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This study explores the decolonial potential of Chinese bilingual postgraduate students' translanguaging practices in English academic writing. It investigates the ways that students enact translanguaging to delink from monolingual standard English norms and integrate their authentic bilingual voices in the writing process. A case study was conducted to collect the students' written products and record and analyze their approaches and views to language use in academic writing in an English for academic purpose course. The findings reveal that students could employ the integrated multilingual repertoires to enhance learning outcomes, negotiate deficit linguistic views, and voice cultural identities in the writing process. Their translanguaging enactment transcends linguistic boundaries and English-dominated norms, providing empirical support for the decolonization of academic writing in Chinese higher education. The study underscores the importance of student-led negotiation of linguistic and cultural differences, advocating for critical engagement with translanguaging to deconstruct social inequalities perpetuated by hegemonic ideologies and promote bilingual subjectivities in non-Anglophone academic contexts.

Accurately describing the path of sheet flow (SF) is crucial in soil erosion. Raindrop impact and underlying surface conditions can affect the SF velocity by changing the velocity profile. However, since this information is rarely known, the estimation of SF velocity is inaccurate. A series of upstream inflow and rainfall experiments were carried out on an impermeable flume to determine the coupling effects of rainfall and rough bed surfaces on the SF velocity and correction factor (α). The results showed that the roughness of the bed surface had a more pronounced effect on reducing the mean velocity compared to the surface velocity in both cases with and without raindrop impact. The raindrop impact notably reduced the flow velocity near the water surface, while the mean velocity slightly decreased or remained almost constant with increasing rainfall intensity. The reduction in SF velocity can be explained by the combined effects of the roughness reducing the mean velocity (up to 33.52%) and the raindrop impact reducing the surface velocity (up to 25.43%). In addition, α was not a constant when the SF was subjected to raindrop impact. The rainfall was found to increase α, while the roughness of the bed surface reduced α for all cases. Finally, a model was created to forecast α based on the ratio of water depth to roughness height, hydraulic slope, and rain Reynolds number. The results are valuable in soil erosion by providing accurate α for estimating the surface and mean velocities of SF.

Objective: The emergence of multidrug-resistant (MDR) Escherichia coli strains has significantly constrained antibiotic treatment options, while the spread of antimicrobial resistance genes (ARGs) and mobile genetic elements exacerbates the situation. This study delves into an MDR E. coli strain, QMM-01, which uniquely co-expresses β-lactamases from all four recognized classes, aiming to uncover the underlying mechanisms of its resistance and assess its potential for global spread. Methods: E. coli QMM-01, isolated from a burn patient, underwent antibiotic susceptibility testing through standard automated procedures commonly employed in clinical settings, with further test by immunochromatographic tests for carbapenemases. For genomic insights, whole-genome sequencing (WGS) was performed using both PacBio Sequel and Illumina NovaSeq platforms, supplemented by bioinformatics analyses to predict antimicrobial resistance genes, determining serotypes, performing multilocus sequence typing, and conducting comparative genomic analysis. Results: QMM-01 exhibited resistance to a broad spectrum of β-lactam antibiotics, including carbapenems and ceftazidime-avibactam, with aztreonam being the sole exception. The resistance profile of the strain might primarily be due to the production of class B metallo-β-lactamases. WGS revealed the presence of a chimeric plasmid, pQMM-2-NDM-5, carrying the blaNDM-5 gene and exhibiting similarities with plasmids from diverse geographical regions. This plasmid contains 161 predicted coding sequences and harbors resistance genes for 13 different antibiotics, forming a resistance island with a complex genetic environment. Conclusion: This study underscores the global challenge posed by antibiotic resistance and emphasizes the need for international collaboration in antibiotic stewardship to mitigate the spread of resistance genes.

Abstract Intracranial germ cell tumors (GCTs) are rare neoplasms with a peak incidence in adolescents. Germinoma is the most common histological subtype of intracranial GCTs. Its symptoms include intracranial hypertension, visual field defects, and hormonal disorders, affecting the physical health of adolescents. Germinoma is sensitive to chemo-radiotherapy, and most patients do not require neurosurgical resection. Therefore, improving the accuracy of germinoma diagnosis helps to avoid unnecessary surgery. At present, the application of artificial intelligence (AI) in medical imaging has improved the accuracy of disease diagnosis. However, few studies focused on the AI model to diagnosis germinoma and there are no publicly available imaging datasets for germinoma. This study aimed to create a comprehensive dataset for germinoma using magnetic resonance imaging/computed tomography findings with clinical and radiomic data to train and validate AI models. Featuring 65 pathologically confirmed germinomas, the dataset included axial T2-weighted imaging, T2-weighted fluid-attenuated inversion recovery, T1-weighted imaging, T1-weighted imaging with contrast enhancement, diffusion-weighted MR imaging, CT images, clinical data, and morphological and radiomic-based features obtained by segmentation.

Abstract The Lightv8nPnP lightweight visual positioning algorithm model has been introduced to make deep learning-based drone visual positioning algorithms more lightweight. The core objective of this research is to develop an efficient visual positioning algorithm model that can achieve accurate 3D positioning for drones. To enhance model performance, several optimizations are proposed. Firstly, to reduce the complexity of the detection head module, GhostConv is introduced into the detection head module, constructing the GDetect detection head module. Secondly, to address the issues of imbalanced sample difficulty and uneven pixel quality in our custom dataset that result in suboptimal detection performance, Wise-IoU is introduced as the model’s bounding box regression loss function. Lastly, based on the characteristics of the drone aerial dataset samples, modifications are made to the YOLOv8n network structure to reduce redundant feature maps, resulting in the creation of the TrimYOLO network structure. Experimental results demonstrate that the Lightv8nPnP algorithm reduces the number of parameters and computational load compared to benchmark algorithms, achieves a detection rate of 186 frames per second, and maintains a positioning error of less than 5.5 centimeters across the X, Y, and Z axes in three-dimensional space.

Abstract Nutrient competition with indigenous microbes or pathogens presents a significant challenge for oral probiotic efficacy. To address this issue, we develop an ameba-inspired food-carrying strategy (AIFS) by prebinding ginger-derived exosome-like nanoparticles (GELNs) onto probiotics as food depots. AIFS enables probiotics to efficiently and exclusively consume GELNs in situ, even in the presence of competing bacteria. This results in up to 21 times higher uptake efficiency compared to unengineered probiotics, dramatically accelerating probiotic proliferation. Meanwhile, AIFS potentiates probiotics’ resistance to multiple GI stressors. In a murine model of colitis, AIFS can improve the abundance of probiotics and inhibit pathogens, maintaining intestinal flora homeostasis. Additionally, it can upregulate the anti-inflammatory IL-10, reduce the proinflammatory IL-1β, and repair damaged intestinal mucus. Thereby, AIFS displays potently elevated prophylactic and therapeutic efficacy for colitis mice. This work provides a method for microbial engineering, with broad implications for microbiotherapy and gut health.

Abstract The quantum anomalous Hall effect in layered antiferromagnet MnBi2Te4 harbors a rich interplay between magnetism and topology, holding a significant promise for low-power electronic devices and topological antiferromagnetic spintronics. In recent years, MnBi2Te4 has garnered considerable attention as the only known material to exhibit the antiferromagnetic quantum anomalous Hall effect. However, this field faces significant challenges as the quantization at zero magnetic field depending critically on fabricating high-quality devices. In this article, we introduce a straightforward yet effective method to mitigate the detrimental effect of the standard fabrication on MnBi2Te4 by depositing an AlOx layer on the surface before fabrication. Optical contrast and magnetotransport measurements on over 50 MnBi2Te4 demonstrate that AlOx can effectively preserve the pristine states of the devices. Surprisingly, we find this simple method can significantly enhance the anomalous Hall effect towards quantization, which resolves a longstanding challenge in the field of MnBi2Te4. Scaling relation analysis further reveals the intrinsic mechanism of anomalous Hall effect dominated by Berry curvature at various magnetic configuration. By tuning the gate voltage, we uncover a gate independent magnetism in odd-layer MnBi2Te4 devices. Our experiments not only pave the way for the fabrication of high-quality dissipationless transport devices, but also advance the investigation of exotic topological quantum phenomena in 2D materials.

Abstract Background Generative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer has not yet been fully evaluated. The objective of this study was to evaluate the accuracy, reliability and validity of GenAI in addressing questions related to remote consultations for oral cancer. Methods A search was conducted on telemedicine platforms in China, summarizing patients’ inquiries regarding oral cancer. A panel of board-certified oral surgeons compiled the reference answers for addressing these questions. GPT-3.5-turbo and GPT-4o were tasked to answer specific questions related to oral cancer, with their responses recorded. The responses were assessed using qualitative and quantitative measures, including the accuracy, the number of key points, text length, lexical density, and a Likert scale. The chi-square test was utilized to detect differences in qualitative data, while Kruskal-Wallis test, Mann-Whitney U test and t-test for quantitative data. Results A total of 34 oral cancer questions were included, covering basic, etiology, diagnosis, intervention, and prognosis. GPT-3.5-Turbo demonstrated an overall accuracy rate of 77.50% in qualitative analysis, and GPT-4o was 88.20%. The average scores of GPT-3.5Turbo and GPT-4o were 3.96 and 4.35, respectively, with statistically significant differences. GPT-3.5-Turbo and GPT-4o were close to the reference answers in terms of the number of key points, but significantly lower in terms of text length and lexical density. Conclusion GPT-4o demonstrated a marginal advantage, although no statistically significant differences in response accuracy were observed between GPT-3.5-Turbo and GPT-4o. Moreover, GPT-4o outperformed in terms of reliability and validity, making it more appropriate for remote consultation scenarios.

Abstract Objective This study aims to assess the effectiveness and safety of mesenchymal stem cell (MSC) transplantation in the treatment of autoimmune and rheumatic immune diseases through randomized controlled trials (RCTs). Methods Two researchers conducted a comprehensive search of Chinese and English databases from their inception until Dec. 2023. The literature screening and data extraction were then performed. Statistical analysis was carried out using RevMan 5.4 software. Results A total of 42 relevant RCTs, involving 2,183 participants, were ultimately included in this study. These RCTs encompassed four types of rheumatic immune and bone diseases, namely rheumatoid arthritis (RA), osteoarthritis (OA), spondyloarthritis, systemic sclerosis arthritis, systemic lupus erythematosus (SLE), inflammatory bowel disease, multiple sclerosis, primary Sjögren’s syndrome (PSS). The systematic review indicates that MSC transplantation may improve spondyloarthritis, RA, PSS. The meta-analysis reveals that MSC transplantation significantly improved symptoms in patients with OA [VAS (visual analogue scale): bone marrow: SMD = − 0.95, 95% CI − 1.55 to − 0.36, P = 0.002; umbilical cord: SMD = − 1.25, 95% CI − 2.04 to − 0.46, P = 0.002; adipose tissue: SMD = -1.26, 95% CI -1.99 to − 0.52, P = 0.0009)], SLE [Systemic lupus erythematosus disease activity index (SLEDAI): SMD = − 2.32, 95% CI − 3.59 to − 1.06, P = 0.0003], inflammatory bowel disease [clinical efficacy: RR = 2.02, 95% CI 1.53 to 2.67, P

Abstract The aim of this study is to evaluate GPT-4's reasoning ability to interpret oral mucosal disease photos and generate structured reports from free-text inputs, while exploring the role of prompt engineering in enhancing its performance. Prompt received by utilizing automatic prompt engineering and knowledge of oral physicians, was provided to GPT-4 for generating structured reports based on cases of oral mucosal disease. The structured reports included 7 fine-grained items: “location”, “shape”, “number”, “size”, “clinical manifestation”, “the border of the lesion” and “diagnosis”. 120 cases were used for testing, which were divided into two datasets, textbook dataset and internet dataset. Oral physicians evaluated GPT-4's responses by confusion matrices, receiving recall and accuracy. ANOVA and Wald χ2 tests with Bonferroni correction were used to statistical analysis. A total of 120 cases of oral mucosal diseases were included, encompassing the following two datasets: textbook dataset (n = 60), internet dataset (n = 60). GPT-4 had higher recall with the textbook dataset compared to the internet dataset (90.73% vs 89.12%; P = .462, χ2 = 0.54) and higher accuracy (87.05% vs 84.87%; P = .393, χ2 = 0.73). Performance varied by items of structured reports within each dataset, with “size” achieving the highest accuracy in the textbook dataset (98.90%) and “the border the lesion” in the internet dataset (95.00%). GPT-4 can transform incomplete descriptive text corresponding to oral mucosal disease photographs into structured reports with the assistance of carefully designed prompts. This study highlights GPT-4's potential in complex and multimodal medical tasks and underscores the importance of prompt engineering in optimizing its capabilities. Nevertheless, achieving further improvements in the model may require more comprehensive and focused efforts. This article demonstrated the capabilities of large multimodal models, represented by GPT-4, in medical photographs interpretation and medical report generation. GPT-4 was capable of recognizing photographs of oral mucosal diseases and generating structured reports, which facilitates telemedicine and peer-to-peer communication.

Abstract Total-body CT scans are useful in saving trauma patients; however, interpreting numerous images with varied window settings slows injury detection. We developed an algorithm for “unified total-body CT image with multiple organ-specific windowings (Uni-CT)”, and assessing its impact on physician accuracy and speed in trauma CT interpretation. From November 7, 2008, to June 19, 2020, 40 cases of total-body CT images for blunt trauma with multiple injuries, were collected from the emergency department of Osaka General Medical Center and randomly divided into two groups. In half of the cases, the Uni-CT algorithm using semantic segmentation assigned visibility-friendly window settings to each organ. Four physicians with varying levels of experience interpreted 20 cases using the algorithm and 20 cases in conventional settings. The performance was analyzed based on the accuracy, sensitivity, specificity of the target findings, and diagnosis speed. In the proposal and conventional groups, patients had an average of 2.6 and 2.5 targeting findings, mean ages of 51.8 and 57.7 years, and male proportions of 60% and 45%, respectively. The agreement rate for physicians’ diagnoses was κ = 0.70. Average accuracy, sensitivity, and specificity of target findings were 84.8%, 74.3%, 96.9% and 85.5%, 81.2%, 91.5%, respectively, with no significant differences. Diagnostic speed per case averaged 71.9 and 110.4 s in each group (p

Abstract Endometrial cancer (EC) is a significant health threat to women, with recurrence after treatment posing a major challenge. While abnormal cholesterol metabolism has been implicated in EC progression, the underlying mechanisms remain unclear. In this study, we identified lanosterol synthase (LSS) as a key mediator in cholesterol metabolism associated with EC. We found that LSS is significantly upregulated in EC tissues. Functional assays revealed that LSS promotes cell proliferation and migration, inhibits apoptosis, and drives tumor growth in vivo. Mechanistically, LSS exerts dual effects by accumulating cholesterol esters, thereby enhancing EC cell growth, and activating the MAPK/JNK signaling pathway. Importantly, inhibition of LSS with the specific inhibitor Ro 48-8071 not only reduced EC cell proliferation and suppressed xenograft tumor growth but also inhibited the growth of patient-derived tumor-like cell clusters (PTCs). These findings establish LSS as a novel oncogene in EC, promoting tumor progression through MAPK/JNK signaling activation and cholesterol ester accumulation, and highlight the therapeutic potential of targeting LSS in EC treatment.

Abstract Background The long peripheral intravenous catheter (long PIVC), a type of PIVC, has an indwelling time of 5–14 days and is one of the options for antibacterial therapy. However, there is no consensus regarding the impact of insertion site selection on the complications associated with long PIVCs. Methods This randomized controlled trial included 90 participants randomly assigned to either the control or experimental group, with 45 patients in each group. In the control group, long PIVCs were placed in the forearm, while in the experimental group, they were inserted in the upper arm. The primary outcome was catheter-related complications, while secondary outcomes included the first-attempt insertion success rate, total procedure time, and indwelling catheter duration. Results The incidence of catheter-related complication rates was significantly lower in the experimental group (25.0%) compared to the control group (66.7%) (χ2 = 14.528, P 0.05). Conclusions Selecting the upper arm as the insertion site for long PIVCs reduced the incidence of thrombophlebitis and extended indwelling catheter duration during antimicrobial therapy. Trial registration ClinicalTrials.gov identifier: NCT06455228 (Initial Release: 05/30/2024).

Abstract Background Liver cancer is among the most prevalent cancers worldwide and is the second leading cause of cancer-related death. Epidemiological evidence suggests a potential correlation between dietary habits and the incidence of liver cancer. However, establishing a definitive causal relationship remains uncertain. Mendelian randomization (MR) is frequently employed to investigate the causal link between exposure and results. Aim This research focuses primarily on exploring and confirming whether there is a causal connection between dietary choices and the risk of liver cancer. Methods Exposure data, encompassing various dietary habits such as the consumption of dried and fresh fruits, both cooked and raw vegetables, types of fish (oily and nonoily), and beverages such as tea and coffee, as well as different meats (poultry, beef, pork, and processed), were obtained from the UK Biobank. Conversely, outcome data were derived from the FinnGen study. Inverse variance weighting (IVW) was predominantly employed to assess the causal relationship. To ensure the validity of our findings, rigorous tests for heterogeneity and horizontal pleiotropy were conducted. Results Our MR study findings revealed a significant association, indicating that genetically influenced oily fish intake is linked to a lower risk of liver cancer (OR = 0.160, 95% CI 0.026–0.968; P = 0.046). However, no substantial causal connections between liver cancer and the intake of other dietary habits were observed. Importantly, our two-sample MR investigations indicated no considerable pleiotropy effects in the instrumental variables (IVs). Conclusion In summary, our findings suggest a potential protective effect of oily fish intake against liver cancer, emphasizing the need for further studies to validate these results.

Abstract Background Since the emergence of SARS-CoV-2, the causative agent of COVID-19, the global health landscape has confronted an unprecedented and formidable challenge. The SARS-CoV-2 receptor-binding domain (RBD) is a key antigen in vaccine design. However, its low immunogenicity has been a hurdle, resulting in the production of minimal anti-RBD antibodies even when combined with alum adjuvant. Outer membrane vesicles (OMVs), secreted by Gram-negative bacteria, are nanospherical structures that can display or deliver antigens while also providing adjuvant activity through pathogen-associated molecular patterns (PAMPs). Results In this study, we utilized the SpyTag (ST)/SpyCatcher (SC) bioconjugation system to couple OMV and SARS-CoV-2 RBD in vitro. We successfully prepared a ‘plug-and-display’ nanovaccine OMV-RBD, which demonstrated good safety profiles and promoted the uptake of antigens by DCs and the maturation of BMDCs by activating TLR3 and NOD2 signaling pathways. Both intranasal and intramuscular immunization with OMV-RBD vaccine elicited robust antigen-specific humoral and cellular immune responses. Importantly, the induced antibodies effectively inhibited the binding of RBD to human angiotensin-converting enzyme 2 (hACE2) and neutralized SARS-CoV-2 pseudoviruses. Conclusions This vaccine platform offers an alternative strategy for developing recombinant subunit vaccines against SARS-CoV-2, potentially enhancing immune responses and improving vaccine efficacy. Graphical abstract

Abstract Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. The 5-methylcytosine (m5C) RNA methyltransferase NSUN2 is involved in cell proliferation and metastasis and is upregulated in a variety of cancers. However, the biological function and regulatory mechanism of NSUN2-mediated m5C modification have not been well studied in HCC. Our results showed that NSUN2 is upregulated and associated with poor prognosis in HCC patients after hepatectomy. NSUN2 overexpression significantly promoted HCC growth and metastasis, whereas NSUN2 knockdown had the opposite effect. m5C RNA immunoprecipitation sequencing (m5C-RIP-Seq) revealed that m5C hypermethylation correlates with mRNA overexpression and that NSUN2-mediated m5C hypermethylation promotes metabolism in HCC patients. Mechanistically, our data revealed that PKM2, a terminal enzyme in the glycolytic pathway, is a downstream target of NSUN2-mediated m5C modification. Specifically, NSUN2 could stabilize PKM2 mRNA by increasing the m5C level of the m5C site C773 in the 3′-UTR of PKM2 mRNA. In addition, rescue assays revealed that NSUN2 promotes HCC glycolysis and progression by upregulating PKM2. In conclusion, this study revealed that NSUN2-mediated m5C modification promotes glycolysis and the progression of hepatocellular carcinoma by stabilizing PKM2 mRNA, and provides a potential prognostic factor and therapeutic target for HCC patients.

Objective The deformations and rupture of rocks under loading will cause potential changes in parameters. Dynamic parameter capture assists in characterizing the generation, propagation, and closure processes of fractures, serving as a significant method for assessing rock quality. Methods Using a multiparameter test system, this study synchronously acquired strain measured using distributed optic fibers, electrode current, and compressional wave (P-wave) velocities of rock specimens under uniaxial loading. Accordingly, this study determined strength vs. parameter characteristic relationship graphs and parametric tomography results, finely describing the multiparameter spatiotemporal evolutionary characteristics of three typical rocks (i.e., sandstone, limestone, and mudstone) throughout the loading process. Results and Conclusions The test results indicate that the time vs. pressure curves were highly consistent with the multiparameter response curves. For the rock specimens, the strain measured using spirally distributed optic fibers exhibited a slow, stable growth in the compression and linear elasticity stages of primary pores but a sudden, rapid growth in the fracture generation and propagation stages. During the tests, the strain measured using distributed optic fibers for sandstone, limestone, and mudstone under critical fracturing were 933×10−6, 401×10−6, and 3790×10−6, respectively. The electrode current changed minimally in the compression and linear elasticity stages of primary pores, decreased significantly in the fracture generation and propagation stages, and rebounded during fracture closure. In the compression, linear elasticity, and failure stages of primary pores, the P-wave velocities of the sandstone specimen were 4.31 km/s, 4.39 km/s, and 1.26 km/s, respectively; those of the limestone specimen were 4.80 km/s, 4.93 km/s, and 3.10 km/s, respectively, and those of the mudstone specimen were 3.65 km/s, 3.57 km/s, and 1.71 km/s, respectively. Based on the energy values of the rock specimens throughout the loading process, this study constructed damage variable D to assess the degrees of damage evolution of the rock specimens. Specifically, the D values of the sandstone specimen experienced gradual increase, decrease, and sudden increase stages; those of the limestone specimen underwent slow increase, rapid increase, stagnation, and sudden increase stages, and those of the mudstone specimen experienced slow increase, rapid increase, and sudden increase stages. This study explored the failure modes of different rock specimens based on the test results of the strain measured using distributed optic fibers. The results of this study will assist in predicting the generation and propagation of secondary fractures, as well as the positions of potential rupture planes, under loading.

Abstract The aim of this research was to conduct randomized trials assessing the extent of cement diffusion following robot-assisted percutaneous vertebroplasty (R-PVP) for osteoporotic vertebral compression fractures (OVCF). A total of 96 OVCF patients meeting the inclusion criteria and admitted between January 2023 and November 2023 were included in the study. Among them, 48 patients were assigned to the robotic-assisted PVP group (R-PVP group) and 48 patients were assigned to the traditional PVP group (PVP group). The study examined the differences in age, sex, BMD T-value, fracture segment, preoperative, postoperative, and 3-month postoperative visual analogue scale (VAS) and Oswestry disability index (ODI) pain scores, fluoroscopic dose, frequency of fluoroscopy, volume of bone cement injected, angle of puncture abduction, degree of cement diffusion, and bone cement spillage among the two patient groups. A logistic regression model was employed to analyze the factors influencing the extent of postoperative bone cement diffusion. The findings indicated that the R-PVP group exhibited a significantly larger puncture abduction angle, improved postoperative cement dispersion, increased cement injection volume, and decreased incidence of cement spillage compared to the PVP group. Furthermore, the R-PVP group demonstrated superior outcomes in these aspects, as well as lower intraoperative fluoroscopic frequency and radiation exposure. Additionally, bone density, puncture abduction angle, cement injection volume, and surgical approach were identified as independent factors associated with the extent of postoperative cement dispersion.

Abstract Nowadays, chemotherapy and immunotherapy remain the major treatment strategies for Triple-Negative Breast Cancer (TNBC). Identifying biomarkers to pre-select and subclassify TNBC patients with distinct chemotherapy responses is essential. In the current study, we performed an unbiased Reverse Phase Protein Array (RPPA) on TNBC cells treated with chemotherapy compounds and found a leading significant increase of phosphor-AURKA/B/C, AURKA, AURKB, and PLK1, which fall into the mitotic kinase group. The increase of AURKA and AURKB protein was majorly due to a post-transcription level regulation, and Paclitaxel treatment induced Aurora Kinases protein phosphorylation on AURKA(T288)/AURKB(T232) sites and their protein stability. In our UAB TNBC cohort, the expression of AURKA and AURKB was significantly higher in TNBC tumors compared to normal adjacent tissues, and AURKB was found to be highly expressed in African American TNBC patients compared to European Americans. Moreover, Aurora Kinases overexpression in TNBC cells renders resistance to Paclitaxel treatment and attenuates the apoptosis effect triggered by chemotherapy treatment, suggesting Aurora Kinases could mediate the chemo-resistance in TNBC. Hence, a combination of Aurora kinase inhibitors or PROTAC degrader and taxane-type chemotherapy significantly enhanced the chemotherapy effect. In summary, we revealed that Aurora Kinases upregulation after treatment with chemotherapy could confer chemotherapy resistance to TNBC cells, and AURKB could serve as preselection markers for stratifying patients’ response to neoadjuvant chemotherapy.

Abstract Although the triglyceride-glucose (TyG) index has been established as a valuable predictor for cardiovascular disease (CVD) and cardiovascular mortality, there is limited research exploring its association with all-cause or CVD mortality specifically in adults with diabetes aged

Abstract Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder affecting women of childbearing age, and we aimed to reveal its underlying molecular mechanisms. Gene expression profiles from GSE138518 and GSE155489, and single-cell RNA sequencing (scRNA-seq) data from PRJNA600740 were collected and subjected to bioinformatics analysis to identify the complex molecular mechanisms of PCOS. The expression of genes was detected by RT-qPCR. Through differential analysis, we identified 230 common differentially expressed genes (DEGs) in GSE138518 and GSE155489. GSEA results showed significant enrichment of purine metabolism and oocyte meiosis in the control group, while GSVA results indicated significant activation of ECM receptor interaction, and antigen processing and presentation in PCOS. Weighted gene co-expression network analysis revealed 7 co-expression modules, with the bisque4 module showing the highest positive correlation with PCOS. Enrichment analysis revealed that genes in the bisque4 module were mainly involved in the PI3K-Akt signaling pathway, calcium signaling pathway, and Ras signaling pathway. Pseudotime trajectory analysis of cell subpopulations revealed the potential developmental trajectory of PCOS. The gene expression consistent with the potential developmental trajectory was validated by RT-qPCR. Our study, by analyzing multiple datasets, has revealed the complex molecular network of PCOS, offering new insights into understanding its pathophysiological basis.

Abstract Proteins that bind to DNA/RNA are typically evolutionarily conserved with multiple regulatory functions in transcription initiation, mRNA translation, stability of RNAs, and RNA splicing. Therefore, dysregulation of DNA/RNA binding proteins such as purine-rich element binding protein alpha (PURα) disrupts signaling transduction and often leads to human diseases including cancer. PURα was initially recognized as a tumor suppressor in acute myeloid leukemia (AML) and prostate cancer (PC). Most recently, several studies have revealed that PURα is dysregulated in multiple cancers, such as breast cancer (BC) and esophageal squamous cell carcinoma (ESCC). The oncogenic or tumor-suppressive functions of PURα are realized via regulating RNA/protein interaction, mRNA translation, formation of stress granules (SGs), and transcriptional regulation of several oncogenes and tumor suppressors. Although DNA/RNA binding proteins are hardly targeted, novel strategies have been applied to identify compounds targeting PURα and have demonstrated promising anti-tumor efficacy in the preclinical study. The present review summarizes the most recently discovered critical roles of PURα in various cancer types, providing an overview of the biomarker and therapeutic target potential of PURα for patients with cancer.

Abstract The chiral edge current is the boundary manifestation of the Chern number of a quantum anomalous Hall (QAH) insulator. The van der Waals antiferromagnet MnBi2Te4 is theorized to be a QAH in odd-layers but has shown Hall resistivity below the quantization value at zero magnetic field. Here, we perform scanning superconducting quantum interference device (sSQUID) microscopy on these seemingly failed QAH insulators to image their current distribution. When gated to the charge neutral point, our device exhibits edge current, which flows unidirectionally on the odd-layer boundary both with vacuum and with the even-layers. The edge current chirality reverses with the magnetization of the bulk. Surprisingly, we find the edge channels coexist with finite bulk conduction even though the bulk chemical potential is in the band gap, suggesting their robustness under significant edge–bulk scattering. Our result establishes the existence of chiral edge currents in a topological antiferromagnet and offers an alternative for identifying QAH states.

The Patented Naoxueshuan formula is an empirical formula for treating cerebral thrombosis, which has been proven to have significant and stable therapeutic effects through long-term clinical application. The Naoxueshuan formula has rich chemical components and diverse structures. In this study, chemical compositions of the Patent Naoxueshuan formula were analyzed by using ultra-performance liquid chromatography-time of flight mass spectrometry (UPLC-Q-TOF MS) and gas chromatography-mass spectrometry (GC-MS). For UPLC-Q-TOF MS analysis, the decoction of Naoxueshuan formula was separated using a Waters BEH C18 column (100 mm×2.1 mm, 1.7 μm). The mobile phase was comprised of 0.1% formic acid solution and acetonitrile with the flow rate of 0.3 mL/min. MS data was collected under positive and negative ion modes. For GC-MS analysis, the Agilent DB-5MS capillary column (30 m×0.25 mm, 0.25 μm) was employed to analyze the volatile components of the decoction of Naoxueshuan formula. The GC-MS analysis was performed under programmed heating conditions with electron ionization (EI) as the ion source and a scanning mass range of m/z 50-550. The main chromatographic peaks in both liquid and gas chromatograms were identified and analyzed according to the secondary mass spectrum information, NIST standard spectrum library and literatures. A total of 61 non-volatile components are identified in the Naoxueshuan decoction, including 14 flavonoids, 13 terpenoids, 9 glycosides, 5 organic acids, and 10 other types of compounds. A total of 29 volatile components are identified in the Naoxueshuan decoction, including 17 hydrocarbons, 3 alcohols, 1 aldehydes, 1 esters, 3 phenols, 2 terpenes and 2 other types of compounds. Among them, the organic acids are mainly from Salvia miltiorrhiza Bunge, the flavonoids are mainly from Pueraria lobata, Astragalus membranaceus (Fisch.) Bunge and Carthamus tinctorius L., the terpenoids are mainly from Salvia miltiorrhiza Bunge and Cornus officinalis Sieb. et Zucc. The volatile components are mainly from Ligusticum sinense, Fructus Amomi, Alpinia katsumadai Hayata, and Semen Alpiniae Katsumadai. This study provides an effective and comprehensive method for qualitative analysis of the chemical components in the Patented Naoxueshuan formula, and also provides data support for clarifying effective substances and establishing a quality evaluation system.

Abstract Diseases and injuries can cause significant bone loss, leading to increased medical expenses, decreased work efficiency, and a decline in quality of life. Bone tissue engineering (BTE) is gaining attention as an alternative to autologous and allogeneic transplantation due to the limited availability of donors. Biomaterials represent a promising strategy for bone regeneration, and their design should consider the three key processes in bone tissue engineering: osteogenesis, bone conduction, and bone induction. Certain bile acids (BAs) demonstrate significant antioxidant, anti-inflammatory, and immunosuppressive properties, and effectively promote bone and tissue regeneration. Additionally, the combination of BA molecule with other biological materials can help overcome problems associated with limited local bone regeneration and maintain a defined release state for a long time. Thus in this review, we focus on the role and the mechanism of bile acids in bone healing under different conditions, highlighting their unique properties and applications in gel fabrication, microencapsulation, and nanotechnology. These advancements serve as a basis for the advancement of biomaterials derived from BAs, specifically for the purpose of bone reconstruction. Graphical Abstract

Abstract The polymorphic microbiome is considered a new hallmark of cancer. Advances in High-Throughput Sequencing have fostered rapid developments in microbiome research. The interaction between cancer cells, immune cells, and microbiota is defined as the immuno-oncology microbiome (IOM) axis. Fungal microbes (the mycobiome), although representing only ∼ 0.1-1% of the microbiome, are a critical immunologically active component of the tumor microbiome. Accumulating evidence suggests a possible involvement of commensal and pathogenic fungi in cancer initiation, progression, and treatment responsiveness. The tumor-associated mycobiome mainly consists of the gut mycobiome, the oral mycobiome, and the intratumoral mycobiome. However, the role of fungi in cancer remains poorly understood, and the diversity and complexity of analytical methods make it challenging to access this field. This review aims to elucidate the causal and complicit roles of mycobiome in cancer development and progression while highlighting the issues that need to be addressed in executing such research. We systematically summarize the advantages and limitations of current fungal detection and analysis methods. We enumerate and integrate these recent findings into our current understanding of the tumor mycobiome, accompanied by the prospect of novel and exhilarating clinical implications.

Abstract Objectives Metrics and instruments can provide guidance for clinical researchers to assess their potential research projects at an early stage before significant investment. Furthermore, metrics can also provide structured criteria for peer reviewers to assess others’ clinical research manuscripts or grant proposals. This study aimed to develop, test, validate, and use evaluation metrics and instruments to accurately, consistently, systematically, and conveniently assess the quality of scientific hypotheses for clinical research projects. Materials and methods Metrics development went through iterative stages, including literature review, metrics and instrument development, internal and external testing and validation, and continuous revisions in each stage based on feedback. Furthermore, two experiments were conducted to determine brief and comprehensive versions of the instrument. Results The brief version of the instrument contained three dimensions: validity, significance, and feasibility. The comprehensive version of metrics included novelty, clinical relevance, potential benefits and risks, ethicality, testability, clarity, interestingness, and the three dimensions of the brief version. Each evaluation dimension included 2 to 5 subitems to evaluate the specific aspects of each dimension. For example, validity included clinical validity and scientific validity. The brief and comprehensive versions of the instruments included 12 and 39 subitems, respectively. Each subitem used a 5-point Likert scale. Conclusion The validated brief and comprehensive versions of metrics can provide standardized, consistent, systematic, and generic measurements for clinical research hypotheses, allow clinical researchers to prioritize their research ideas systematically, objectively, and consistently, and can be used as a tool for quality assessment during the peer review process.

Abstract Background Physical activity (PA) interventions have been shown to yield positive effects on cognitive functions. However, it is unclear which type of PA intervention is the most effective in children and adolescents with Neurodevelopmental Disorders (NDDs). This study aimed to compare the effectiveness of different types of PA interventions on cognitive functions in children and adolescents with NDDs, with additional analyses examining intervention effects across specific NDD types including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Methods In this systematic review and network meta-analysis, seven databases (Web of Science, PubMed, Medline, APA PsycINFO, Embase, CINAHL, and SPORTDiscus) for randomized controlled trials from database inception to September 2023 were searched. Randomized controlled trials comparing the effectiveness of PA intervention with any non-pharmacological treatment or control group on cognitive functions in children and adolescents diagnosed with NDDs aged 5–17 years were included. Frequentist network meta-analyses were performed based on standardized mean differences (SMD) using random effects models to examine post-intervention differences in cognitive functions, including attention, memory, and executive functions. Intervention dropout was assessed as a measure of treatment acceptability. Results Thirty-one randomized controlled trials (n = 1,403, mean age 10.0 ± 1.9 years) with 66 arms were included in the network. Mind-body exercise (MBE; SMD = 1.91 for attention; 0.92 for executive functions), exergaming (SMD = 1.58 for attention; 0.97 for memory; 0.94 for executive functions), and multi-component physical activity (MPA; SMD = 0.79 for executive functions) were associated with moderate to substantial cognitive improvements compared with usual care, whereas the effectiveness of aerobic exercise (AE) was non-significant. Exergaming (SMD = 0.78, 95%CI 0.12 to 1.45) and MPA (SMD = 0.64, 95%CI 0.11 to 1.18) were more effective than AE for executive functions. When analyzing specific NDD types, exergaming lost its superiority over usual care for attention and memory in ADHD, nor for executive functions in ASD. Instead, MPA demonstrated significant benefits across these domains and populations. The certainty of evidence for these comparisons was very low to low. No significant differences in acceptability were observed among MBE, exergaming, and MPA. Conclusions The findings in this study suggest that MBE, exergaming, and MPA were effective interventions for improving domain-specific cognitive functions in children and adolescents with NDDs. AE demonstrated non-significant effectiveness for all outcomes. MBE emerges as particularly advantageous for attention. MPA yielded consistent improvements in memory and executive functions across NDD types. Further high-quality randomized controlled trials of direct comparisons are needed to confirm and expand on the findings from this NMA. Trial registration PROSPERO CRD42023409606.

This paper presents a systematic overview of the resilience framework for power electronics converter-based cyber-physical systems (CPSs), emphasizing end-to-end responses to the emerging challenges posed by cyber-physical attacks. While recent advancements in control and communication have enhanced the functionalities of power electronic converters in applications such as electric vehicles and smart grids, such advancements have also introduced new vulnerabilities, particularly to cyber-physical attacks. The existing literature tends to focus on isolated research areas, and a comprehensive review that encompasses strategies applicable before, during, and after an attack remains lacking. To address this gap, this paper categorizes state-of-the-art research into four key stages of an attack: anticipate and prepare, resist and absorb, detect and evaluate, and recover. Topics reviewed in this paper include converter and cyber-physical attack modeling, converter-based CPS testbeds, system hardening at the cyber and physical layers, attack detection, post-attack evaluation, and recovery strategies. Real-world case studies and practical regulations are also analyzed. Additionally, challenges and opportunities of the resilience framework are discussed. Despite notable advancements in modeling and identifying cyber-physical attacks, considerable efforts are still required to improve attack mitigation strategies and recovery mechanisms.

Abstract Metabolic reprogramming fuels cancer cell metastasis and remodels the immunosuppressive tumor microenvironment (TME). We report here that circPETH, a circular RNA (circRNA) transported via extracellular vesicles (EVs) from tumor-associated macrophages (TAMs) to hepatocellular carcinoma (HCC) cells, facilitates glycolysis and metastasis in recipient HCC cells. Mechanistically, circPETH-147aa, encoded by circPETH in an m6A-driven manner, promotes PKM2-catalyzed ALDOA-S36 phosphorylation via the MEG pocket. Furthermore, circPETH-147aa impairs anti-HCC immunity by increasing HuR-dependent SLC43A2 mRNA stability and driving methionine and leucine deficiency in cytotoxic CD8+ T cells. Importantly, through virtual and experimental screening, we find that a small molecule, Norathyriol, is an effective inhibitor that targets the MEG pocket on the circPETH-147aa surface. Norathyriol reverses circPETH-147aa-facilitated acquisition of metabolic and metastatic phenotypes by HCC cells, increases anti-PD1 efficacy, and enhances cytotoxic CD8+ T-cell function. Here we show that Norathyriol is a promising anti-HCC agent that contributes to attenuating the resistance of advanced HCC to immune checkpoint blocker (ICB) therapies.

Abstract Key functions of antibodies, such as viral neutralisation, depend on high-affinity binding. However, viral neutralisation poorly correlates with antigen affinity for reasons that have been unclear. Here, we use a new mechanistic model of bivalent binding to study >45 patient-isolated IgG1 antibodies interacting with SARS-CoV-2 RBD surfaces. The model provides the standard monovalent affinity/kinetics and new bivalent parameters, including the molecular reach: the maximum antigen separation enabling bivalent binding. We find large variations in these parameters across antibodies, including reach variations (22–46 nm) that exceed the physical antibody size (~15 nm). By using antigens of different physical sizes, we show that these large molecular reaches are the result of both the antibody and antigen sizes. Although viral neutralisation correlates poorly with affinity, a striking correlation is observed with molecular reach. Indeed, the molecular reach explains differences in neutralisation for antibodies binding with the same affinity to the same RBD-epitope. Thus, antibodies within an isotype class binding the same antigen can display differences in molecular reach, substantially modulating their binding and functional properties.

Abstract The recently emerged remote epitaxy technique, utilizing 2D materials (mostly graphene) as interlayers between the epilayer and the substrate, enables the exfoliation of crystalline nanomembranes from the substrate, expanding the range of potential device applications. However, remote epitaxy has been so far applied to a limited range of material systems, owing to the need of stringent growth conditions to avoid graphene damaging, and has therefore remained challenging for the synthesis of oxide nanomembranes. Here, we demonstrate the remote epitaxial growth of an oxide nanomembrane (vanadium dioxide, VO2) with a sub-nanometer thick amorphous interlayer, which can withstand potential sputtering-induced damage and oxidation. By removing the amorphous interlayer, a 4-inch wafer-scale freestanding VO2 nanomembrane can be obtained, exhibiting intact crystalline structure and physical properties. In addition, multi-shaped freestanding infrared bolometers are fabricated based on the epitaxial VO2 nanomembranes, showing high detectivity and low current noise. Our strategy provides a promising way to explore various freestanding heteroepitaxial oxide materials for future large-scale integrated circuits and functional devices.

Abstract Vibrio vulnificus is a significant zoonotic pathogen that causes severe vibriosis in humans and fish. The lack of a national annual surveillance program in China has hindered understanding of its epidemiological characteristics and genetic diversity. This study characterized 150 V. vulnificus isolates collected from diverse sources in China during 2012–2023, including seafood, aquaculture water, migratory birds, marine animals, and clinical patients. Most seafood-derived isolates and all 15 clinical isolates harbored the virulence-related gene vcgC and 16S rRNA type B. The isolates exhibited diverse virulence factors (VFs), including flagella, outer membrane components, RTX toxins, and multiple secretion systems. Genes associated with the Type III secretion system were identified in migratory bird isolates, while a unique Type VI secretion system (T6SS1) were identified exclusively within a specific phylogenetic sub-lineage. T6SS1-positive strains demonstrated an increased number of genomic islands (GIs) and VFs compared to T6SS1-negative strains. Enrichment of genes related to secretion systems and biofilm formation likely facilitated the expansion of the T6SS1-positive population. The novel association between T6SS1 and a specific sub-lineage underscores potential ecological and adaptive advantages. These findings provide new insights into the ecological and evolutionary dynamics of V. vulnificus.

Abstract Background Acute Kidney Injury (AKI) is a sudden and often reversible condition characterized by rapid kidney function reduction, posing significant risks to coronary artery disease (CAD) patients. This study focuses on developing accurate predictive models to improve the early detection and prognosis of AKI in CAD patients. Methods We used Electronic Health Records (EHRs) from a nationwide CAD registry including 54 429 patients. Initially, univariate analysis identified potential predictors. Subsequently, a stepwise multivariate logistic model integrated clinical significance and data distribution. To refine predictor selection, we applied a random forest algorithm. The top 10 variables, including admission to the surgical department, EGFR, hemoglobin, and others, were incorporated into a logistic regression-based prediction model. Model performance was assessed using the area under the curve (AUC) and calibration analysis, and a nomogram was developed for practical application. Results During hospitalization, 2,112 (3.88%) patients in the overall population of both the development and validation groups experienced AKI within 30 days. The final prediction model exhibited strong discrimination with an AUC of 0.867 (95% CI: 0.858 to 0.876) and well calibration capability in both the development and validation groups. Key predictors included surgical department admission, eGFR, hemoglobin, chronic kidney disease history, male sex, white blood cell count, age, left ventricular ejection fraction, acute myocardial infarction at admission, and congestive heart failure history. Bootstrap resampling confirmed model stability (Harrell's optimism-correct AUC = 0.866). The nomogram provided a practical tool for AKI risk assessment. Conclusion This study introduced a refined AKI risk prediction model for CAD patients. This model showed adaptability to subgroups and held the potential for early AKI alerts and personalized interventions, thereby enhancing patient care.