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ObjectiveTo analyze the factors affecting the cost of hospitalization for patients and provide insights using the intrauterine lesion surgery group (DRG code NE19) as an example.MethodsThis study was a retrospective cross-sectional study, with data from the first page of medical records of patients enrolled under NE19 at a comprehensive tertiary hospital in Beijing from March 15, 2022 to November 30, 2023. Influence factor selection and multifactorial linear regression analysis were conducted with hospitalization cost as the dependent variable, and patient's basic information, treatment information and key concern factors as independent variables. The profit and loss of medical records containing key factors and differences in indicators of hospitalization cost structure were analyzed in the context of clinical practice.ResultsA total of 2213 valid medical records (all female patients) were included, with patients predominantly young and middle-aged women under 45 years of age (72.12%), and with 931 day surgery medical records (42.07%). The diagnosis records included 334(15.09%) multiple uterine leiomyomas, and 246(11.12%) pelvic adhesions. A total of 150(6.78%) medical records involved ovary- and tubal-related surgeries or manipulations, with 160(7.23%) main operations being laparoscopic hysterectomy of diseased uterine lesions and 38(1.72%) mechanical rotational excision of abnormal uterine tissue using transhysteroscopy. Linear regression analysis showed that whether or not ovarian and tubal surgical operations were involved (βi=0.30), whether or not the main operation was laparoscopic hysterectomy for uterine lesions (βi=0.30), and whether or not transhysteroscopic mechanical rotational excision of abnormal uterine tissue was used (βi=0.20) had a greater impact on hospitalization costs. In the analysis of the focal factors, the percentage of patients who experienced a deficit was higher for surgical operations involving the ovaries and fallopian tubes, whether the primary operation was laparoscopic hysterotomy for uterine lesions, multiple uterine leiomyosarcomas, and pelvic adhesions (all P < 0.05), and "whether or not transhysteroscopic mechanical rotational excision of abnormal uterine tissues was used" and "whether it was a day surgery" had a significant effect on several structural indicators of hospitalization costs (all P < 0.05).ConclusionsThe NE19 group of hospitals in the study had a high loss rate, and factors such as the severity of the patient's condition and the use of new technologies affected hospitalization costs, suggesting that there is room for further optimization of the existing grouping scheme. Tiered payment standards can be set up for different tiers of healthcare institutions, and a sound and optimized exclusion mechanism can be used to promote the development of new technologies. The internal management of hospitals should encourage the development of daytime surgery to improve the efficiency of medical services.

Abstract Background Spinal cord injury (SCI) often leads to a loss of motor and sensory function. Axon regeneration and outgrowth are key events for functional recovery after spinal cord injury. Endogenous growth of axons is associated with a variety of factors. Inspired by the relationship between developing nerves and blood vessels, we believe spinal cord-derived microvascular endothelial cells (SCMECs) play an important role in axon growth. Results We found SCMECs could promote axon growth when co-cultured with neurons in direct and indirect co-culture systems via downregulating the miR-323-5p expression of neurons. In rats with spinal cord injury, neuron-targeting nanoparticles were employed to regulate miR-323-5p expression in residual neurons and promote function recovery. Conclusions Our study suggests that SCMEC can promote axon outgrowth by downregulating miR-323-5p expression within neurons, and miR-323-5p could be selected as a potential target for spinal cord injury repair. Graphical Abstract

This paper proposes a new adaptive approach called adaptive mean (ADM) that combines the strengths of trimming and winsorization to minimize the mean square error (MSE). ADM will contribute significantly to insurers by enabling them to mitigate risk exposure caused by inaccurate premium estimation and establish more precise premiums for their clients. Furthermore, the proposed mean offers several pros compared to the conventional mean. It facilitates the natural and intuitive calculation of risk loading, identifies and measures the impact of large claims, and analyzes premium susceptibility to skewed risk by capturing the tails of the relevant loss models. In addition, this paper reviews two established, robust credibility methods (trimming and winsorization). It compares them with our proposed method, resulting in a more reliable and robustly accurate method for credibility premium estimation. We presented and analyzed two real data sets from engineering insurance companies and the Wisconsin Office of the Insurance Commissioner to highlight the advances of ADM in minimizing the MSE and building more robust credibility models that are less vulnerable to outlier events and model uncertainty.

In recent years, black phosphorus, a new two-dimensional nanomaterial, has been widely used in sensors and analytical instrumentation due to its tunable band gap, high electron mobility and large specific surface area. This article introduces the structure and properties of black phosphorus and its preparation methods, and reviews recent progress in the application of electrochemical sensors based on black phosphorus for the detection of nutrients and harmful substances in foods, harmful substances in food packaging materials. Finally, we summarize the problems in the application of black phosphorus-based electrochemical sensors and provides some suggestions to solve these problems.

Abstract The significant role of the cathodic binder in modulating mass transport within the catalyst layer (CL) of fuel cells is essential for optimizing cell performance. This investigation focuses on enhancing the membrane electrode assembly (MEA) through the utilization of a short‐side‐chain perfluoro‐sulfonic acid (SSC‐PFSA) ionomer as the cathode binder, referred to as SSC‐MEA. This study meticulously visualizes the distinctive interpenetrating networks of ionomers and catalysts, and explicitly clarifies the triple‐phase interface, unveiling the transport‐friendly microstructure and transport mechanisms inherent in SSC‐MEA. The SSC‐MEA exhibits advantageous microstructural features, including a better‐connected ionomer network and well‐organized hierarchical porous structure, culminating in superior mass transfer properties. Relative to the MEA bonded by long‐side‐chain perfluoro‐sulfonic acid (LSC‐PFSA) ionomer, noted as LSC‐MEA, SSC‐MEA exhibits a notable peak power density (1.23 W cm−2), efficient O2 transport, and remarkable proton conductivity (65% improvement) at 65 °C and 70% relativity humidity (RH). These findings establish crucial insights into the intricate morphology‐transport‐performance relationship in the CL, thereby providing strategic guidance for developing highly efficient MEA.

MicroRNAs (miRNAs) are small noncoding RNAs of 18–25 bases. miRNAs are also important new biomarkers that can be used for disease diagnosis in the future. Studies have shown that miR-124 levels are significantly elevated during acute myocardial infarction (AMI) and play a key role in the cardiovascular system. A variety of methods have been established to detect myocardial infarction-related miRNAs. However, most require complex miRNA extraction and isolation, and these methods are virtually undetectable when RNA levels are low in the sample. It may lead to biased results. Thus, it is necessary to develop a technique that can detect miRNA without extracting it, which means that intracellular detection is of great significance. Here, we improved the traditional silicon spheres and obtained a biosensor that could effectively capture and detect specific noncoding nucleic acids through the layer-by-layer assembly method. The sensor is protected by hyaluronic acid so it can successfully escape the lysosome into the cell and achieve detection. With the help of a full-featured microplate reader, we determined that the detection limit of the biosensor could reach 1 fM, meeting the needs of intracellular detection. At the same time, we prepared an oxidative stress cardiomyocyte infarction model and successfully captured the overexpressed miR-124 in the infarcted cells to achieve in situ detection. This study could provide a new potential tool to develop miRNAs for sensitive diagnosis in AMI, and the proposed strategy implies its potential for biomedical research.

Albumin has a variety of biological functions, such as immunomodulatory and antioxidant activity, which depends largely on its thiol activity. However, in clinical trials, the treatment of albumin by injection of commercial human serum albumin (HSA) did not achieve the desired results. Here, we constructed reduced modified albumin (SH-Alb) for in vivo and in vitro experiments to investigate the reasons why HSA did not achieve the expected effects. SH-Alb was found to delay the progression of liver fibrosis in mice by alleviating liver inflammation and oxidative stress. Although R-Alb also has some of the above roles, the effect of SH-Alb is more remarkable. Mechanism studies have shown that SH-Alb reduces the release of pro-inflammatory and pro-fibrotic cytokine through the mitogen-activated protein kinase (MAPK) signaling pathway. In addition, SH-Alb deacetylates SOD2, a key enzyme of mitochondrial reactive oxygen species (ROS) production, by promoting the expression of SIRT3, thereby reducing the accumulation of ROS. Finally, macrophages altered by R-Alb or SH-Alb can inhibit the activation of hepatic stellate cells and endothelial cells, further delaying the progression of liver fibrosis. These results indicate that SH-Alb can remodel the phenotype of macrophages, thereby affecting the intrahepatic microenvironment and delaying the process of liver fibrosis. It provides a good foundation for the application of albumin in clinical treatment.

Abstract In recent decades, rising air temperatures (AT) and apparent temperatures (AP) have posed growing health risks. In the context of China's rapid urbanization and global climate change, it is crucial to understand the impact of urban land use/land cover (LULC) changes on AP. This study investigates the spatial distribution and long-term variation patterns of AT and AP, using data from 834 meteorological stations across China from 1996 to 2020. It also explores the relationship between AT, AP, and LULC in the urban core areas of 30 major cities. Study reveals that AT and AP exhibit overall high spatial similarity, albeit with greater spatial variance in AP. Notably, regions with significant disparities between the two have been identified. Furthermore, it's observed that the spatial range of high AP change rates is wider than that of AT. Moreover, the study suggests a potential bivariate quadratic function relationship between ΔT (the difference between AT and AP) and Wa_ratio and Ar_ratio, indicating the presence of a Least Suitable Curve (LSC), $${\text{W}}_{{\text{a}}} \_{\text{ratio}} = {0}{{.263(}} \pm {0}{{.0269)}} - {0}{{.437(}} \pm {0}{{.0417)}} \times {\text{Ar}}\_{\text{ratio}}$$ W a _ ratio = 0 . 263 ( ± 0 . 0269 ) - 0 . 437 ( ± 0 . 0417 ) × Ar _ ratio . Urban LULC planning should carefully avoid intersecting with this curve. These findings can provide valuable insights for urban LULC planning, ultimately enhancing the thermal comfort of urban residents.

Abstract Mimicking living creatures, soft robots exhibit incomparable adaptability and various attractive new features. However, untethered insect-scale soft robots are often plagued with inferior controllability and low kinetic performance. Systematically inspired by the swift swingable abdomen, conducting canals for secretion transport, and body setae of Stenus comma, together with magnetic-induced fast-transformed postures, herein, we present a swift, agile untethered millimetre-scale soft propulsor propelling on water. The demonstrated propulsor, with a body length (BL) of 3.6 mm, achieved a recorded specific speed of ~201 BL/s and acceleration of ~8,372 BL/s2. The comprehensive kinetic performance of this propulsor surpasses those of previous ones at similar scales by several orders. Notably, we discovered momentum-transfer-induced over-biological on-demand braking (deceleration ~−5,010 BL/s2) and elucidated the underlying hydrodynamics. This work offers new insights into systematically bio-inspired artificial insect-scale soft robots, enabling them to push boundaries in performance, and potentially revolutionizing robot design, optimization, and control paradigms.

Muscles generate varying levels of force by recruiting different numbers of motor units (MUs), and as the force increases, the number of recruited MUs gradually rises. However, current decoding methods encounter difficulties in maintaining a stable and consistent growth trend in MU numbers with increasing force. In some instances, an unexpected reduction in the number of MUs can even be observed as force intensifies. To address this issue, in this study, we propose an enhanced decoding method that adaptively reutilizes MU filters. Specifically, in addition to the normal decoding process, we introduced an additional procedure where MU filters are reused to initialize the algorithm. The MU filters are iterated and adapted to the new signals, aiming to decode motor units that were actually activated but cannot be identified due to heavy superimposition. We tested our method on both simulated and experimental surface electromyogram (sEMG) signals. We simulated isometric signals (10%-70%) with known MU firing patterns using experimentally recorded MU action potentials from forearm muscles and compared the decomposition results to two baseline approaches: convolution kernel compensation (CKC) and fast independent component analysis (fastICA). Our method increased the decoded MU number by a rate of 135.4% $\pm ~62.5$ % and 63.6% $\pm ~20.2$ % for CKC and fastICA, respectively, across different signal-to-noise ratios. The sensitivity and precision for MUs decomposed using the enhanced method remained at the same accuracy level (p $\pm ~10.9$ % across all subjects. We discussed the possibility of fully capturing all activated motor units by appropriately reusing previously decoded MU filters and improving the balance of activated motor unit numbers across varying excitation levels.

Human–robot (HR) collaboration (HRC) is an emerging research field because of the complementary advantages of humans and robots. An HRC framework for robotic assembly based on impedance control is proposed in this paper. In the HRC framework, the human is the decision maker, the robot acts as the executor, while the assembly environment provides constraints. The robot is the main executor to perform the assembly action, which has the position control, drag and drop, positive impedance control, and negative impedance control modes. To reveal the characteristics of the HRC framework, the switch condition map of different control modes and the stability analysis of the HR coupled system are discussed. In the end, HRC assembly experiments are conducted, where the HRC assembly task can be accomplished when the assembling tolerance is 0.08 mm or with the interference fit. Experiments show that the HRC assembly has the complementary advantages of humans and robots and is efficient in finishing complex assembly tasks.

Abstract Heart failure (HF) is a disease with high mortality and morbidity rate. Autophagy is critically implicated in HF progression. The current research was designed to investigate the function of Dioscin on oxidative stress, autophagy, and apoptosis in HF. In this study, doxorubicin (Dox) was employed to induce HF model and HL‐1 cell damage model. Echocardiography implied that Dioscin could dramatically relieve heart function in vivo. Western blotting determined that Dioscin treatment reversed the promotive effect of autophagy caused by Dox through modulating levels of key autophagy‐associated molecules, including Atg5 and Beclin1. Dioscin also impaired apoptosis by regulating apoptosis‐related protein, including Bcl‐2 and cleaved caspase‐3 following Dox treatment in vivo and in vitro. Furthermore, the impacts of Dioscin were mediated by upregulation of PDK1‐mediated Akt/mTOR signaling. The mTOR inhibitor (rapamycin) could counteract the therapeutic impact of Dioscin in vitro. Taken together, Dioscin could relieve cardiac function through blocking apoptosis and autophagy by activating the PDK1‐elicited Akt/mTOR pathway.

Background: The effects of heat acclimation (HA) on the hypothalamus after exertional heatstroke (EHS) and the specific mechanism have not been fully elucidated, and this study aimed to address these questions. Methods: In the present study, rats were randomly assigned to the control, EHS, HA, or HA + EHS groups (n = 9). Hematoxylin and eosin (H&E) staining was used to examine pathology. Tandem mass tag (TMT)-based proteomic analysis was utilized to explore the impact of HA on the protein expression profile of the hypothalamus after EHS. Bioinformatics analysis was used to predict the functions of the differentially expressed proteins. The differential proteins were validated by western blotting. An enzyme-linked immunosorbent assay was used to measure the expression levels of inflammatory cytokines in the serum. Results: The H&E staining (n = 5) results revealed that there were less structural changes in hypothalamus in the HA + EHS group compared with the EHS group. Proteomic analysis (n = 4) revealed that proinflammatory proteins such as argininosuccinate synthetase (ASS1), high mobility group protein B2 (HMGB2) and vimentin were evidently downregulated in the HA + EHS group. The levels of interleukin (IL)-1β, IL-1, and IL-8 were decreased in the serum samples (n = 3) from HA + EHS rats. Conclusions: HA may alleviate hypothalamic damage caused by heat attack by inhibiting inflammatory activities, and ASS1, HMGB2 and vimentin could be candidate factors involved in the exact mechanism.

Abstract Catalytic glycosylation is a vital transformation in synthetic carbohydrate chemistry due to its ability to expediate the large-scale oligosaccharide synthesis for glycobiology studies with the consumption of minimal amounts of promoters. Herein we introduce a facile and efficient catalytic glycosylation employing glycosyl ortho−2,2-dimethoxycarbonylcyclopropylbenzoates (CCBz) promoted by a readily accessible and non-toxic Sc(III) catalyst system. The glycosylation reaction involves a novel activation mode of glycosyl esters driven by the ring-strain release of an intramolecularly incorporated donor-acceptor cyclopropane (DAC). The versatile glycosyl CCBz donor enables highly efficient construction of O-, S-, and N-glycosidic bonds under mild conditions, as exemplified by the convenient preparation of the synthetically challenging chitooligosaccharide derivatives. Of note, a gram-scale synthesis of tetrasaccharide corresponding to Lipid IV with modifiable handles is achieved using the catalytic strain-release glycosylation. These attractive features promise this donor to be the prototype for developing next generation of catalytic glycosylation.

IntroductionUbiquitination is a crucial biological mechanism in humans, essential for regulating vital biological processes, and has been recognized as a promising focus for cancer therapy. Our objective in this research was to discover potential enzymes associated with ubiquitination that may serve as therapeutic targets for individuals with esophageal carcinoma (ESCA).MethodsTo identify genes linked to the prognosis of ESCA, we examined mRNA sequencing data from patients with ESCA in the TCGA database. Further investigation into the role of the candidate gene in ESCA was conducted through bioinformatic analyses. Subsequently, we carried out biological assays to assess its impact on ESCA development.ResultsThrough univariate Cox regression analysis, we identified Ubiquitin Conjugating Enzyme E2 B (UBE2B) as a potential gene associated with the prognosis of ESCA. UBE2B exhibited significant upregulation and was found to be correlated with survival outcomes in ESCA as well as other cancer types. Additionally, UBE2B was observed to be involved in various biological pathways linked to the development of ESCA, including TNF-a signaling via NF-κB, epithelial-mesenchymal transition, inflammatory response, and hypoxia. Moreover, immune-related pathways like B cell activation (GO: 0042113), B cell receptor signaling pathway (GO: 0050853) and B cell mediated immunity (GO:0019724) were also involved. It was found that high expression of UBE2B was correlated with the increase of several kinds of T cells (CD8 T cells, Th1 cells) and macrophages, while effector memory T cell (Tem) and Th17 cells decreased. Furthermore, UBE2B showed potential as a prognostic biomarker for ESCA, displaying high sensitivity and specificity. Notably, proliferation and migration in ESCA cells were effectively suppressed when the expression of UBE2B was knocked down.ConclusionsTo summarize, this study has made a discovery regarding the importance of gaining new insights into the role of UBE2B in ESCA. UBE2B might be an oncogene with good ability in predicting and diagnosing ESCA. Consequently, this discovery highlights the feasibility of targeting UBE2B as a viable approach for treating patients with ESCA.

Small‐scale robots need to be agile to perform various tasks in complex environments and the design faces great challenges with limited size and power consumption. However, the advent of advanced functional materials, compliant structures/mechanisms, and flexible fabrication techniques has brought new evolution directions to robotics. These technologies enrich the robots' actuation strategies, improving their performance of small robots while simplifying the complexity of the system and thus making it possible to be applied in diverse scenarios, such as disaster rescue, medical, and environmental exploration. In nature, small organisms have shown numerous efficient survival strategies. They can easily achieve locomotion tasks with low energy consumption. For example, dragonflies complete long flights with the help of wind, and stenus (one kind of rove beetle) uses the surface tension of liquids to dodge prey quickly. Insects are usually considered to be agile, efficient, and intelligent, which is the same requirement as for small robots. Yet the corresponding bioinspired design strategies bring new opportunities and challenges to the development of small‐scale robots. Herein, the development trends of small‐scale robots are analyzed and discussed, and several potential bioinspired synergy strategies are induced, which may be useful for the future design of insect‐level soft robots.

Die Autoren gehen davon aus, dass eine Anleitung zum Tandemlernen mit kulturbezogenen Aufgaben, die die Lerner dazu motiviert, im Team jenseits des Klassenzimmers gemeinsam Aufgaben und Projekte zu bewältigen, der Sprachlernsituation im Tandem dienlich ist. Im vorliegenden Beitrag werden die Ergebnisse einer Untersuchung an der University of International Business and Economics in Beijing mit 20 deutschen und 20 chinesischen Teilnehmern dargelegt, die in Beijing mit Hilfe eines Leitfadens im Tandem Deutsch bzw. Chinesisch gelernt haben. Der Leitfaden gibt jeweils in der Muttersprache der Teilnehmenden anleitende Hinweise zur Fremdsprachenvermittlung, zum Fremdsprachenlernen und speziell zum Lernen im Tandem. Der Kern des Leitfadens sind acht Lektionen mit kulturbezogenen Aufgaben, die ausgewogen chinesische wie auch deutsche Themen beinhalten. Die Auswertung der Untersuchung anhand von 26 Umfragen und 14 Interviews mit den Projekt-Teilnehmern zeigt, dass Lernerfahrung in Sprachpartnerschaften durch Anleitungen zum Lernen im Tandem und durch kulturbezogene Aufgaben in deutsch-chinesischen Tandems verbessert werden können. In dem Beitrag werden auch die Unzulänglichkeiten dieser Studie und potentielle Richtungen für die künftige Forschung diskutiert.

Net-pen aquaculture, one of the primary forms of aquaculture in shallow lakes, has generated substantial economic benefits but has also triggered eutrophication and ecological degradation. Therefore, the accurate and scientific dynamic monitoring of aquaculture areas is of the utmost importance. However, existing studies have predominantly employed annual monitoring, failing to fully exploit the unique advantage of synthetic aperture radar (SAR) imagery for seasonal, monthly or more frequent time scale monitoring. This study aimed to develop an approach for monitoring the monthly dynamics of net-pen aquaculture using Sentinel-1 time series images. We integrated threshold segmentation and temporal consistency checking to extract spatial data on the net-pen aquaculture from eight typical shallow lakes in Jiangsu Province, one of the eastern coastal provinces of China, from 2016 to 2021. This study yielded the following results: (1) The VV polarization image offers a particularly noticeable contrast between net-pen aquaculture structures and their surroundings and checking for temporal consistency can help alleviate the problem of distinguishing between changes in error caused by misclassification and actual changes that occurred. The overall accuracy of the net-pen aquaculture extraction results was over 85%. (2) This approach not only enables the analysis of changes in the aquaculture area and fence length but can also identify key time points. For instance, the net-pen aquaculture area in Gehu Lake experienced a rapid decline from May to November 2018, the decrease in while Eastern Taihu Lake occurred from September 2018 to June 2019. (3) The removal of net-pen aquaculture in lakes within the Jiangsu Province is primarily attributed to policy responses. In response to the ecological river and lake action plan implemented in Jiangsu Province, a decrease was observed in both the aquaculture areas and fence lengths across most lakes from 2016 to 2021. These results can provide a reference for lake management and ensuring the effective implementation of related policies.

Emotion recognition using the electroencephalogram (EEG) has garnered significant attention within the realm of human–computer interaction due to the wealth of genuine emotional data stored in EEG signals. However, traditional emotion recognition methods are deficient in mining the connection between multi-domain features and fitting their advantages. In this paper, we propose a novel capsule Transformer network based on a multi-domain feature for EEG-based emotion recognition, referred to as MES-CTNet. The model’s core consists of a multichannel capsule neural network(CapsNet) embedded with ECA (Efficient Channel Attention) and SE (Squeeze and Excitation) blocks and a Transformer-based temporal coding layer. Firstly, a multi-domain feature map is constructed by combining the space–frequency–time characteristics of the multi-domain features as inputs to the model. Then, the local emotion features are extracted from the multi-domain feature maps by the improved CapsNet. Finally, the Transformer-based temporal coding layer is utilized to globally perceive the emotion feature information of the continuous time slices to obtain a final emotion state. The paper fully experimented on two standard datasets with different emotion labels, the DEAP and SEED datasets. On the DEAP dataset, MES-CTNet achieved an average accuracy of 98.31% in the valence dimension and 98.28% in the arousal dimension; it achieved 94.91% for the cross-session task on the SEED dataset, demonstrating superior performance compared to traditional EEG emotion recognition methods. The MES-CTNet method, utilizing a multi-domain feature map as proposed herein, offers a broader observation perspective for EEG-based emotion recognition. It significantly enhances the classification recognition rate, thereby holding considerable theoretical and practical value in the EEG emotion recognition domain.

Background: After spinal cord injury (SCI), the native immune surveillance function of the central nervous system is activated, resulting in a substantial infiltration of immune cells into the affected tissue. While numerous studies have explored the transcriptome data following SCI and revealed certain diagnostic biomarkers, there remains a paucity of research pertaining the identification of immune subtypes and molecular markers related to the immune system post-spinal cord injury using single-cell sequencing data of immune cells. Methods: The researchers conducted an analysis of spinal cord samples obtained at three time points (3,10, and 21 days) following SCI using the GSE159638 dataset. The SCI subsets were delineated through pseudo-time analysis, and differentiation related genes were identified after principal component analysis (PCA), cell clustering, and annotation techniques. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were employed to assess the differentiation-related genes (DRGs) across different subsets. The molecular subtypes of SCI were determined using consensus clustering analysis. To further explore and validate the correlation between the molecular subtypes and the immune microenvironment, the CIBERSORT algorithm was employed. High-value diagnostic gene markers were identified using LASSO regression, and their diagnostic sensitivity was assessed using receiver operating characteristic curves (ROC) and quantitative real-time polymerase chain reaction (qRT-PCR). Results: Three SCI subsets were obtained, and differentiation-related genes were characterized. Within these subsets, two distinct molecular subtypes, namely C1 and C2, were identified. These subtypes demonstrated significant variations in terms of immune cell infiltration levels and the expression of immune checkpoint genes. Through further analysis, three candidate biomarkers (C1qa, Lgals3 and Cd63) were identified and subsequently validated. Conclusions: Our study revealed a diverse immune microenvironment in SCI samples, highlighting the potential significance of C1qa, Lgals3 and Cd63 as immune biomarkers for diagnosing SCI. Moreover, the identification of immune checkpoints corresponding to the two molecular subtypes suggests their potential as targets for immunotherapy to enhance SCI repair in future interventions.

Abstract Background Inflammatory response is an essential part of secondary injury after spinal cord injury (SCI). During this period, the injury may be exacerbated through the release of a large number of inflammatory factors and the polarization of infiltrating macrophages and microglia towards M1. Ang-(1–7), mainly generated by Ang II via angiotensin-converting enzyme 2 (ACE2), can specifically bind to the G protein-coupled receptor Mas (MasR) and plays an important role in regulating inflammation and alleviating oxidative stress. Methods We aimed to investigate whether activating the Ang-(1–7)/MasR axis in rats after SCI can regulate local neuroinflammation to achieve functional recovery and obtain its potential mechanism. MasR expression of bone marrow-derived macrophages was determined by Western blot. Immunofluorescence, Western blot, Flow cytometry, and RT-qPCR were applied to evaluate the polarization of Ang-(1–7) on macrophages and the regulation of inflammatory cytokines. Previous evaluation of the spinal cord and bladder after SCI was conducted by hematoxylin–eosin staining, Basso, Beattie, and Bresnahan (BBB) score, inclined plate test, electrophysiology, and catwalk were used to evaluate the functional recovery of rats. Results MasR expression increased in macrophages under inflammatory conditions and further elevated after Ang-(1–7) treatment. Both in vivo and in vitro results confirmed that Ang-(1–7) could regulate the expression of inflammatory cytokines by down-regulating proinflammatory cytokines and up-regulating anti-inflammatory cytokines, and bias the polarization direction of microglia/macrophages to M2 phenotypic. After SCI, Ang-(1–7) administration in situ led to better histological and functional recovery in rats, and this recovery at least partly involved the TLR4/NF-κB signaling pathway. Conclusion As shown in our data, activating Ang-(1–7)/MasR axis can effectively improve the inflammatory microenvironment after spinal cord injury, promote the polarization of microglia/macrophages towards the M2 phenotype, and finally support the recovery of motor function. Therefore, we suggest using Ang-(1–7) as a feasible treatment strategy for spinal cord injury to minimize the negative consequences of the inflammatory microenvironment after spinal cord injury.

Text readability assessment has gained significant attention from researchers in various domains. However, the lack of exploration into corpus compatibility poses a challenge as different research groups utilize different corpora. In this study, we propose a novel evaluation framework, Cross-corpus text Readability Compatibility Assessment (CRCA), to address this issue. The framework encompasses three key components: (1) Corpus: CEFR, CLEC, CLOTH, NES, OSP, and RACE. Linguistic features, GloVe word vector representations, and their fusion features were extracted. (2) Classification models: Machine learning methods (XGBoost, SVM) and deep learning methods (BiLSTM, Attention-BiLSTM) were employed. (3) Compatibility metrics: RJSD, RRNSS, and NDCG metrics. Our findings revealed: (1) Validated corpus compatibility, with OSP standing out as significantly different from other datasets. (2) An adaptation effect among corpora, feature representations, and classification methods. (3) Consistent outcomes across the three metrics, validating the robustness of the compatibility assessment framework. The outcomes of this study offer valuable insights into corpus selection, feature representation, and classification methods, and it can also serve as a beginning effort for cross-corpus transfer learning.