve people's driving experience. The study on traffic accident of autonomous vehicles (AVs) helps provide suggestions for autonomous driving safety from multiple disciplines and perspectives, and provide support for formulating traffic accident treatment schemes. Knowledge mapping, as a cutting-edge research method in bibliometrics, scientifically and objectively displays the relevant research status using visual means. This paper uses CiteSpace 6.1.r3 to analyze 5068 related literature on the Web of Science database from 1991 to 2022 and finds out major thematic clusters, important documents and representative journals according to citation frequency. The results show that research on traffic accidents involving AVs focuses on accident preventing technologies, including how to avoid collisions, track lane-position, and enhance vehicle-to-everything (V2X) communication. This paper extracts the mean research topics and key points involved in the field and illustrates journals related to AVs and traffic accidents, which provides guidance for subsequent researchers to carry out in-depth research and contribute their papers. Popular journals are in disciplines of mathematics, systems, computer, economics, and social science. This paper also suggests scholars to consider the aspects of scene reconstruction, cause analysis, and injury of vulnerable road users, so as to investigate traffic accidents and put forward effective treatment schemes to reduce AV accidents, and ultimately improve road safety.

Insulin secretion by pancreatic islets plays a vital role in regulating blood glucose levels. Nevertheless, the mechanism responsible for this dynamic insulin secretion has not been completely understood, particularly at the single islet level. In this study, we have successfully developed an easy microfluidic platform that allows for the exploration of dynamic glucose-stimulated insulin secretion (GSIS) at the single islet level. With the utilization of this platform, we evaluated dynamic GSIS from single islets isolated from both normal and diabetic rats. Our results demonstrate that islets can be categorized into three types based on their dynamic GSIS: Type I exhibits a biphasic GSIS profile with a fast first phase and flat second phase; Type II also has a biphasic GSIS profile with a fast first phase but a slow increased second phase; Type III displays only a slowly increased second phase and lacks a fast first phase. RNA sequencing analysis demonstrated that the cell type and exocytosis-specific genes are consistent with the proportion of cells and insulin release kinetics among the three types of islets, respectively. Moreover, our findings suggest that high expression of Atp5pb is anti-correlated with the first phase of insulin secretion. Furthermore, we revealed that diabetic islets exhibit only the type I GSIS response, indicating a deliberate impairment of the second phase of insulin secretion. Together, this device serves as a crucial tool in the research field of islets and diabetes, allowing researchers to investigate islet functional heterogeneity and identity at the single islet level.

Abstract When developing models in cognitive science, researchers typically start with their own intuitions about human behavior in a given task and then build in mechanisms that explain additional aspects of the data. This refinement step is often hindered by how difficult it is to distinguish the unpredictable randomness of people’s decisions from meaningful deviations between those decisions and the model. One solution for this problem is to compare the model against deep neural networks trained on behavioral data, which can detect almost any pattern given sufficient data. Here, we apply this method to the domain of planning with a heuristic search model for human play in 4-in-a-row, a combinatorial game where participants think multiple steps into the future. Using a data set consisting of 10,874,547 games, we train deep neural networks to predict human moves and find that they accurately do so while capturing meaningful patterns in the data. Thus, deviations between the model and the best network allow us to identify opportunities for model improvement despite starting with a model that has undergone substantial testing in previous work. Based on this analysis, we add three extensions to the model that range from a simple opening bias to specific adjustments regarding endgame planning. Overall, our work demonstrates the advantages of model comparison with a high-performance deep neural network as well as the feasibility of scaling cognitive models to massive data sets for systematically investigating the processes underlying human sequential decision-making.

Abstract Background Efferocytosis is a biological process in which phagocytes remove apoptotic cells and vesicles from tissues. This process is initiated by the release of inflammatory mediators from apoptotic cells and plays a crucial role in resolving inflammation. The signals associated with efferocytosis have been found to regulate the inflammatory response and the tumor microenvironment (TME), which promotes the immune escape of tumor cells. However, the role of efferocytosis in glioblastoma multiforme (GBM) is not well understood and requires further investigation. Methods In this study, we conducted a comprehensive analysis of 22 efferocytosis-related genes (ERGs) by searching for studies related to efferocytosis. Using bulk RNA-Seq and single-cell sequencing data, we analyzed the expression and mutational characteristics of these ERGs. By using an unsupervised clustering algorithm, we obtained ERG clusters from 549 GBM patients and evaluated the immune infiltration characteristics of each cluster. We then identified differential genes (DEGs) in the two ERG clusters and classified GBM patients into different gene clusters using univariate cox analysis and unsupervised clustering algorithms. Finally, we utilized the Boruta algorithm to screen for prognostic genes and reduce dimensionality, and the PCA algorithm was applied to create a novel efferocytosis-related scoring system. Results Differential expression of ERGs in glioma cell lines and normal cells was analyzed by rt-PCR. Cell function experiments, on the other hand, validated TIMD4 as a tumor risk factor in GBM. We found that different ERG clusters and gene clusters have distinct prognostic and immune infiltration profiles. The ERG signature we developed provides insight into the tumor microenvironment of GBM. Patients with lower ERG scores have a better survival rate and a higher likelihood of benefiting from immunotherapy. Conclusions Our novel efferocytosis-related signature has the potential to be used in clinical practice for risk stratification of GBM patients and for selecting individuals who are likely to respond to immunotherapy. This can help clinicians design appropriate targeted therapies before initiating clinical treatment.

Abstract Polymorphic structures of transition metal dichalcogenides (TMDs) host exotic electronic states, like charge density wave and superconductivity. However, the number of these structures is limited by crystal symmetries, which poses a challenge to achieving tailored lattices and properties both theoretically and experimentally. Here, we report a coloring-triangle (CT) latticed MoTe2 monolayer, termed CT-MoTe2, constructed by controllably introducing uniform and ordered mirror-twin-boundaries into a pristine monolayer via molecular beam epitaxy. Low-temperature scanning tunneling microscopy and spectroscopy (STM/STS) together with theoretical calculations reveal that the monolayer has an electronic Janus lattice, i.e., an energy-dependent atomic-lattice and a Te pseudo-sublattice, and shares the identical geometry with the Mo5Te8 layer. Dirac-like and flat electronic bands inherently existing in the CT lattice are identified by two broad and two prominent peaks in STS spectra, respectively, and verified with density-functional-theory calculations. Two types of intrinsic domain boundaries were observed, one of which maintains the electronic-Janus-lattice feature, implying potential applications as an energy-tunable electron-tunneling barrier in future functional devices.

Objective Although it is an effective fixation technique for an unstable odontoid, anterior fixation remains challenging in pediatric populations. Our study measures the anatomical parameters of the odontoid to identify the feasibility of anterior fixation with a single screw for children. Methods We retrospectively collected data from 112 normal male and female children (aged between 2 and 18) in our institute from January 1, 2022 to December 31, 2022. Subjects were divided into a youth group (2–6 years old), a juvenile group (7–12 years old), and an adolescent group (13–18 years old). Sagittal and coronal computed tomography images of the upper cervical spine were used to measure the screw length, angle, and inner and outer diameters of the odontoid. One‐way analysis of variance with the Tukey test was used to analyze the parameters among the groups, while the t‐test was used to analyze gender differences. Correlations between parameters and age were assessed using Pearson's test. Results There were significant differences between male and female subjects in screw length and inner and outer diameters (of both sagittal and coronal views) but not in screw angle. The narrowest diameter of the odontoid was 4.0 ± 1.5 mm in the youth group, 5.5 ± 1.5 mm in the juvenile group, and 5.6 ± 1.1 mm in the adolescent group, respectively. There were significant differences among the three groups in screw length (p 4 mm. Screw length and inner and outer diameters in lateral view were positively correlated with age, and screw angle was negatively correlated with age. Conclusion It is feasible to insert a standard single screw (Φ 3.5 mm) into the odontoid of children aged 7–18 years old but not those aged 2–6 years old. How the anatomical parameters of the odontoid change with age, especially the narrowest diameters, is worthy of attention.

The nitrogen cycling process in alpine wetlands is profoundly affected by precipitation changes, yet the dynamic response mechanism of denitrifiers to long-term precipitation shifts in the alpine wetland of the Qinghai-Tibet Plateau remains enigmatic. Utilizing high-throughput sequencing analysis of nirS-type functional genes, this study delved into the dynamic response mechanism of nirS-type denitrifiers to precipitation changes in the alpine wetland of Qinghai Lake. The findings revealed that nirS-type denitrifiers in the alpine wetland of Qinghai Lake were primarily Proteobacteria, and Alpha diversity exhibited a negative correlation with the precipitation gradient, with deterministic processes predominating in the community assembly of denitrifying microbes. A 50% increase in rainfall shifted the community assembly process of denitrifiers from deterministic to stochastic. Dominant microflora at the genus level responded significantly to precipitation changes, with aerobic bacteria comprising the majority of differentially abundant taxa (55.56%). As precipitation increased, the complexity of the microbial interaction network decreased, and a 25% reduction in precipitation notably elevated the relative abundance of three key functional groups: chemoheterotrophic, aerobic chemoheterotrophic, and nitrogen fixation. Precipitation notably emerged as the primary regulator of nirS-type denitrifiers in the alpine wetland of Qinghai Lake, accounting for 51% of the variation in community composition. In summary, this study offers a fresh perspective for investigating the ecological processes of nitrogen cycling in alpine ecosystems by examining the diversity and community composition of nirS-type denitrifiers in response to precipitation changes.

Improving drought tolerance in plants is essential for increasing crop yields under water-limited conditions. In this study, we investigated the functional role of the maize gene ZmDST44, which is targeted by the miRNA ZmmiR139. Our results indicate that ZmmiR139 regulates ZmDST44 by cleaving its mRNA, as confirmed by inverse expression patterns and 5′-RACE analysis. Overexpression of ZmDST44 in Arabidopsis, rice, and maize resulted in significant enhancements in drought tolerance. Transgenic plants exhibited reduced malondialdehyde (MDA) levels, increased proline accumulation, and upregulation of drought-responsive genes compared to wild-type plants. Transgenic Arabidopsis and rice showed improved drought resistance and higher post-drought recovery rates, and transgenic maize displayed lower sensitivity to drought stress. These findings suggest that ZmDST44 acts as a positive regulator of drought tolerance across different plant species and holds promise for developing drought-resistant crops through genetic engineering.

In this work, nanocrystalline high-entropy ceramics (HECs) were prepared by the combination of combustion synthesis and ultra-high pressure sintering. The prepared high-entropy (La0.2Nd0.2Sm0.2Eu0.2Gd0.2)2Zr2O7 ceramic powder had the average grain size of 11 nm and displayed the disordered defective fluorite structure. The HECs sintered under ultra-high pressure showed the defective fluorite structure, whereas the control samples fabricated by pressureless sintering showed the ordered pyrochlore structure. The HECs sintered under pressure of 10 GPa possessed much smaller grain size than that obtained by pressureless sintering. In particular, the grain size of ceramics sintered under 10 GPa at 600 °C was not significantly larger than that of raw powder and its Vickers hardness was 11.9 GPa. Ultra-high pressure sintering could remarkably increase the density of ceramics and restrain the growth of grains. The plastic deformation under ultra-high pressure was believed as the main densification mechanism for the grain refinement and performance improvement.

If dedicate a lane to connected autonomous vehicle (CAV) on a multilane road, the traffic congestion and safety risks remain a major problem but in a different style. Random and disorderly mandatory lane-changing behaviour before approaching the next ramp or intersection would have a disturbing effect on the following vehicles of the traffic flow. This paper mainly establishes the optimal mandatory lane-changing location matching model for each target vehicle in the dedicated CAV lane environment. The aim is to minimizing the total travel time, which could take the disturbing effect into account. This model nests the cell transmission model (CTM) to describe vehicle running. The constraints include the relation between target CAV lane-changing cell and the corresponding behaviour start time, the updating of the flow, and occupancy for varied cells. We use the Ant Colony Optimization (ACO) algorithm to solve the problem. Through the case study of a basic two-lane road scenario in Ningbo, we acquire the convergence results based on the ACO algorithm. Our optimal lane-changing location matching scheme can save 5.9% total travel time when compared to the near-end location lane-changing scheme. We test our model by increasing the total number of upstream input vehicles with 4%, 11%, 15%, and the mandatory lane-changing vehicles with 60%, 200%, respectively. The testing results prove that out optimization method could deal with varied road traffic flow situations. Specifically, when the traffics and mandatory lane-changing vehicles increase, our method could perform better.

Traumatic brain injury (TBI) is the main cause of death among young adults and the main cause of mortality and disability for all ages groups worldwide. Ginkgolides terpenoid compounds unique to Ginkgo biloba, which have protective effects on cardiovascular and cerebrovascular diseases. The aim of this study is to investigate whether ginkgolide A (GA) can improve TBI in mice and whether it can alleviate cell apoptosis in the brain of TBI mice by reducing oxidative stress. Mice received TBI and GA administration for 7 days. Neurological deficits were monitored and brain tissues were examined for molecular pathological markers. TBI mice had more severer neurobehavioral deficits compared with sham group, which could be improved by administration of GA. GA administration improveed Modified Neurological Severity Scale (mNSS) scores, Grid-Walking test and Rotarod test of TBI mice. The apoptosis increased in TBI mice, and reduced after GA treatment. The biomarkers of oxidative stress 8-OHdG and malondialdehyde (MDA) in the brain of TBI mice increased, while SOD reduced. These changes were reversed after GA administration. These outcomes showed that GA could raise neurobehavioral deficiency of TBI mice. GA treatment could attenuate apoptosis in TBI mice by reducing oxidative stress.

Objective To evaluate the biomechanical stability of anterior transarticular crossing screw (ATCS) and compare it with anterior transarticular screw (ATS) which may provide basic evidence for clinical application. Methods Eight human fresh cadaveric specimens (occiput-C4) were tested with 5 conditions including the intact status, the injury status (type II odontoid fracture), the injury+ATS fixation status (traditional bilateral ATS fixation); the injury+unilateral ATCS fixation status; and the injury+bilateral ATCS fixation status. Specimens were applied to a pure moment of 1.5 Nm in flexion-extension, lateral bending, and axial rotation, respectively. The range of motions (ROMs) and the neutral zones (NZs) of C1 to C2 segment were calculated and compared between 5 status. Results ATS and ATCS fixations significantly reduced the motions in all directions when compared with the intact and injury statues (p < 0.05). In flexion-extension, the ROMs of ATS, unilateral ATCS, and bilateral ATCS were 4.7° ±2.5°, 4.1° ±1.9°, and 3.2° ±1.2°, respectively. Bilateral ATCS resulted in a significant decrease in ROM in flexion-extension when compared with ATS and unilateral ATCS (p = 0.035 and p = 0.023). In lateral bending and axial rotation, there was no significant difference in ROM between the 3 fixations (p > 0.05). Three fixations resulted in similar NZs in all directions (p > 0.05). Conclusion ATCS is a biomechanically effective alternative or supplemental method for atlantoaxial instability.

Objective There is lack of an internal fixation following resection of a dumbbell tumor by hemi‐laminectomy and facetectomy that achieves adequate stability with less trauma. Unilateral fixation and reconstruction (unilateral pedicle screw and contralateral lamina screw fixation combined with lateral mass reconstruction, UPS + CLS + LM) may be an ideal technique to address this problem. A biomechanical comparison and a case report were designed to evaluate its spinal stability and clinical effect. Methods Seven fresh‐frozen human subcervical specimens were used for the biomechanical testing. The conditions tested were: (1) intact; (2) injured (single‐level hemi‐laminectomy and facetectomy); (3) unilateral pedicle screw (UPS) fixation; (4) UPS fixation combined with lateral mass (LM) reconstruction (UPS + LM); (5) UPS fixation and contralateral lamina screw fixation (UPS + CLS); (6) UPS + CLS + LM; (7) UPS fixation and contralateral transarticular screw fixation (UPS + CTAS); (8) bilateral pedicle screw (BPS) fixation. Range of motion (ROM) and neutral zone (NZ) were obtained at C5‐C7 segment under eight conditions. In addition, we report the case of a patient with a C7‐T1 dumbbell tumor that was treated by UPS + CLS + LM technique. Results Except left/right lateral bending and right axial rotation (all, p 0.05). There was no significant difference between UPS + CLS + LM and the UPS + CTAS condition in other directions of ROM (all, p > 0.05), except in left/right axial rotation (both, p 0.05). There was no significant difference between UPS + CLS + LM and UPS + CTAS condition in NZ in all directions (all, p > 0.05). Axial rotation NZ of UPS + CLS + LM condition was significantly reduced compared to UPS + CLS condition (p

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co3Sn2S2, we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co3Sn2S2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co3Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co3Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

Abstract The improvement of non-oxide ceramic plasticity while maintaining the high-temperature strength is a great challenge through the classical strategy, which generally includes decreasing grain size to several nanometers or adding ductile binder phase. Here, we report that the plasticity of fully dense boron carbide (B4C) is greatly enhanced due to the boundary non-stoichiometry induced by high-pressure sintering technology. The effect decreases the plastic deformation temperature of B4C by 200 °C compared to that of conventionally-sintered specimens. Promoted grain boundary diffusion is found to enhance grain boundary sliding, which dominate the lower-temperature plasticity. In addition, the as-produced specimen maintains extraordinary strength before the occurrence of plasticity. The study provides an efficient strategy by boundary chemical change to facilitate the plasticity of ceramic materials.

Models for maturity discrimination and polyphenol content determination of Aronia melanocarpa (AM) were established to nondestructively determinethe maturityand polyphenol content of AM based on the hyperspectral imaging (HSI) technology. The HSI technology was adopted to collect the image information of Fukangyuan No. 1 AM in different maturity levels, and the Folin-Ciocalteu colorimetric method was employed to determine the polyphenol content. The Monte Carlo method was used to eliminate the outliers. The original image information was preprocessed with the following procedures: Moving average, median filter, normalize, baseline calibration, multiple scattering correction, detrending, and standard normal variate. Meanwhile, the sample set partitioning based on joint x-y distance method was applied to divide the samples. The competitive adaptive reweighting sampling and uninformative variable elimination method were selected to extract the feature wavelengths, based on which the partial least squares model (PLS) and support vector machine (SVM) model were established and compared. The results showed that the UVE-SVM model after multiple scattering correction showed the best performance among all established discriminant models, with the comprehensive recognition rate of 94.62%, Rc2 of 0.9712, and accuracy of 100%. The CARS-SVM model after median filter exhibited the best efficiency in detection of polyphenol content, with the Rc2 of 0.8331. In addition, this work proved that the polyphenol content in AM was visual. This work provided a theoretical basis for the application of HSI technology in berry industry.

Abstract Background MSM are at high risk of HIV infection. Previous studies have shown that the cell cycle regulation plays an important role in HIV-1 infection, especially at the G2/M checkpoint. ATR, Chk1, Cdc25C and CDK1 are key genes of G2/M checkpoint. However, the association between SNPs of these genes and susceptibility to HIV-1 infection and AIDS progression remains unknown. Methods In this study, 42 tSNPs from the above four G2/M checkpoint genes were genotyped in 529 MSM and 529 control subjects from northern China to analyze this association. Results The results showed that rs34660854 A and rs75368165 A in ATR gene and rs3756766 A in Cdc25C gene could increase the risk of HIV-1 infection (P = 0.049, OR = 1.234, 95% CI 1.001–1.521; P = 0.020, OR = 1.296, 95% CI 1.042–1.611; P = 0.011, OR = 1.392, 95% CI 1.080–1.794, respectively), while Chk1 rs10893405 (P = 0.029, OR = 1.629, 95% CI 1.051–2.523) were significantly associated with AIDS progression. Besides, rs34660854 (P = 0.019, OR = 1.364, 95% CI 1.052–1.769; P = 0.022, OR = 1.337, 95% CI 1.042–1.716, under Codominant model and Dominant model, respectively) and rs75368165 (P = 0.006, OR = 1.445, 95% CI = 1.114–1.899; P = 0.007, OR = 1.418, 95% CI 1.099–1.831, under Codominant model and Dominant model, respectively) in ATR gene, rs12576279 (P = 0.013, OR = 0.343, 95% CI 0.147-0.800; P = 0.048, OR = 0.437, 95% CI 0.192–0.991, under Codominant model and Dominant model, respectively) and rs540436 (P = 0.012, OR = 1.407, 95% CI 1.077–1.836; P = 0.021, OR = 1.359, 95% CI 1.048–1.762, under Codominant model and Dominant model, respectively) in Chk1 gene, rs3756766 (P = 0.013, OR = 1.455, 95% CI 1.083–1.954; P = 0.009, OR = 1.460, 95% CI 1.098–1.940, under Codominant model and Dominant model, respectively) in Cdc25C gene and rs139245206 (P = 0.022, OR = 5.011, 95% CI 1.267–19.816; P = 0.020, OR = 5.067, 95% CI 1.286–19.970, under Codominant model and Recessive model, respectively) in CDK1 gene were significantly associated with HIV-1 infection under different models. Conclusions We found that genetic variants of G2/M checkpoint genes had a molecular influence on the occurrence of HIV-1 infection and AIDS progression in a northern Chinese MSM population.

Abstract Introduction/objectives Systemic lupus erythematosus (SLE) is a classic prototype of the multisystem autoimmune disease and follows a relapsing and remitting course. Triptolide is a diterpene triepoxide extracted from Chinese medicine Tripterygium wilfordii Hook F, with potent immunosuppressive and anti-inflammatory properties. Our previous work observed that triptolide alleviated lupus in MRL/lpr lupus mice with the upregulation of regulatory T cells (Treg) proportion in previous study. In this study, we explored the proportion of follicular T regulatory (Tfr), follicular T helper (Tfh) and germinal center (GC) B cells in lupus mice and evaluated the efficacy of triptolide for lupus treatment in vivo. Methods 20 female MRL/lpr mice were randomly divided into 2 treatment groups and treated orally with vehicle or triptolide. C3H mice were all housed as controlled group and treated orally with vehicle. The percentage of Tfr cells, Tfh cells and GC B cells in spleen of mice were detected by Flow cytometric analysis and immunohistochemistry after 13 weeks of treatment. Results We found that the percentage of Tfr cells decreased in MRL/lpr mice compared with controlled mice. The percentage of Tfh cells in MRL/lpr mice was significantly higher compared with that in controlled mice. The ratio of Tfr/Tfh is also decreased in lupus mice. After treated with triptolide in MRL/Lpr mice in vivo, the percentage of Tfr cells and ratio of Tfr/Tfh increased. The proportion of GC B cells also decreased in mice treated with triptolide by FACS and immunohistochemistry. Conclusions Our results demonstrate that the effect of triptolide in alleviating lupus is partly by reversing immune imbalance with increased percentage of Tfr cells and ratio of Tfr/Tfh. Triptolide might also has effect on immune response through inhibiting proliferating GC B cells.

The quality of apple picking affects the sales of apples, and the grasping force of the end effector of an apple picking robot is very important for apple picking. It is easy to cause apple damage due to excessive contact force, or when the contact force is too small to grasp the apple. However, the current research lacks an analysis of the minimum stable grasping force of apples. Therefore, in order to realize the stable grasping of apples by the end-effector of a picking robot and reduce fruit damage, this study first analyzes the grasping stability of the end-effector based on the force closure theory, and comprehensively considers the force closure constraints, nonlinear friction cone constraints and the introduction of torque constraints. Next, the constraint conditions are processed using an obstacle function, and a penalty factor is introduced to construct an optimization model of the contact force distribution of the end-effector. Then, the improved Newton method is used to grasp and solve the contact force distribution model. Under the premise of selecting the penalty factor, the optimal contact force of grasping an apple is determined using a method of numerical example simulation analysis, and the validity of the solution is verified. In order to verify the reliability of the contact force distribution optimization model, the practical significance of the method for apple grasping is verified in an actual grasping experiment. The actual experiment shows that the method can provide the minimum stable grasping force to the end-effector to achieve stable grasping.

As the climate warms, the thickening of the active layer of permafrost has led to permafrost melting and surface collapse, forming thermokarst landforms. These changes significantly impact regional vegetation, soil physicochemical properties, and hydrological processes, thereby exacerbating regional carbon cycling. This study analyzed the relationship between soil respiration rate (Rs), soil temperature (T), and volumetric water content (VWC) in the thermokarst depression zone of the headwater wetlands of Qinghai Lake, revealing their influence on these soil parameters. Results showed a significant positive correlation between soil temperature and Rs (p < 0.001), and a significant negative correlation between VWC and Rs (p < 0.001). The inhibitory effect of VWC on Rs in the thermokarst depression zone was stronger than under natural conditions (p < 0.05). Single-factor models indicated that the temperature-driven model had higher explanatory power for Rs variation in both the thermokarst depression zone (R2 = 0.509) and under natural conditions (R2 = 0.414), while the humidity-driven model had lower explanatory power. Dual-factor models further improved explanatory power, slightly more so in the thermokarst depression zone. This indicates that temperature and humidity jointly drive Rs. Additionally, during the daytime, temperature had a more significant impact on Rs under natural conditions, while increased VWC inhibited Rs. At night, the positive correlation between Rs and temperature in the thermokarst depression zone increased significantly. The temperature sensitivity (Q10) values of Rs were 3.32 and 1.80 for the thermokarst depression zone and natural conditions, respectively, indicating higher sensitivity to temperature changes at night in the thermokarst depression zone. This study highlights the complexity of soil respiration responses to temperature and humidity in the thermokarst depression zone of Qinghai Lake’s headwater wetlands, contributing to understanding carbon cycling in wetland ecosystems and predicting wetland carbon emissions under climate change.

Carbon-sequestering microorganisms play an important role in the carbon cycle of wetland ecosystems. However, the response mechanism of carbon-sequestering microbial communities to wetland type changes and their relationship with soil carbon remain unclear. To explore these differences and identify the main influencing factors, this study selected marsh wetlands, river wetlands and lakeside wetlands around Qinghai Lake as research subjects. High-throughput sequencing was employed to analyze the functional gene cbbM of carbon-sequestering microorganisms. The results revealed that the alpha diversity of cbbM carbon-sequestering microorganisms mirrored the trend in total carbon content, with the highest diversity observed in marsh wetlands and the lowest in lakeside wetlands. The dominant bacterial phylum was Proteobacteria, with prevalent genera including Thiothrix, Acidithiobacillus, and Thiodictyon. Acidithiobacillus served as a biomarker in lakeside wetlands, while two other genera were indicative of marsh wetlands. The hierarchical partitioning analysis indicated that the diversity of cbbM carbon-fixing microorganisms was primarily influenced by the total nitrogen content, while the community structure was significantly affected by the soil total carbon content. Moreover, an increased soil temperature and humidity were found to favor the carbon fixation processes of Thiomicrospira, Thiomonas, Polaromonas, and Acidithiobacillus. In summary, changes in wetland types seriously affected the characteristics of cbbM carbon sequestration in microbial communities, and a warm and humid climate may be conducive to wetland carbon sequestration.

Abstract A promising approach to the next generation of low-power, functional, and energy-efficient electronics relies on novel materials with coupled magnetic and electric degrees of freedom. In particular, stripy antiferromagnets often exhibit broken crystal and magnetic symmetries, which may bring about the magnetoelectric (ME) effect and enable the manipulation of intriguing properties and functionalities by electrical means. The demand for expanding the boundaries of data storage and processing technologies has led to the development of spintronics toward two-dimensional (2D) platforms. This work reports the ME effect in the 2D stripy antiferromagnetic insulator CrOCl down to a single layer. By measuring the tunneling resistance of CrOCl on the parameter space of temperature, magnetic field, and applied voltage, we verified the ME coupling down to the 2D limit and probed its mechanism. Utilizing the multi-stable states and ME coupling at magnetic phase transitions, we realize multi-state data storage in the tunneling devices. Our work not only advances the fundamental understanding of spin-charge coupling, but also demonstrates the great potential of 2D antiferromagnetic materials to deliver devices and circuits beyond the traditional binary operations.

Abstract Background The peroxisome is a ubiquitous single membrane-enclosed organelle with an important metabolic role. Peroxisomal disorders represent a class of medical conditions caused by deficiencies in peroxisome function and are segmented into enzyme-and-transporter defects (defects in single peroxisomal proteins) and peroxisome biogenesis disorders (defects in the peroxin proteins, critical for normal peroxisome assembly and biogenesis). In this study, we employed multivariate supervised and non-supervised statistical methods and utilized mass spectrometry data of neurological patients, peroxisomal disorder patients (X-linked adrenoleukodystrophy and Zellweger syndrome), and healthy controls to analyze the role of common metabolites in peroxisomal disorders, to develop and refine a classification models of X-linked adrenoleukodystrophy and Zellweger syndrome, and to explore analytes with utility in rapid screening and diagnostics. Results T-SNE, PCA, and (sparse) PLS-DA, operated on mass spectrometry data of patients and healthy controls were utilized in this study. The performance of exploratory PLS-DA models was assessed to determine a suitable number of latent components and variables to retain for sparse PLS-DA models. Reduced-features (sparse) PLS-DA models achieved excellent classification performance of X-linked adrenoleukodystrophy and Zellweger syndrome patients. Conclusions Our study demonstrated metabolic differences between healthy controls, neurological patients, and peroxisomal disorder (X-linked adrenoleukodystrophy and Zellweger syndrome) patients, refined classification models and showed the potential utility of hexacosanoylcarnitine (C26:0-carnitine) as a screening analyte for Chinese patients in the context of a multivariate discriminant model predictive of peroxisomal disorders.

Abstract Background Hepatoid adenocarcinoma of the stomach (HAS) is a highly malignant and rare extrahepatic tumor. The prognosis is controversial because of its rarity and the lack of multi-center cohort studies, especially on the influence of serum Alpha-fetoprotein (AFP) level on prognosis. We aimed to analyze the clinicopathological characteristics and prognosis of HAS, particularly the effect of serum AFP on the prognosis of HAS. Methods We retrospectively reviewed clinical data of one HAS patient treated at our institution in 2019 and of 252 patients reported between 1984 and 2020 in research databases. Results Among these patients, 60.1% were > 60 years, 51% had lesions in the gastric antrum, and 51.0% (73/143) had the ulcerative lesion type. The preoperative elevated levels of serum alpha-fetoprotein (AFP) were detected in most patients (76.7%). Lymph-node (84.6%) and preoperative liver metastasis (39.1%) were often found. The high-AFP group was characterized by a higher rate of stage IV (P = 0.000682) and liver metastasis (P = 0.000068). The 1-, 3-and 5-year progression-free survival(PFS) rates were 41%, 18%, and 0%, and the 1-, 3-, and 5-year overall survival (OS) rates were 64%, 26%, and 21%, respectively. The survival analysis showed that OS was significantly shorter for HAS with high-AFP (> 300 ng/ml) than with low-AFP (≤ 300 ng/ml) (P = 0.023). The univariate analysis indicated that the OS of HAS was associated with tumor location, pTNM stage, lymph-node metastasis, surgical resection, and serum AFP > 300 ng/ml. However,the prognostic factors for PFS was only pTNM stage and surgical resection. The multivariate analysis confirmed that the independent prognostic factor affecting OS of HAS included pTNM stage and surgical resection. Conclusions Liver metastasis was increasingly more likely with increasingly higher serum AFP, but the prognosis of HAS is not necessarily poor. Serum AFP level is an important prognostic indicator in HAS and should be monitored.

Abstract The fabrication of one-dimensional (1D) magnetic systems on solid surfaces, although of high fundamental interest, has yet to be achieved for a crossover between two-dimensional (2D) magnetic layers and their associated 1D spin chain systems. In this study, we report the fabrication of 1D single-unit-cell-width CrCl3 atomic wires and their stacked few-wire arrays on the surface of a van der Waals (vdW) superconductor NbSe2. Scanning tunneling microscopy/spectroscopy and first-principles calculations jointly revealed that the single wire shows an antiferromagnetic large-bandgap semiconducting state in an unexplored structure different from the well-known 2D CrCl3 phase. Competition among the total energies and nanostructure-substrate interfacial interactions of these two phases result in the appearance of the 1D phase. This phase was transformable to the 2D phase either prior to or after the growth for in situ or ex situ manipulations, in which the electronic interactions at the vdW interface play a nontrivial role that could regulate the dimensionality conversion and structural transformation between the 1D-2D CrCl3 phases.

An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a multi-stage computation. The first stage is linear filtering. The second stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of the linear filters in quadrature phase. The third stage is normalization, in which a local population of complex cells mutually inhibit one another. Because the population includes cells tuned to a range of orientations and spatial frequencies, the result is that the responses are effectively normalized by the local stimulus contrast. Here, using evidence from human functional MRI, we show that the classical model fails to account for the relative responses to two classes of stimuli: straight, parallel, band-passed contours (gratings), and curved, band-passed contours (snakes). The snakes elicit fMRI responses that are about twice as large as the gratings, yet a traditional divisive normalization model predicts responses that are about the same. Motivated by these observations and others from the literature, we implement a divisive normalization model in which cells matched in orientation tuning ("tuned normalization") preferentially inhibit each other. We first show that this model accounts for differential responses to these two classes of stimuli. We then show that the model successfully generalizes to other band-pass textures, both in V1 and in extrastriate cortex (V2 and V3). We conclude that even in primary visual cortex, complex features of images such as the degree of heterogeneity, can have large effects on neural responses.

Background The study aims to explore diagnostic value of albumin/fibrinogen ratio (AFR) and C-reactive protein (CRP)/albumin (ALB)/globulin (GLO) ratio (CAGR) for periprosthetic joint infection (PJI). Methods A retrospective analysis was conducted on clinical data collected from 190 patients who had joint replacement surgery in Qilu Hospital of Shandong University (Qingdao), from January 2017 to December 2022. Based on the occurrence of PJI after surgery, patients were divided as an infection group (10 cases) and non-infection group (180 cases). Diagnostic indicators were analyzed, univariate and multivariate logistic regression analyses were further performed to identify factors related to PJI. Sensitivity and specificity of AFR and CAGR, both individually and in combination, were calculated using ROC curves, and their diagnostic performance was compared based on the area under the curve (AUC). Results Levels of CRP, ESR, FIB, GLO, and CAGR were significantly higher in the infection group than in non-infection group (P < 0.05). Levels of ALB and AFR were significantly lower in infection group (P < 0.05). Multivariate logistic regression analysis reviewed that CRP (OR = 3.324), ESR (OR = 2.118), FIB (OR = 3.142), ALB (OR = 0.449), GLO (OR = 1.985), AFR (OR = 0.587), and CAGR (OR = 2.469) were factors influencing PJI (P < 0.05). The AUC for AFR and CAGR in diagnosing PJI were 0.739 and 0.780, while AUC for their combined detection was 0.858. Conclusion Abnormal levels of AFR and CAGR are associated with PJI, and their combined use has certain diagnostic value for PJI.

Metal–insulator transition has long been one of the key subjects in condensed matter systems. Herein, the emergence of a large energy gap (Eg, 0.8–1.0 eV) in Bi(110) two‐atomic‐layer nanoribbons grown on a SnSe(001) substrate is reported, which normally has an intrinsic semimetal‐like characteristic. The existence of this abnormally large Eg in Bi(110) is, however, determined by Bi coverage. When coverage is above ≈64 ± 2%, Eg vanishes, and instead, a Bi(110) semimetal‐like phase appears through a singular insulator–metal transition. Measurements using qPlus atomic force microscopy demonstrate that either insulating or semimetal‐like Bi(110) possesses a distorted black phosphorous structure with noticeable atomic buckling. Density function theory fully reproduces the semimetal‐like Bi(110) on SnSe(001). However, none of the insulating phases with this large Eg could be traced. Although the underlying mechanism of the large Eg and the insulator‐metal transition requires further exploration, experiments demonstrate that similar results can be achieved for Bi grown on SnS, the structural analog of SnSe, exhibiting an even larger Eg of ≈2.3 eV. The experimental strategy may be generalized to utilization of group‐IV monochalcogenides to create Bi(110) nanostructures with properties unachievable on other surfaces, providing an intriguing platform for exploring the interesting quantum electronic phases.

Negative Poisson's ratio as the anomalous characteristic generally exists in artificial architectures, such as re‐entrant and honeycomb structures. The structures with negative Poisson's ratio have attracted intensive attention due to their unique auxetic effect and many promising applications in shear‐resistant and energy absorption fields. However, experimental observation of negative Poisson's ratio in natural materials barely happens, although various 2D layered materials are predicted in theory. Herein, the anisotropic Raman response and the intrinsic intralayer negative Poisson's ratio of 2D natural black arsenic (b‐As) via strain engineering strategy are reported. The results are evident by the detailed Raman spectrum of b‐As under uniaxial strain together with density functional theory calculations. It is found that b‐As is softer along the armchair than zigzag direction. The anisotropic mechanical features and van der Waals interactions play essential roles in strain‐dependent Raman shifts and negative Poisson's ratio in the natural b‐As along zigzag direction. This work may shed a light on the mechanical properties and potential applications of 2D puckered materials.

ABSTRACTThe aim of atom electronics, i.e. the final scale of electronics, is to make use of specific individual atoms as active electronic components. Here, we review recent researches on atom electronics in single-molecule transistors (SMTs) through single-atom access and manipulation. We begin by describing the basic concepts and characteristics of atom electronics in SMTs, before discussing some of the most recent examples, including atomic transistors and atomic storage. In our concluding remarks, we discuss some perspectives on fabrication, integration, and other potential atomic devices in which high precision access to, and manipulation of single atoms could be of great significance. This will affect integrated circuits, quantum computing, and other devices that will drive the electronics of the future.