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Objective To identify the characteristics of nutritional problems in patients with Parkinsonism who participated in multi-disciplinary team (MDT) and to investigate the correlation between nutritional status and dysphagia in these patients. The predictive value of video fluoroscopic swallowing study (VFSS) and EAT-10 scale for malnutrition was compared. Methods Subjects were patients with Parkinsonism participated in joint MDT consultation project in Peking Union Medical College Hospital from November 2020 to January 2023. Subjective and objective dysphagia were evaluated by EAT-10 scale score and VFSS dysphagia score. Nutritional status of the patients was evaluated by geriatric nutrition risk index (GNRI), albumin, prealbumin, serum folic acid, vitamin B12 and temporal muscle thickness. Results A total of 30 participants met the criteria and were included in the study. The age was 45-82 (66.1±9.0) years old. Six (20%) were at risk of malnutrition shown b a comprehensive nutritional status assessment using GNRI. The areas under receiver operating characteristic(ROC) curves(AUC) of VFSS dysphagia score and EAT-10 score to predict malnutrition were 0.781 (0.568-0.995) and 0.927 (0.827-1.000), respectively. EAT-10 score was correlated with GNRI(r=-0.524, P＜0.01), BMI(r=-0.618, P＜0.001), prealbumin (r=-0.616, P＜0.001). The VFSS dysphagia score was only correlated with BMI (r=-0.446, P＜0.05) and prealbumin(r=-0.387, P＜0.05). Conclusions Patients with Parkinsonism requiring MDT often have multiple micronutrient imbalance. Patients′ subjective perception of dysphagia has a greater impact on their nutritional status than objective assessment of dysphagia.

Abstract Currently, surgical resection remains the primary approach for treating oral squamous cell carcinoma (OSCC), with limited options for effective drug therapy. Cardamonin, a principal compound derived from Myristica fragrans of the Zingiberaceae family, has garnered attention for its potential to suppress the onset and progression of various malignancies encompassing breast cancer, hepatocellular carcinoma, and ovarian cancers. Nevertheless, the involvement of cardamonin in the treatment of OSCC and its underlying mechanisms are yet to be elucidated. This research explored the possible target of cardamonin in treating OSCC via network pharmacological analysis. Subsequently, this research investigated the impact of cardamonin on OSCC cells via in vitro experiments, revealing its capacity to impede the migration, proliferation, and invasion of OSCC cells. Additionally, western blotting analysis demonstrated that cardamonin facilitates apoptosis by regulating the PI3K/AKT pathway. The findings suggest that MMP9 and the PI3K/AKT signaling pathway may serve as the target and pathway of cardamonin in treating OSCC. To summarize, the research findings suggest that cardamonin may facilitate apoptosis in OSCC cells by inhibition of PI3K/AKT pathway activation. These outcomes offer a theoretical basis for the utilization of cardamonin as a natural drug for treating OSCC.

Abstract Background Nasopharyngeal carcinoma (NPC) is diagnosed relatively late and has a poor prognosis, requiring early detection to reduce the disease burden. This diagnostic test accuracy meta-analysis evaluated the serological diagnostic value of nine EBV-related IgA antibody panels (EBNA1-IgA, VCA-IgA, EA-IgA, Zta-IgA, EBNA1-IgA + VCA-IgA, VCA-IgA + EA-IgA, VCA-IgA + Rta-IgG, EBNA1-IgA + VCA-IgA + Zta-IgA and VCA-IgA + EA-IgA + Rta-IgG), aiming to identify suitable serological detection biomarkers for NPC screening. Methods PubMed, Embase, China National Knowledge Infrastructure and Chinese BioMedical Literature Database were searched from January 1st, 2000 to September 30th, 2023, with keywords nasopharyngeal carcinoma, IgA, screening, early detection, early diagnosis, sensitivity and specificity. Articles on the diagnostic value of serum EBV-related IgA antibody panels for NPC were included. Study selection, data extraction, and quality assessment were performed independently by two researchers, and a third researcher was consulted in the case of disagreement. Bivariate models were used for statistical analysis. The quality of included studies was evaluated through Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2). Results A total of 70 articles were included, involving 11 863 NPC cases and 34 995 controls. Among the nine EBV-related IgA antibody panels, EBNA1-IgA + VCA-IgA [0.928 (0.898, 0.950)], VCA-IgA + Rta-IgG [0.925 (0.890, 0.949)], EBNA1-IgA + VCA-IgA + Zta-IgA [0.962 (0.909, 0.985)] and VCA-IgA + EA-IgA + Rta-IgG [0.945 (0.918, 0.964)] demonstrated higher pooled sensitivity (95%CI). In terms of diagnostic odds ratio (DOR) (95%CI), EBNA1-IgA + VCA-IgA [107.647 (61.173, 189.430)], VCA-IgA + Rta-IgG [105.988 (60.118, 186.857)] and EBNA1-IgA + VCA-IgA + Zta-IgA [344.450 (136.351, 870.153)] showed superior performance. Additionally, the SROC curves for EBNA1-IgA + VCA-IgA and VCA-IgA + Rta-IgG were more favorable. However, publication bias was detected for VCA-IgA (P = 0.005) and EBNA1-IgA + VCA-IgA (P = 0.042). Conclusions In general, parallel detection of serum EBNA1-IgA, VCA-IgA and Zta-IgA antibodies using ELISA demonstrates better pooled sensitivity and DOR among the studied panels. In the cases where fewer indicators are used, serum VCA-IgA and EBNA1-IgA/Rta-IgG antibody panel exhibits a comparable performance. Trial registration The International Prospective Register of Systematic Reviews registration number: CRD42023426984, registered on May 28, 2023.

Olfaction, the sense of smell, is crucial for animal survival, especially in localizing prey or food. However, little is known about the fish behavioral responses to specific food odors and which olfactory receptor might be activated by the food odors. Here, we examined the evolutionary relationships and classified the subfamilies of olfactory receptors (ORs), and conducted behavioral and gene expression analysis in grass carp (Ctenopharyngodon idellus). We identified 196 intact ORs in the grass carp genome and classified them into 8 subfamilies: β, δ, ε, η, γ, κ, θ, and ζ. 12 representative ORs (4 β, 4 δ, and 4 ε) were highly expressed in the olfactory epithelium (OE) of 24-month-old grass carp. Behavioral exploration found that grass carp showed different behaviors to different food odors at a series of concentrations. Specifically, 0.01 μmol/L amino acid mixtures and 0.005 × Hydrilla verticillata extracts strongly changed the preference index and swimming trajectories in 6-month-old grass carp. In addition, the two food odors stimulation differentially induced ORs expression in three tissues, especially strong in the olfactory bulb and brain. Altogether, our results suggest that olfaction plays an important role in the regulation of fish feeding behavior and provide a basis for further studies on the function and specific recognition of olfactory receptors in fish.

Nano zero-valent iron (nZVI) and sulfidation-modified nZVI (S-nZVI) were synthesized and used to remove hexavalent chromium (Cr(VI)) in wastewater. Characterization of the products showed that the sulfidation process significantly changed the morphology of nZVI, with enhanced crystallinity. The effects of S/Fe ratio, pH value, and reaction temperature on Cr(VI) removal were studied. A S/Fe ratio of 0.5 was the most appropriate parameter, with a removal efficiency of 98% in the condition of pH = 2. The effects of anions (Cl−, NO3−, CO32−, and SO42−) and cations (Ca2+ and Mg2+) on the Cr(VI) removal efficiency were investigated, and the relevant mechanisms were discussed. The Cr(VI) removal efficiency of S-nZVI was significantly greater than that of nZVI, mainly owing to the existence of FeS layers that could protect Fe0 cores and prompt electron transfer. The aging and cycling experiments showed that S-nZVI could maintain its reactivity when facing the corrosion of water, and showed cycling stability. Thus, S-nZVI is an effective and feasible agent for the remediation of Cr(VI)-contained wastewater.

Abstract This study introduces a novel self-supervised learning method for single-frame subtraction and vessel segmentation in coronary angiography, addressing the scarcity of annotated medical samples in AI applications. We pretrain a U-Net model on a large dataset of unannotated coronary angiograms using an image-to-image translation framework, then fine-tune it on a limited set of manually annotated samples. The pretrained model excels at comprehensive single-frame subtraction, outperforming existing DSA methods. Fine-tuning with just 40 samples yields a Dice coefficient of 0.828 for vessel segmentation. On the public XCAD dataset, our model sets a new state-of-the-art benchmark with a Dice coefficient of 0.755, surpassing both unsupervised and supervised learning approaches. This method achieves robust single-frame subtraction and demonstrates that combining pretraining with minimal fine-tuning enables accurate coronary vessel segmentation with limited manual annotations. We successfully apply this approach to assist physicians in visualizing potential vascular stenosis sites during coronary angiography. Code, dataset, and a live demo will be available available at: https://github.com/newfyu/DeepSA .

Abstract Renal cell carcinoma (RCC) is one of the most common tumors that afflicts the urinary system, accounting for 90–95% of kidney cancer cases. Although its incidence has increased over the past decades, its pathogenesis is still unclear. Tumor-associated macrophages (TAMs) are the most prominent immune cells in the tumor microenvironment (TME), comprising more than 50% of the tumor volume. By interacting with cancer cells, TAMs can be polarized into two distinct phenotypes, M1-type and M2-type TAMs. In the TME, M2-type TAMs, which are known to promote tumorigenesis, are more abundant than M1-type TAMs, which are known to suppress tumor growth. This ratio of M1 to M2 TAMs can create an immunosuppressive environment that contributes to tumor cell progression and survival. This review focused on the role of TAMs in RCC, including their polarization, impacts on tumor proliferation, angiogenesis, invasion, migration, drug resistance, and immunosuppression. In addition, we discussed the potential of targeting TAMs for clinical therapy in RCC. A deeper understanding of the molecular biology of TAMs is essential for exploring innovative therapeutic strategies for the treatment of RCC.

Abstract The primary aim of this investigation was to leverage radiomics features derived from contrast-enhanced abdominal computed tomography (CT) scans to devise a predictive model to discern the benign and malignant nature of intraductal papillary mucinous neoplasms (IPMNs). Radiomic signatures were meticulously crafted to delineate benign from malignant IPMNs by extracting pertinent features from contrast-enhanced CT images within a designated training cohort (n = 84). Subsequent validation was conducted with data from an independent test cohort (n = 37). The discriminative ability of the model was quantitatively evaluated through receiver operating characteristic (ROC) curve analysis, with the integration of carefully selected clinical features to improve the comparative analysis. Arterial-phase images were utilized to construct a model comprising 8 features for distinguishing between benign and malignant cases. The model achieved an accuracy of 0.891 [95% confidence interval (95% CI), 0.816–0.996] in the cross-validation set and 0.553 (95% CI 0.360–0.745) in the test set. Conversely, employing 9 features from the venous-phase resulted in a model with a cross-validation accuracy of 0.862 (95%CI 0.777–0.946) and a test set accuracy of 0.801 (95% CI 0.653–0.950).Integrating the identified clinical features with imaging features yielded a model with a cross-validation accuracy of 0.934 (95% CI 0.879–0.990) and a test set accuracy of 0.904 (95% CI 0.808–0.999), thereby further improving its discriminatory ability. Our findings distinctly illustrate that venous-phase radiomics features eclipse arterial-phase radiomic features in terms of predictive accuracy regarding the nature of IPMNs. Furthermore, the synthesis and meticulous screening of clinical features with radiomic data significantly increased the diagnostic efficacy of our model, underscoring the pivotal importance of a comprehensive and integrated approach for accurate risk stratification in IPMN management.

Efficient fire response and the coordination of various fire vehicles are paramount for delivering optimal services and conducting effective rescue operations. This study explores the challenges of cooperative station location and vehicle assignment, focusing on the synergistic dispatch of fire vehicles from multiple stations. It highlights that the response time of the last arriving vehicle, crucial for forming a complete and effective response unit, is a critical determinant in the overall success of fire rescue operations. The primary objective of the model is to minimize the total system cost, encompassing both the capital investment in fire stations and the potential losses from fire incidents. By employing a Lagrangian relaxation technique, the model effectively simplifies the optimization challenge into more manageable sub-problems, thereby enhancing solution accuracy. The robustness and flexibility of the model were tested through simulations in a hypothetical network and a real-world scenario, using data from urban fire services. The results demonstrate the model’s scalability and adaptability to different network configurations and operational constraints, showcasing its potential to substantially enhance emergency response efficiency and decision-making in urban fire management. This research makes a significant contribution to emergency response management by providing a validated framework that improves the coordination and effectiveness of fire rescue operations, thereby reducing fire damage and enhancing public safety.

Objective To summarize the experience of nursing care of patients with severe alopecia areata treated with topical diphenylcyclopropenone. Methods Seventeen patients with severe alopecia areata treated with topical diphenylcyclopropenone were enrolled. Before the treatment, self-protection was given to the therapist and informed consent was given to the patients. During the treatment, the principles of procedure and drug dosages were strictly followed. After the treatment, WeChat APP was used in the follow-up management of patients. This management included one-to-one evaluation of and consultation on efficacy, adverse reactions, diet and psychology. Results Seventeen patients completed the 16-week treatments, with an effective rate of 58.82%. The adverse reactions were mild and controllable. The therapists did not experience any adverse reactions such as allergic reactions. Conclusion In the treatment of severe alopecia areata with topical diphenylcyclopropenone, appropriate pre-operative preparation and post-operative care can effectively improve the patient's compliance and the therapeutic efficacy.

Abstract Fermenting Chinese medicinal herbs could enhance their bioactivities. We hypothesized probiotic-fermented gastrodia elata Blume (GE) with better potential to alleviate insomnia than that of unfermented, thus the changes in chemical composition and the insomnia-alleviating effects and mechanisms of fermented GE on pentylenetetrazole (PTZ)-induced insomnia zebrafish were explored via high-performance liquid chromatography (HPLC) and mass spectroscopy-coupled HPLC (HPLC-MS), phenotypic, transcriptomic, and metabolomics analysis. The results demonstrated that probiotic fermented GE performed better than unfermented GE in increasing the content of chemical composition, reducing the displacement, average speed, and number of apoptotic cells in zebrafish with insomnia. Metabolomic investigation showed that the anti-insomnia effect was related to regulating the pathways of actin cytoskeleton and neuroactive ligand-receptor interactions. Transcriptomic and reverse transcription qPCR (RT-qPCR) analysis revealed that secondary fermentation liquid (SFL) significantly modulated the expression levels of neurod1, msh2, msh3, recql4, ercc5, rad5lc, and rev3l, which are mainly involved in neuron differentiation and DNA repair. Collectively, as a functional food, fermented GE possessed potential for insomnia alleviation.

T cell-redirecting bispecific antibodies are specifically designed to bind to tumor-associated antigens, thereby engaging with CD3 on the T cell receptor. This linkage between tumor cells and T cells actively triggers T cell activation and initiates targeted killing of the identified tumor cells. These antibodies have emerged as one of the most promising avenues within tumor immunotherapy. However, despite success in treating hematological malignancies, significant advancements in solid tumors have yet to be explored. In this review, we aim to address the critical challenges associated with T cell-redirecting bispecific antibodies and explore novel strategies to overcome these obstacles, with the ultimate goal of expanding the application of this therapy to include solid tumors.

Abstract Background Emerging evidence indicates carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) is involved in the development of atherosclerosis (AS). However, the roles and functions of CEACAM1 in AS remain unknown. Therefore, this study aims to investigate the roles and molecular functions of CEACAM1 in AS. Methods We constructed a diabetes mellitus (DM) + high-fat diet (HFD) mouse model based on the streptozotocin (STZ)-induced apolipoprotein E-knockdown (ApopE−/−) mouse to investigate the roles and regulatory mechanism of miR-449a/CEACAM1 axis. The mRNA expression and protein levels in this study were examined using quantity PCR, western blot, immunofluorescence (IF), enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry (IHC), respectively. And the lipid deposition and collagen content were detected using Oil Red O and Sirius Red staining. Cell apoptosis, migration, invasion, and tuber formation were detected by Annexin-V FITC/PI, wound healing, transwell, and tuber formation assays, respectively. The relationship between miR-449a and CEACAM1 was determined by a dual-luciferase reporter gene assay. Results miR-449a and MMP-9 were upregulated, and CEACAM1 was downregulated in the DM + HFD MOUSE model. Upregulation of CEACAM1 promoted atherosclerotic plaque stability and inhibited inflammation in the DM + HFD mouse model. And miR-449a directly targeted CEACAM1. Besides, miR-449a interacted with CEACAM1 to regulate atherosclerotic plaque stability and inflammation in DM-associated AS mice. In vitro, the rescue experiments showed miR-449a interacted with CEACAM1 to affect apoptosis, migration, invasion, and tuber formation ability in high glucose (HG)-induced HUVECs. Conclusion These results demonstrated that miR-449a promoted plaque instability and inflammation in DM and HFD-induced mice by targeting CEACAM1.

Abstract Chimeric antigen receptors (CAR) are engineered fusion proteins that target T-cells to specific surface antigens of tumor cells to generate effective anti-tumor responses. CAR T-cell therapy is playing an increasingly important role in the treatment of relapsed/refractory B-cell malignancies (R/R BCM). Attempting to make CAR T-cells safer and more effective in treating R/R BCM, various novel engineered CAR T-cell agents are currently in the research and development or clinical trial stages. We have summarized here the latest reports on the novel CAR T-cell therapies for R/R BCM presented at the 2023 ASH Annual Meeting as well as the latest updates in related clinical trials.

Abstract Background Rwanda has aimed to rebuild its health care system since the Rwandan genocide against the Tutsis in 1994, though one of the challenges has been a scarcity of radiologic resources. Objective To assess the location and accessibility of radiologic facilities in Rwanda using geospatial mapping and population-based data. Methods A cross-sectional study was conducted in May 2023 using location and radiologic modality data provided by the Department of Radiology at the University Teaching Hospital of Kigali and the WorldPop database, a publicly available database providing open-access geospatial population data. Radiologic equipment included magnetic resonance (MR), computed tomography (CT), positron emission tomography (PET), radiotherapy, X-ray, mammography, and fluoroscopy machines. Geospatial analysis was performed using ArcGIS Pro 2.8.6 software. Results Fifty-six radiologic facilities were identified, including 5 MR, 7 CT, 1 radiotherapy, 52 X-ray, 5 mammography, 5 fluoroscopy, and 0 PET machines. There were 0.4 MR, 0.5 CT, 0 PET, 0.1 radiotherapy, 3.9 X-ray, 0.4 mammography, and 0.4 fluoroscopy units per 1 million people. Conclusion Rwanda is one of the countries with the lowest radiologic access in East Africa; however, there is evidence of progress, particularly in more advanced diagnostic imaging techniques such as computed tomography and magnetic resonance imaging. Critical relevance statement This study provides a 10-year update on current radiologic resources and access in Rwanda, identifying areas of progress and ongoing scarcity, serving as a guide for future direction of growth. Key points • As Rwanda works on rebuilding its health care system, this study provides an assessment of the current radiologic resources within the country. • There is less than one radiologic unit for every million of the Rwandan population for every imaging modality other than X-ray. • While radiologic access in Rwanda lags behind that of its neighbors, there has been growth focused on advanced imaging modalities and the training of human resources. Graphical Abstract

Abstract The pathogenesis of Parkinson’s disease (PD) is strongly associated with neuroinflammation, and type I interferons (IFN-I) play a crucial role in regulating immune and inflammatory responses. However, the specific features of IFN in different cell types and the underlying mechanisms of PD have yet to be fully described. In this study, we analyzed the GSE157783 dataset, which includes 39,024 single-cell RNA sequencing results for five PD patients and six healthy controls from the Gene Expression Omnibus database. After cell type annotation, we intersected differentially expressed genes in each cell subcluster with genes collected in The Interferome database to generate an IFN-I-stimulated gene set (ISGs). Based on this gene set, we used the R package AUCell to score each cell, representing the IFN-I activity. Additionally, we performed monocle trajectory analysis, and single-cell regulatory network inference and clustering (SCENIC) to uncover the underlying mechanisms. In silico gene perturbation and subsequent experiments confirm NFATc2 regulation of type I interferon response and neuroinflammation. Our analysis revealed that microglia, endothelial cells, and pericytes exhibited the highest activity of IFN-I. Furthermore, single-cell trajectory detection demonstrated that microglia in the midbrain of PD patients were in a pro-inflammatory activation state, which was validated in the 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model as well. We identified transcription factors NFATc2, which was significantly up-regulated and involved in the expression of ISGs and activation of microglia in PD. In the 1-Methyl-4-phenylpyridinium (MPP+)-induced BV2 cell model, the suppression of NFATc2 resulted in a reduction in IFN-β levels, impeding the phosphorylation of STAT1, and attenuating the activation of the NF-κB pathway. Furthermore, the downregulation of NFATc2 mitigated the detrimental effects on SH-SY5Y cells co-cultured in conditioned medium. Our study highlights the critical role of microglia in type I interferon responses in PD. Additionally, we identified transcription factors NFATc2 as key regulators of aberrant type I interferon responses and microglial pro-inflammatory activation in PD. These findings provide new insights into the pathogenesis of PD and may have implications for the development of novel therapeutic strategies.

Although advancements in genomic and epigenetic research have deepened our understanding of acute myeloid leukemia (AML), only one-third of patients can achieve durable remission. Growing evidence suggests that the immune microenvironment in bone marrow influences prognosis and survival in AML. There is a specific association between CD8+ T cells and the prognosis of AML patients. To develop a CD8+ T cell-related immune risk score for AML, we first evaluated the accuracy of CIBERSORTx in predicting the abundance of CD8+ T cells in bulk RNA-seq and found it significantly correlated with observed single-cell RNA sequencing data and the proportions of CD8+ T cells derived from flow cytometry. Next, we constructed the CTCG15, a 15-gene prognostic signature, using univariate and LASSO regression on the differentially expressed genes between CD8+ THigh and CD8+ TLow groups. The CTCG15 was further validated across six datasets in different platforms. The CTCG15 has been shown to be independent of established prognostic markers, and can distill transcriptomic consequences of several genetic abnormalities closely related to prognosis in AML patients. Finally, integrating this model into the 2022 European LeukemiaNet contributed to a higher predictive power for prognosis prediction. Collectively, our study demonstrates that CD8+ T cell-related signature could improve the comprehensive risk stratification and prognosis prediction in AML.

The effective containment of fission products (FPs) within tri-structural isotropic (TRISO) fuel particles is crucial for the safety and efficiency of High Temperature Gas-cooled Reactors (HTGRs). Combining multi-scale (µm to nm) and multi-dimensional (2D and 3D) analysis, this study focuses on the migration mechanisms of silver (Ag), for which the Ag-110 m FP isotope is radiotoxic, facilitated by reactions with palladium (Pd) alloys and the silicon carbide (SiC) layer at elevated temperatures (1300–1500 °C). Three primary pathways for Ag migration are identified: (1) diffusion in solid palladium silicide to form (Pd,Ag)2Si, (2) infiltration through cracks and pores in the carbon phase, and (3) liquid phase migration along SiC grain boundaries. Especially at temperatures above the melting point of Pd2Si (1404 °C), a ‘dissolution-recrystallisation’ mechanism is proposed of the Ag-Pd-Si liquid phase migrating along SiC grain boundaries. The study employs state-of-the-art in-situ heating transmission electron microscopy (TEM) techniques to directly observe the dynamic migration processes of Pd silicide within SiC, providing unprecedented insights into the liquid behaviour in TRISO fuel. These findings highlight the significant role of liquid phases in determining the transport of FPs through the TRISO-SiC which is vital for developing strategies that enhance the safety and efficacy of HTGRs.

Olfaction plays an important role in the survival and reproduction of various organisms. Aside from being a nutrient, in many fish species, amino acids also function as attractants to induce feeding behaviors. As the herbivorous fish, blunt snout bream (Megalobrama amblycephala) commonly consumes an aquatic plant, Hydrilla verticillata. Here, we studied the effect of food odors on the feeding behavior of blunt snout bream using a mixture of amino acids and H. verticillata extract. The behavioral and electro-olfactogram tests demonstrated that the mixture of amino acids and H. verticillata extract induced an attractive reaction and olfactory response in blunt snout bream, respectively. Through Western blotting and immunohistochemical analyses, we confirmed that ciliated and microvillus neurons are distributed on the olfactory placode. The results of phospho-extracellular regulated protein kinases (pERK) showed that a large number of microvillus and ciliated neurons were activated under the stimulation of 10−5 mol/L amino acid mixture and 0.005× H. verticillata extract. The calcium signal imagery demonstrated that the nerve signals of the olfactory bulb were activated by the food odors. The quantitative real-time PCR (qPCR) analysis revealed significant changes in the expression of representative olfactory receptor genes in the olfactory bulb and brain of blunt snout bream upon stimulation with food odor. Collectively, these results provided evidence and preliminary explanations for the mediating role of olfaction in the feeding behavior of fish.

ABSTRACT Numerous host factors, in addition to human angiotensin-converting enzyme 2 (hACE2), have been identified as coreceptors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), demonstrating broad viral tropism and diversified druggable potential. We and others have found that antihistamine drugs, particularly histamine receptor H1 (HRH1) antagonists, potently inhibit SARS-CoV-2 infection. In this study, we provided compelling evidence that HRH1 acts as an alternative receptor for SARS-CoV-2 by directly binding to the viral spike protein. HRH1 also synergistically enhanced hACE2-dependent viral entry by interacting with hACE2. Antihistamine drugs effectively prevent viral infection by competitively binding to HRH1, thereby disrupting the interaction between the spike protein and its receptor. Multiple inhibition assays revealed that antihistamine drugs broadly inhibited the infection of various SARS-CoV-2 mutants with an average IC50 of 2.4 µM. The prophylactic function of these drugs was further confirmed by authentic SARS-CoV-2 infection assays and humanized mouse challenge experiments, demonstrating the therapeutic potential of antihistamine drugs for combating coronavirus disease 19.IMPORTANCEIn addition to human angiotensin-converting enzyme 2, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can utilize alternative cofactors to facilitate viral entry. In this study, we discovered that histamine receptor H1 (HRH1) not only functions as an independent receptor for SARS-CoV-2 but also synergistically enhances ACE2-dependent viral entry by directly interacting with ACE2. Further studies have demonstrated that HRH1 facilitates the entry of SARS-CoV-2 by directly binding to the N-terminal domain of the spike protein. Conversely, antihistamine drugs, primarily HRH1 antagonists, can competitively bind to HRH1 and thereby prevent viral entry. These findings revealed that the administration of repurposable antihistamine drugs could be a therapeutic intervention to combat coronavirus disease 19.

BackgroundSolid pseudopapillary tumor of the pancreas (SPT) is a rare low-grade malignant tumor predominantly observed in young women without significant clinical symptoms. While most SPTs occur in the pancreatic region, rare cases have occurred in the retroperitoneum, making the diagnosis of ectopic SPTs difficult.Case presentationHerein, we report a rare case of an extrapancreatic solid SPT with superior mesenteric artery (SMA) involvement in a 47-year-old man together with a literature review to provide context with clinical information, CT and a literature review.ConclusionsThis case may provide a practical approach for the diagnosis of ectopic SPT, especially for patients with vascular invasion.

IntroductionHuman cytomegalovirus (HCMV) is the most common viral infection seen in newborns. The major route of transmission for acquired human cytomegalovirus infection is breast milk from mothers who are HCMV seropositive to the infants. Thus, a rapid, economical, and simple method to perform HCMV test in breast milk is crucial and necessary for preventing acquired HCMV infection, especially in underdeveloped regions with limited laboratory resources.MethodsIn this study, an effective technique for the detection of HCMV was constructed by combining multienzyme isothermal rapid amplification (MIRA) and lateral flow chromatography strip (LFD). Primers for the conserved HCMV sequence UL83 were utilized for MIRA-LFD testing.ResultsOur results showed that the entire MIRA reaction could be completed in 12 minutes at 37°C, and LFD outcomes could be observed visibly after 10 minutes. The detection sensitivity of this method reached 50 copy/μl. Samples of breast milk were examined to compare MIRA-LFD and conventional qPCR. The accuracy of MIRA-LFD was 100%.DiscussionThe straightforward, rapid, economic features of the test can provide the significant advantages for the prevention of breast milk-acquired cytomegalovirus infection, particularly in resource-limited locations with high seroprevalence of cytomegalovirus.

Abstract This study aimed to develop and validate a deep learning radiomics nomogram (DLRN) for the preoperative evaluation of axillary lymph node (ALN) metastasis status in patients with a newly diagnosed unifocal breast cancer. A total of 883 eligible patients with breast cancer who underwent preoperative breast and axillary ultrasound were retrospectively enrolled between April 1, 2016, and June 30, 2022. The training cohort comprised 621 patients from Hospital I; the external validation cohorts comprised 112, 87, and 63 patients from Hospitals II, III, and IV, respectively. A DLR signature was created based on the deep learning and handcrafted features, and the DLRN was then developed based on the signature and four independent clinical parameters. The DLRN exhibited good performance, yielding areas under the receiver operating characteristic curve (AUC) of 0.914, 0.929, and 0.952 in the three external validation cohorts, respectively. Decision curve and calibration curve analyses demonstrated the favorable clinical value and calibration of the nomogram. In addition, the DLRN outperformed five experienced radiologists in all cohorts. This has the potential to guide appropriate management of the axilla in patients with breast cancer, including avoiding overtreatment.

Abstract Background The relationship between vitamin D status and mortality among adults with hypertension remains unclear. Methods This prospective cohort study involved a sample of 19,500 adults with hypertension who participated in the National Health and Nutrition Examination Survey (NHANES) from 2001 to 2018. We utilized a weighted COX proportional hazard model to assess the association between vitamin D status and mortality. This statistical model calculates hazard ratios (HR) and their corresponding 95% confidence intervals (95% CI). Results The study indicated that lower serum 25(OH)D concentration was associated with an increased risk of all-cause mortality among individuals with hypertension. Specially. Those with concentrations between 25.0 and 49.9 nmol/L (HR = 1.71, 95%CI = 1.22–2.40) and less than 25.0 nmol/L (HR = 1.97, 95%CI = 1.15–3.39) had higher hazard ratios for all-cause mortality. Individuals with hypertension who took vitamin D supplements had a lower risk of all-cause mortality, but not the risk of CVD mortality (HR 0.75, 95%CI 0.54–1.03), compared to those who did not supplement (HR = 0.76, 95%CI = 0.61–0.94). Subgroup analysis further revealed that vitamin D supplementation was associated with a reduced risk of all-cause mortality among individuals without diabetes (HR = 0.65, 95%CI = 0.52–0.81) and individuals without CVD (HR = 0.75, 95%CI = 0.58–0.97), and a decreased risk of CVD mortality among individuals without diabetes (HR = 0.63, 95%CI = 0.45–0.88) and without CVD (HR = 0.61, 95%CI = 0.40–0.92). Furthermore, higher-dose vitamin D supplementation was also associated with a greater reduction in all-cause mortality among hypertensive individuals, and there was the potential synergistic effect of combining normal-dose calcium and vitamin D supplementation, showing a superior effect on mortality compared to low-dose supplementation in adults with hypertension. Conclusions This prospective cohort study demonstrated a significant association between lower serum 25 (OH)D concentration and increased all-cause mortality among adults with hypertension. Furthermore, the study found that vitamin D supplementation had a strong and significantly positive correlation with reduced all-cause and CVD mortality among hypertensive individuals without diabetes or CVD. This positive correlation suggests that vitamin D supplementation could potentially be an effective strategy to reduce the risk of mortality in this specific group of people.

The role of co-agonists of glucagon-like peptide-1 receptor (GLP-1R) and glucagon receptor (GCGR) in chronic kidney disease (CKD) remains unclear. Herein we found that GLP-1R and GCGR expression levels were lower in the kidneys of mice with CKD compared to healthy mice and were correlated with disease severity. Interestingly, GLP-1R or GCGR knockdown aggravated the progression of kidney injury in both diabetic db/db mice and non-diabetic mice undergoing unilateral ureteral obstruction (UUO). Based on the importance of GLP-1R and GCGR in CKD, we reported a novel monomeric peptide, 1907-B, with dual-agonism on both GLP-1R and GCGR. The data confirmed that 1907-B had a longer half-life than long-acting semaglutide in rats or cynomolgus monkeys (∼2–3 fold) and exhibited better therapeutic contribution to CKD than best-in-class monoagonists, semaglutide, or glucagon, in db/db mice and UUO mice. Various lock-of-function models, including selective pharmacological activation and genetic knockdown, confirmed that 1907-B's effects on ameliorating diabetic nephropathy in db/db mice, as well as inhibiting kidney fibrosis in UUO mice, were mediated through GLP-1 and glucagon signaling. These findings highlight that 1907-B, a novel GLP-1R and GCGR co-agonist, exerts multifactorial improvement in kidney injuries and is an effective and promising therapeutic option for CKD treatment.

Abstract In this study, a new short‐term wind power prediction model based on a temporal convolutional network (TCN) and the Informer model is proposed to solve the problem of low prediction accuracy caused by large wind speed fluctuations in short‐term prediction. First, an input feature selection method based on the maximum information coefficient is proposed after considering the problem of information interference caused by excessively large input features. A dynamic time planning method is used to select the optimal input step of historical power. Then, the combined forecasting model composed of TCN and the Informer is constructed in accordance with the numerical weather forecast and historical power data. Lastly, the pinball loss function is used to expand the prediction model into a quantile regression model, measure the effect of volatility, quantify the volatility range of prediction, and finally, obtain a deterministic prediction result. The actual measured data of wind farms in the Bohai Sea area are selected for analysis and calculation. The results show that the prediction model proposed in this study achieves better accuracy in deterministic prediction and interval prediction than the traditional model.

Abstract Background Infectious diseases are a serious threat to human especially since the COVID-19 outbreak has proved the importance and urgency of their diagnosis and treatment again. Metagenomic next-generation sequencing (mNGS) has been widely used and recognized in clinical and carried out localized testing in hospitals. Increasing the training of mNGS detection technicians can enhance their professional quality and more effectively realize the application value of the hospital platform. Methods Based on the initial theoretical understanding and practice of the mNGS platform for localization construction, we have designed a training program to enhance the ability of technicians to detect pathogens by utilizing mNGS, and hence to conduct training practices nationwide. Results Until August 30, 2022, the page views of online classes have reached 51,500 times and 6 of offline small-scale training courses have been conducted. A total of 67 trainees from 67 hospitals have participated in the training with a qualified rate of 100%. After the training course, the localization platform of 1 participating hospital has been put into use, 2 have added the mNGS localization platform for admission, among which 3 have expressed strong intention of localization. Conclusions This study focuses on the training procedures and practical experience of the project which is the first systematic standardized program of mNGS in the world. It solves the training difficulties in the current industry, and effectively promotes the localization construction and application of mNGS in hospitals. It has great development potential in the future and is worth further promotion.

Abstract Background Pathway mutations have been calculated to predict the poor prognosis and immunotherapy resistance in head and neck squamous cell carcinoma (HNSCC). To uncover the unique markers predicting prognosis and immune therapy response, the accurate quantification of pathway mutations are required to evaluate epithelial-mesenchymal transition (EMT) and immune escape. Yet, there is a lack of score to accurately quantify pathway mutations. Material and methods Firstly, we proposed Individualized Weighted Hallmark Gene Set Mutation Burden (IWHMB, https://github.com/YuHongHuang-lab/IWHMB ) which integrated pathway structure information and eliminated the interference of global Tumor Mutation Burden to accurately quantify pathway mutations. Subsequently, to further elucidate the association of IWHMB with EMT and immune escape, support vector machine regression model was used to identify IWHMB-related transcriptomic features (IRG), while Adversarially Regularized Graph Autoencoder (ARVGA) was used to further resolve IRG network features. Finally, Random walk with restart algorithm was used to identify biomarkers for predicting ICI response. Results We quantified the HNSCC pathway mutation signatures and identified pathway mutation subtypes using IWHMB. The IWHMB-related transcriptomic features (IRG) identified by support vector machine regression were divided into 5 communities by ARVGA, among which the Community 1 enriching malignant mesenchymal components promoted EMT dynamically and regulated immune patterns associated with ICI responses. Bridge Hub Gene (BHG) identified by random walk with restart was key to IWHMB in EMT and immune escape, thus, more predictive for ICI response than other 70 public signatures. Conclusion In summary, the novel pathway mutation scoring-IWHMB suggested that the elevated malignancy mediated by pathway mutations is a major cause of poor prognosis and immunotherapy failure in HNSCC, and is capable of identifying novel biomarkers to predict immunotherapy response.

Abstract Appropriate antibiotic dosing to ensure early and sufficient target attainment is crucial for improving clinical outcome in critically ill patients. Parametric survival analysis is a preferred modeling method to quantify time‐varying antibiotic exposure – response effects, whereas bias may be introduced in hazard functions and survival functions when competing events occur. This study investigated predictors of in‐hospital mortality in critically ill patients treated with meropenem by pharmacometric multistate modeling. A multistate model comprising five states (ongoing meropenem treatment, other antibiotic treatment, antibiotic treatment termination, discharge, and death) was developed to capture the transitions in a cohort of 577 critically ill patients treated with meropenem. Various factors were investigated as potential predictors of the transitions, including patient demographics, creatinine clearance calculated by Cockcroft–Gault equation (CLCRCG), time that unbound concentrations exceed the minimum inhibitory concentration (fT>MIC), and microbiology‐related measures. The probabilities to transit to other states from ongoing meropenem treatment increased over time. A 10 mL/min decrease in CLCRCG was found to elevate the hazard of transitioning from states of ongoing meropenem treatment and antibiotic treatment termination to the death state by 18%. The attainment of 100% fT>MIC significantly increased the transition rate from ongoing meropenem treatment to antibiotic treatment termination (by 9.7%), and was associated with improved survival outcome. The multistate model prospectively assessed predictors of death and can serve as a useful tool for survival analysis in different infection scenarios, particularly when competing risks are present.

The aim of this study was to isolate biocontrol bacteria that could antagonize brown rot of Dendrocalamus latiflorus, optimize the culture conditions, and develop an effective biocontrol preparation for brown rot of D. latiflorus. This study isolated a bacterium with an antagonistic effect on bamboo brown rot from healthy D. latiflorus rhizosphere soil. Morphology, molecular biology, and physiological biochemistry methods identified it as Bacillus siamensis. The following culturing media and conditions improved the inhibition effect of B. siamensis: the best culturing media were 2% sucrose, 1.5% yeast extract, and 0.7% potassium chloride; the optimal culturing time, temperature, pH, and inoculation amount were 48 h, 30°C, 6, and 20%. The optimum formula of the applying bacterial suspension was 14% sodium dodecyl benzene sulfonate emulsifier, 4% Na2HPO4·2H2O, 0.3% hydroxypropyl methylcellulose thickener, and 20% B. siamensis. The pot experiment results showed the control effect of applying bacterial suspension, diluted 1,000 times is still better than that of 24% fenbuconazole suspension. The applying bacterial suspension enables reliable control of brown rot in D. latiflorus.

Calcium-based biomaterials have been intensively studied in the field of drug delivery owing to their excellent biocompatibility and biodegradability. Calcium-based materials can also deliver contrast agents, which can enhance real-time imaging and exert a Ca2+-interfering therapeutic effect. Based on these characteristics, amorphous calcium carbonate (ACC), as a brunch of calcium-based biomaterials, has the potential to become a widely used biomaterial. Highly functional ACC can be either discovered in natural organisms or obtained by chemical synthesis However, the standalone presence of ACC is unstable in vivo. Additives are required to be used as stabilizers or core–shell structures formed by permeable layers or lipids with modified molecules constructed to maintain the stability of ACC until the ACC carrier reaches its destination. ACC has high chemical instability and can produce biocompatible products when exposed to an acidic condition in vivo, such as Ca2+ with an immune-regulating ability and CO2 with an imaging-enhancing ability. Owing to these characteristics, ACC has been studied for self-sacrificing templates of carrier construction, targeted delivery of oncology drugs, immunomodulation, tumor imaging, tissue engineering, and calcium supplementation. Emphasis in this paper has been placed on the origin, structural features, and multiple applications of ACC. Meanwhile, ACC faces many challenges in clinical translation, and long-term basic research is required to overcome these challenges. We hope that this study will contribute to future innovative research on ACC.

The integration of Artificial Intelligence (AI) and Wearable Internet of Things (WIoT) for mental health detection is a promising area of research with the potential to revolutionize mental health monitoring and diagnosis. Since early detection of mental diseases, i.e., depression, is of great importance for diagnosis and treatment, a fast and convenient way is urgently needed. Traditional diagnostic methods are time-consuming, laborious, over-subjective, and easily lead to misdiagnosis. The advance in information techniques and wearable devices brings innovation to mental disease detection. Therefore, this article first compares intelligent depression detection methods and traditional methods to illustrate the significance and then analyzes the opportunities of the wearable device. Then we provide specific psychophysiological data measured by wearable devices and introduce relevant datasets for depression detection. An illustrative example of depression detection with sleep data is presented and discussed and our proposed ensemble method has improved nearly 10% to baselines. Analytical results demonstrate the great potential of using wearable device-measured psychophysiological data to detect depression intelligently.

Abstract Background The overall comprehensive consideration of the factors influencing the recommendations in the traditional Chinese medicine (TCM) guidelines remains poorly studied. This study systematically evaluate the factors influencing recommendations formation in the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) clinical practice guidelines (CPGs) and TCM CPGs. Methods This was a methodological review in which we searched six databases and multiple related websites. The GRADE CPGs were identified as the guidelines developed by the GRADE Working Group or the two Co-Chairs. For the TCM CPGs, we randomly selected guidelines that were published by the TCM or integrative medicine academic societies from China mainland (published by the TCM or integrative medicine academic societies of China mainland). Two reviewers independently screened and extracted data. We included CPGs published in 2018–2022. We extracted information on the influencing factors of evidence to recommendation and conducted the analyses using descriptive statistics and calculated the proportion of relevant items by IBM SPSS Statistics and Microsoft Excel to compare the differences between the GRADE CPGs and the TCM CPGs. Results Forty-five GRADE CPGs (including 912 recommendations) and 88 TCM CPGs (including 2452 recommendations) were included. TCM recommendations mainly considered the four key determinants of desirable anticipated effects, undesirable anticipated effects, balance between desirable and undesirable effects, certainty of evidence, with less than 20% of other dimensions. And TCM CPGs presented more strong recommendations (for or against) and inappropriate discordant recommendations than GRADE CPGs. GRADE CPGs were more comprehensive considered about the factors affecting the recommendations, and considered more than 70% of all factors in the evidence to recommendation. Conclusions The TCM CPGs lack a comprehensive consideration of multiple influencing determinants from evidence to recommendations. In the future, the correct application of the GRADE approaches should be emphasized.

Abstract Background Concerns have been raised regarding the impact of preoperative intravenous dexamethasone on postoperative glycemic control in diabetic patients undergoing total joint arthroplasty (TJA). This study aimed to determine relationships between preoperative different dexamethasone regimens and postoperative fasting blood glucose (FBG), as well as to identify risk factors for postoperative FBG ≥ 200 mg/dl in diabetic patients undergoing TJA. Methods This retrospective study included 1216 diabetic patients undergoing TJA and categorized into group A (dexamethasone = 0 mg), group B (dexamethasone = 5 mg), and group C (dexamethasone = 10 mg). All dexamethasone was administered before skin incision. FBG levels were monitored until postoperative day (POD) 3. Analyses were conducted for periprosthetic joint infection (PJI) and wound complications during 90 days postoperatively. And the risk factors for postoperative FBG ≥ 200 mg/dl were identified. Results Preoperative dexamethasone administration resulted in a transiently higher FBG on POD 0 and POD 1 (all P

Abstract Background Uncontrolled ulcer bleeding of duodenal ulcer (DU) after endoscopic therapy often needs surgery. At present, cutting the bottom of the ulcer with ligation and performing its excision-lesion are the common ways to achieve immediate efficacy in stopping bleeding. For the problem of its great trauma, we seek an easy and useful technical method to reach the same therapeutic effect to stop acute bleeding. Methods We determined the distribution of the lesion and its innervated blood vessels under the guidance of the endoscopy and then performed suture and hemostasis on the external surface of the stomach and duodenum. Results An immediate efficacy in stopping bleeding was shown and the hemoglobin (Hb) level returned to normal after operation with no recurrence of bleeding. Conclusion We created a successful and novel strategy for laparotomy-endoscopic assisted suture for DU emergency hemostasis without duodenectomy.

Accurately understanding the temperature field distribution and hot-spot temperature of oil-immersed transformers is of great significance for ensuring the safe and stable operation of the transformer. A magnetic-thermal-flow coupling simulation model for oil-immersed transformer is established in this paper. In order to better simulate the heat dissipation process of the transformer, the winding uses a pie shaped structure with interval arrangement instead of the traditional cylindrical structure. The losses of iron core and winding are calculated through magnetic field simulation. Then, the losses are used as heat source for coupling simulation of thermal field and laminar flow to obtain the oil flow distribution, 3-D temperature field distribution, and temperature and location distribution of hot-spot. Finally, coupling simulations are conducted under different load currents to analyze the impact of load currents on the temperature and location of transformer hotspots. The simulation results show that as the current increases, the hot-spot temperature increases. When the load current changes, the hot-spot fluctuates within the range of 85% - 90% of the total height of the low-voltage winding, providing a methodological basis for the maintenance of transformers and monitoring of hot-spot temperatures.

Few-shot image classification remains a persistent challenge due to the intrinsic difficulty faced by visual recognition models in achieving generalization with limited training data. Existing methods primarily focus on exploiting marginal distributions and overlook the disparity between the product of marginals and the joint characteristic functions. This can lead to less robust feature representations. In this paper, we introduce DBDC-SSL, a method that aims to improve few-shot visual recognition models by learning a feature extractor that produces image representations that are more robust. To improve the robustness of the model, we integrate DeepBDC (DBDC) during the training process to learn better feature embeddings by effectively computing the disparity between product of the marginals and joint characteristic functions of the features. To reduce overfitting and improve the generalization of the model, we utilize an auxiliary rotation loss for self-supervised learning (SSL) in the training of the feature extractor. The auxiliary rotation loss is derived from a pretext task, where input images undergo rotation by predefined angles, and the model classifies the rotation angle based on the features it generates. Experimental results demonstrate that DBDC-SSL is able to outperform current state-of-the-art methods on 4 common few-shot image classification benchmark, which are miniImageNet, tieredImageNet, CUB and CIFAR-FS. For 5-way 1-shot and 5-way 5-shot tasks respectively, the proposed DBDC-SSL achieved the accuracy of 68.64±0.43 and 86.02±0.28 on miniImageNet, 73.88±0.48 and 89.03±0.29 on tieredImageNet, 84.67±0.39 and 94.76±0.16 on CUB, and 75.60±0.44 and 88.49±0.31 on CIFAR-FS.

Additive manufacturing is capable of forming part solids from a digital model of the workpiece, which often needs to be sliced due to the nature of the process of stacking materials layer by layer. Previous algorithms require more time to order the intersection points during slicing and only consider a fixed axis vector as the slicing direction. With the increasing complexity of the workpiece model, it is necessary to improve the efficiency of the slicing algorithm, and the given slicing direction should be flexible and convenient. Therefore, this paper proposes an efficient algorithm for slicing in any direction using the shared edges of adjacent triangles. Firstly, the model can be efficiently sliced in any direction by custom vectors, which is convenient for process validation; secondly, the shared edges of neighboring triangular facets intersecting the plane need to be calculated only once to reduce redundant calculations; finally, the ordered intersections of the constructed inner and outer contours are directly outputted without any additional sorting to reduce the running time. The experimental results show that compared with other algorithms, the proposed algorithm can improve the execution efficiency and eliminate the constraint that the slicing direction is fixed on the Z-axis, which is of application value and reference significance for additive.

Few-shot learning continues to pose a challenge as it is inherently difficult for visual recognition models to generalize with limited labeled examples. When the training data is limited, the process of training and fine-tuning the model will be unstable and inefficient due to overfitting. In this paper, we introduce NegCosIC: Negative Cosine Similarity-Invariance-Covariance Regularization, a method that aims to improve the mean accuracy from the perspective of stabilizing the fine-tuning process and regularizing variance. NegCosIC incorporates a negative simple cosine similarity loss to stabilize the parameters of the feature extractor during fine-tuning. In addition, NegCosIC integrates invariance loss and covariance loss to regularize the embeddings in order to reduce overfitting. Experimental results demonstrate that NegCosIC is able to bring substantial improvements over the current state-of-the-art methods. An in-depth worse case analysis is also conducted and shows that NegCosIC is able to outperform state-of-the-art methods on worst case accuracy. The proposed NegCosIC achieved 2.15% and 2.13% higher accuracy on miniImageNet 1-shot and 5-shot tasks, 3.22% and 2.67% higher accuracy on CUB 1-shot and 5-shot tasks, and 2.13% and 7.74% higher accuracy on CIFAR-FS 1-shot and 5-shot tasks in terms of worst-case accuracies.

Non terrestrial network (NTN) has been regarded as an important component of beyond 5G communication. The 3rd Generation Partnership Project (3GPP) has officially started studies on NTN for the purpose of integrating satellites with New Radio (NR) terrestrial networks. However, the NR defined orthogonal frequency division multiplexing (OFDM) waveform is susceptible to doubly selective fading and nonlinear distortions in the NTN uplink, thus leading to severe performance loss. In this paper, a type of block scalable OFDM (BS-OFDM) waveform is proposed, which has modified subcarrier and sub-symbol segmentation when compared to the conventional NR defined OFDM. With our proposed framework, block scalable discrete Fourier transform spread OFDM (BS-DFT-s-OFDM) and block scalable orthogonal time frequency space (BS-OTFS) can also be implemented. To obtain a comprehensive understanding of different waveforms, performance metrics concerning peak to average power ratio (PAPR), total degradation (TD), bit error rate (BER), and complexity are presented. The simulation results demonstrate that the proposed block scalable waveforms can obtain better performance and lower complexity than existing NR waveforms in different NTN uplink scenarios, and can therefore be promising candidate waveforms for NR NTN.

The overdiagnosis of prostate cancer (PCa) caused by nonspecific elevation serum prostate-specific antigen (PSA) and the overtreatment of indolent PCa have become a global problem that needs to be solved urgently. We aimed to construct a prediction model and provide a risk stratification system to reduce unnecessary biopsies. In this retrospective study, clinical data of 1807 patients from three Chinese hospitals were used. The final model was built using stepwise logistic regression analysis. The apparent performance of the model was assessed by receiver operating characteristic curves, calibration plots, and decision curve analysis. Finally, a risk stratification system of clinically significant prostate cancer (csPCa) was created, and diagnosis-free survival analyses were performed. Following multivariable screening and evaluation of the diagnostic performances, a final diagnostic model comprised of the PSA density and Prostate Imaging-Reporting and Data System (PI-RADS) score was established. Model validation in the development cohort and two external cohorts showed excellent discrimination and calibration. Finally, we created a risk stratification system using risk thresholds of 0.05 and 0.60 as the cut-off values. The follow-up results indicated that the diagnosis-free survival rate for csPCa at 12 months and 24 months postoperatively was 99.7% and 99.4%, respectively, for patients with a risk threshold below 0.05 after the initial negative prostate biopsy, which was significantly better than patients with higher risk. Our diagnostic model and risk stratification system can achieve a personalized risk calculation of csPCa. It provides a standardized tool for Chinese patients and physicians when considering the necessity of prostate biopsy.

Multimodal Aspect-Based Sentiment Analysis (MABSA), as an emerging task in the field of sentiment analysis, has recently received widespread attention. Its aim is to combine relevant multimodal data to determine the sentiment polarity of a given aspect in text. Researchers have surveyed both aspect-based sentiment analysis and multimodal sentiment analysis, but, to the best of our knowledge, there is no survey on MABSA. Therefore, in order to assist related researchers to know MABSA better, we surveyed the research work on MABSA in recent years. Firstly, the relevant concepts of MABSA were introduced. Secondly, the existing research methods for the two subtasks of MABSA research (that is, multimodal aspect sentiment classification and aspect sentiment pairs extraction) were summarized and analyzed, and the advantages and disadvantages of each type of method were analyzed. Once again, the commonly used evaluation corpus and indicators for MABSA were summarized, and the evaluation results of existing research methods on the corpus were also compared. Finally, the possible research trends for MABSA were envisioned.

ABSTRACT: The transition period in dairy cows is a critical stage and peripartum oxidative status, negative energy balance (NEB), and inflammation are highly prevalent. Fecal microbial metabolism is closely associated with blood oxidative status and nonesterified fatty acids (NEFA) levels. Here, we investigated dynamic changes in total oxidative status markers and NEFA in blood, fecal microbiome, and metabolome of 30 dairy cows during transition (−21, −7, +7, +21 d relative to calving). Then the Bayesian network and 9 machine-learning algorithms were applied to dismantle their relationship. Our results show that the oxidative status indicator (OSI) of −21, −7, +7 d was higher than +21 d. The plasma concentration of NEFA peaked on +7 d. For fecal microenvironment, a decline in bacterial α diversity was observed at postpartum and in bacterial interactions at +7 d. Conversely, microbial metabolites involved in carbohydrate, lipid, and energy metabolism increased on +7 d. A correlation analysis revealed that 11 and 10 microbial metabolites contributed to OSI and NEFA variations, respectively (arc strength >0.5). The support vector machine (SVM) radial model showed the highest average predictive accuracy (100% and 88.9% in the test and external data sets) for OSI using 1 metabolite and 3 microbiota. The SVM radial model also showed the highest average diagnostic accuracy (100% and 91% in the test and external data sets) for NEFA with 2 metabolites and 3 microbiota. Our results reveal a relationship between variation in the fecal microenvironment and indicators of oxidative status, NEB, and inflammation, which provide a theoretical basis for the prevention and precise regulation of peripartum oxidative status and NEB.

Abstract Ferroptosis is an iron-dependent cell death mechanism involving the accumulation of lipid peroxides. As a critical regulator, glutathione peroxidase 4 (GPX4) has been demonstrated to be downregulated in epilepsy. However, the mechanism of ferroptosis in epilepsy remains unclear. In this study, bioinformatics analysis, analysis of epilepsy patient blood samples and cell and mouse experiments revealed strong associations among epilepsy, ferroptosis, microRNA-211-5p and purinergic receptor P2X 7 (P2RX7). P2RX7 is a nonselective ligand-gated homotrimeric cation channel, and its activation mainly increases neuronal activity during epileptic seizures. In our study, the upregulation of P2RX7 in epilepsy was attributed to the downregulation of microRNA (miR)-211-5p. Furthermore, P2RX7 has been found to regulate GPX4/HO-1 by alleviating lipid peroxidation induced by suppression of the MAPK/ERK signaling pathway in murine models. The dynamic decrease in miR-211-5p expression induces hypersynchronization and both nonconvulsive and convulsive seizures, and forebrain miR-211-5p suppression exacerbates long-lasting pentylenetetrazole-induced seizures. Additionally, in this study, induction of miR-211-5p expression or genetic-silencing of P2RX7 significantly reduced the seizure score and duration in murine models through the abovementioned pathways. These results suggest that the miR-211-5p/P2RX7 axis is a novel target for suppressing both ferroptosis and epilepsy.