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Abstract Lung Cancer remains the leading cause of cancer deaths in the USA and worldwide. Non-small cell lung cancer (NSCLC) harbors high transcriptomic intratumor heterogeneity (RNA-ITH) that limits the reproducibility of expression-based prognostic models. In this study, we used multiregional RNA-seq data (880 tumor samples from 350 individuals) from both public (TRACERx) and internal (MDAMPLC) cohorts to investigate the effect of RNA-ITH on prognosis in localized NSCLC at the gene, signature, and tumor microenvironment levels. At the gene level, the maximal expression of hazardous genes (expression negatively associated with survival) but the minimal expression of protective genes (expression positively associated with survival) across different regions within a tumor were more prognostic than the average expression. Following that, we examined whether multiregional expression profiling can improve the performance of prognostic signatures. We investigated 11 gene signatures collected from previous publications and one signature developed in this study. For all of them, the prognostic prediction accuracy can be significantly improved by converting the regional expression of signature genes into sample-specific expression with a simple function—taking the maximal expression of hazardous genes and the minimal expression of protective genes. In the tumor microenvironment, we found a similar rule also seems applicable to immune ITH. We calculated the infiltration levels of major immune cell types in each region of a sample based on expression deconvolution. Prognostic analysis indicated that the region with the lowest infiltration level of protective or highest infiltration level of hazardous immune cells determined the prognosis of NSCLC patients. Our study highlighted the impact of RNA-ITH on the prognostication of NSCLC, which should be taken into consideration to optimize the design and application of expression-based prognostic biomarkers and models. Multiregional assays have the great potential to significantly improve their applications to prognostic stratification.

Abstract Background Bone metastasis (BM) occurs when colon cancer cells disseminate from the primary tumor site to the skeletal system via the bloodstream or lymphatic system. The emergence of such bone metastases typically heralds a significantly poor prognosis for the patient. This study's primary aim is to develop a machine learning model to identify patients at elevated risk of bone metastasis among those with right-sided colon cancer undergoing complete mesocolonectomy (CME). Patients and methods The study cohort comprised 1,151 individuals diagnosed with right-sided colon cancer, with a subset of 73 patients presenting with bone metastases originating from the colon. We used univariate and multivariate regression analyses as well as four machine learning algorithms to screen variables for 38 characteristic variables such as patient demographic characteristics and surgical information. The study employed four distinct machine learning algorithms, namely, extreme gradient boosting (XGBoost), random forest (RF), support vector machine (SVM), and k-nearest neighbor algorithm (KNN), to develop the predictive model. Additionally, the model was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA), while Shapley additive explanation (SHAP) was utilized to visualize and analyze the model. Results The XGBoost algorithm performed the best performance among the four prediction models. In the training set, the XGBoost algorithm had an area under curve (AUC) value of 0.973 (0.953–0.994), an accuracy of 0.925 (0.913–0.936), a sensitivity of 0.921 (0.902–0.940), and a specificity of 0.908 (0.894–0.922). In the validation set, the XGBoost algorithm had an AUC value of 0.922 (0.833–0.995), an accuracy of 0.908 (0.889–0.926), a sensitivity of 0.924 (0.873–0.975), and a specificity of 0.883 (0.810–0.956). Furthermore, the AUC value of 0.83 for the external validation set suggests that the XGBoost prediction model possesses strong extrapolation capabilities. The results of SHAP analysis identified alkaline phosphatase (ALP) levels, tumor size, invasion depth, lymph node metastasis, lung metastasis, and postoperative neutrophil-to-lymphocyte ratio (NLR) levels as significant risk factors for BM from right-sided colon cancer subsequent to CME. Conclusion The prediction model for BM from right-sided colon cancer developed using the XGBoost machine learning algorithm in this study is both highly precise and clinically valuable.

Abstract Multiple synchronous lung cancers (MSLCs) constitute a unique subtype of lung cancer. To explore the genomic and immune heterogeneity across different pathological stages of MSLCs, we analyse 16 MSLCs from 8 patients using single-cell RNA-seq, single-cell TCR sequencing, and bulk whole-exome sequencing. Our investigation indicates clonally independent tumours with convergent evolution driven by shared driver mutations. However, tumours from the same individual exhibit few shared mutations, indicating independent origins. During the transition from pre-invasive to invasive adenocarcinoma, we observe a shift in T cell phenotypes characterized by increased Treg cells and exhausted CD8+ T cells, accompanied by diminished cytotoxicity. Additionally, invasive adenocarcinomas exhibit greater neoantigen abundance and a more diverse TCR repertoire, indicating heightened heterogeneity. In summary, despite having a common genetic background and environmental exposure, our study emphasizes the individuality of MSLCs at different stages, highlighting their unique genomic and immune characteristics.

Abstract The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

In order to reduce personnel and increase efficiency in the underground slurry filling system of coal mines and accelerate the intelligent process of slurry filling technology, a filling control method based on intelligent PID algorithm was proposed to realize accurate pulping. A monitoring and fault intelligent identification method for slurry pipelines has been constructed, achieving early warning of pipeline blockage and rapid fault handling. Integrated with a data-driven production management system and AI+NOSA intelligent control platform, the safety production management of the entire slurry filling system has achieved intelligent and comprehensive coverage. The application effect shows that after the system is officially put into use, it has achieved integration of system monitoring, less manual filling production, digital production management, and standardized equipment control. The efficiency of slurry filling is increased by more than 40%, and the failure shutdown rate of the filling system is reduced by more than 60%. The labor quota has been reduced from 15 to 3, resulting in a significant decrease in labor intensity and a significant improvement in production efficiency.

Abstract Introduction Bronchobiliary fistulas are rare and difficult to treat. Peacock first reported this entity in 1850 while treating a patient with hepatic encopresis. Case presentation A 67-year-old Chinese male patient presented to the outpatient clinic with a complaint of coughing up phlegm with chest tightness for 4 days with symptoms of intermittent bilirubin sputum with a sputum volume of about 500 ml per day but no symptoms of abdominal pain or jaundice and no yellow urine or steatorrhea. The examination revealed cyanosis of the lips and mouth, barrel chest, low breath sounds on the right side, and a large number of wet rales heard in both lungs. The imaging investigations were suggestive of bronchobiliary fistula. Therefore, the patient was operated on and discharged with no perioperative complications. Conclusion Bronchobiliary fistula should be considered diagnostically in patients with known liver disease who also experience trauma or medical treatment and cough up bile-colored sputum, regardless of the presence of concurrent infections, and in conjunction with radiological expertise to identify it. Here, we report a case of bronchobiliary fistula and a brief review of the literature on it.

Abstract Endophytes have been shown to promote plant growth and health. In the present study, a Bacillus velezensis CH1 (CH1) strain was isolated and identified from high-quality oats, which was capable of producing indole-3-acetic acid (IAA) and strong biofilms, and capabilities in the nitrogen-fixing and iron carriers. CH1 has a 3920 kb chromosome with 47.3% GC content and 3776 code genes. Compared genome analysis showed that the largest proportion of the COG database was metabolism-related (44.79%), and 1135 out of 1508 genes were associated with the function “biosynthesis, transport, and catabolism of secondary metabolites.” Furthermore, thirteen gene clusters had been identified in CH1, which were responsible for the synthesis of fifteen secondary metabolites that exhibit antifungal and antibacterial properties. Additionally, the strain harbors genes involved in plant growth promotion, such as seven putative genes for IAA production, spermidine and polyamine synthase genes, along with multiple membrane-associated genes. The enrichment of these functions was strong evidence of the antimicrobial properties of strain CH1, which has the potential to be a biofertilizer for promoting oat growth and disease resistance.

PurposeTo clarify the prognostic value of lymph node regression (LNR) status including the lymph node regression grade (LNRG) and N downstaging in patients with esophageal cancer receiving neoadjuvant therapy based on available evidence.MethodsSeveral databases were searched up to 25 March 2024. The main outcomes included overall survival (OS), disease-free survival (DFS) and cancer-specific survival (CSS). Hazard ratios (HRs) and 95% confidence intervals (CIs) were combined. Subgroup analyses based on the neoadjuvant therapy and pathological type were also conducted.ResultsIn total, 14 retrospective studies with 3,212 participants were included. Nine and five studies explored the relationship between LNRG and N downstaging and survival, respectively. Pooled results indicated that complete LNR predicted significantly improved OS (HR = 0.47, 95% CI: 0.41–0.55, P < 0.001) and DFS (HR = 0.42, 95% CI: 0.32–0.55, P < 0.001) and subgroup analysis based on neoadjuvant therapy and pathological type manifested similar results. Besides, N downstaging was also significantly related to improved OS (HR = 0.40, 95% CI: 0.21–0.77, P = 0.006) and CSS (HR = 0.27, 95% CI: 0.12–0.60, P < 0.001).ConclusionLNR could serve as a novel and reliable prognostic factor in patients with esophageal cancer receiving neoadjuvant therapy and complete LNR and N downstaging predict better survival.

Fatty acyl desaturases (Fads) are crucial enzymes that catalyze the rate-limiting step of the desaturation reactions by introducing a double bond into to pre-existing fatty acyl chains. As a group of key enzymes involved in the biosynthesis of long-chain polyunsaturated fatty acids (LC-PUFAs), Fads have been well investigated in teleost fishes but they are still rarely known in chondrichthyans. In this study, we first identified a fatty acyl desaturases gene (fads2) from the Chinese sturgeon (Acipenser sinensis), a critically endangered cartilaginous species in China, by combining with bioinformatic analyses and molecular cloning methods. Then, the spatio-temporal distribution patterns, functional characteristics and transcriptional changes of this gene in response to different nutritional conditions were investigated. The coding sequences of the fads2 gene was 1350 bp in length, encoding a protein of 449 amino acids. Multiple protein sequences alignment, genetic synteny and phylogenetic analyses further suggested that fads2 gene was evolutionary conserved. Functional characterization by heterologous expression in yeast showed that Fads2 exhibited Δ6 and Δ8 bifunctional desaturation activities, and possessed capacities to convert 18:2n-6, 18:3n-3, 20:2n-6 and 20:3n-3–18:3n-6, 18:4n-3, 20:3n-6 and 20:4n-3, respectively. In vivo experiment, diets full with C18 PUFA but not LC-PUFA significantly induced the expression levels of fads2 in Chinese sturgeon brain and liver tissues. Our findings suggest that fads2 is an evolutionary and functionally conserved desaturase in Chinese sturgeon, and which plays important roles in regulation of endogenous LC-PUFAs biosynthesis. In summary, these findings will provide a new insight into the evolutionary history of key enzymes of LC-PUFA biosynthesis in vertebrates.

Lung cancer, one of the most prevalent cancers worldwide, stands as the primary cause of cancer-related deaths. As is well-known, the utmost crucial risk factor contributing to lung cancer is smoking. In recent years, remarkable progress has been made in treating lung cancer, particularly non-small cell lung cancer (NSCLC). Nevertheless, the absence of effective and accurate biomarkers for diagnosing and treating lung cancer remains a pressing issue. Interleukin 22 (IL-22) is a member of the IL-10 cytokine family. It exerts biological functions (including induction of proliferation and anti-apoptotic signaling pathways, enhancement of tissue regeneration and immunity defense) by binding to heterodimeric receptors containing type 1 receptor chain (R1) and type 2 receptor chain (R2). IL-22 has been identified as a pro-cancer factor since dysregulation of the IL-22-IL-22R system has been implicated in the development of different cancers, including lung, breast, gastric, pancreatic, and colon cancers. In this review, we discuss the differential expression, regulatory role, and potential clinical significance of IL-22 in lung cancer, while shedding light on innovative approaches for the future.

Summary: This study aims to elucidate the pivotal role of aldolase A (ALDOA) in retinoblastoma (RB) and evaluate the potential of the ALDOA inhibitor itaconate in impeding RB progression. Utilizing single-cell RNA sequencing, ALDOA consistently exhibits overexpression across diverse cell types, particularly in cone precursor cells, retinoma-like cells, and retinoblastoma-like cells. This heightened expression is validated in RB tissues and cell lines. ALDOA knockdown significantly diminishes RB cell viability, impedes colony formation, and induces notable metabolic alterations. RNA-seq analysis identifies SUSD2, ARHGAP27, and CLK2 as downstream genes associated with ALDOA. The application of itaconate demonstrates efficacy in inhibiting RB cell proliferation, validated through in vitro and in vivo models. This study emphasizes ALDOA as a promising target for innovative RB therapies, with potential implications for altering tumor energy metabolism.

Abstract Background Tumors exhibit metabolic heterogeneity, influencing cancer progression. However, understanding metabolic diversity in retinoblastoma (RB), the primary intraocular malignancy in children, remains limited. Methods The metabolic landscape of RB was constructed based on single-cell transcriptomic sequencing from 11 RB and 5 retina samples. Various analyses were conducted, including assessing overall metabolic activity, metabolic heterogeneity, and the correlation between hypoxia and metabolic pathways. Additionally, the expression pattern of the monocarboxylate transporter (MCT) family in different cell clusters was examined. Validation assays of MCT1 expression and function in RB cell lines were performed. The therapeutic potential of targeting MCT1 was evaluated using an orthotopic xenograft model. A cohort of 47 RB patients was analyzed to evaluate the relationship between MCT1 expression and tumor invasion. Results Distinct metabolic patterns in RB cells, notably increased glycolysis, were identified. This metabolic heterogeneity correlated closely with hypoxia. MCT1 emerged as the primary monocarboxylate transporter in RB cells. Disrupting MCT1 altered cell viability and energy metabolism. In vivo studies using the MCT1 inhibitor AZD3965 effectively suppressed RB tumor growth. Additionally, a correlation between MCT1 expression and optic nerve invasion in RB samples suggested prognostic implications. Conclusions This study enhances our understanding of RB metabolic characteristics at the single-cell level, highlighting the significance of MCT1 in RB pathogenesis. Targeting MCT1 holds promise as a therapeutic strategy for combating RB, with potential prognostic implications.

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

Abstract Multiple myeloma (MM) is a heterogenous plasma cell malignancy, for which the established prognostic models exhibit limitations in capturing the full spectrum of outcome variability. Leveraging single-cell RNA-sequencing data, we developed a novel plasma cell gene signature. We evaluated and validated the associations of the resulting plasma cell malignancy (PBM) score with disease state, progression and clinical outcomes using data from five independent myeloma studies consisting of 2115 samples (1978 MM, 65 monoclonal gammopathy of undetermined significance, 35 smoldering MM, and 37 healthy controls). Overall, a higher PBM score was significantly associated with a more advanced stage within the spectrum of plasma cell dyscrasias (all p

Tissue-resident memory T cells (TRM) are a specialized subset of long-lived memory T cells that reside in peripheral tissues. However, the impact of TRM-related immunosurveillance on the tumor-immune microenvironment (TIME) and tumor progression across various non-small-cell lung cancer (NSCLC) patient populations is yet to be elucidated. Our comprehensive analysis of multiple independent single-cell and bulk RNA-seq datasets of patient NSCLC samples generated reliable, unique TRM signatures, through which we inferred the abundance of TRM in NSCLC. We discovered that TRM abundance is consistently positively correlated with CD4+ T helper 1 cells, M1 macrophages, and resting dendritic cells in the TIME. In addition, TRM signatures are strongly associated with immune checkpoint and stimulatory genes and the prognosis of NSCLC patients. A TRM-based machine learning model to predict patient survival was validated and an 18-gene risk score was further developed to effectively stratify patients into low-risk and high-risk categories, wherein patients with high-risk scores had significantly lower overall survival than patients with low-risk. The prognostic value of the risk score was independently validated by the Cancer Genome Atlas Program (TCGA) dataset and multiple independent NSCLC patient datasets. Notably, low-risk NSCLC patients with higher TRM infiltration exhibited enhanced T-cell immunity, nature killer cell activation, and other TIME immune responses related pathways, indicating a more active immune profile benefitting from immunotherapy. However, the TRM signature revealed low TRM abundance and a lack of prognostic association among lung squamous cell carcinoma patients in contrast to adenocarcinoma, indicating that the two NSCLC subtypes are driven by distinct TIMEs. Altogether, this study provides valuable insights into the complex interactions between TRM and TIME and their impact on NSCLC patient prognosis. The development of a simplified 18-gene risk score provides a practical prognostic marker for risk stratification.

Abstract Malignant pleural mesothelioma (MPM) is a rare but lethal pleural cancer with high intratumor heterogeneity (ITH). A recent study in lung adenocarcinoma has developed a clonal gene signature (ORACLE) from multiregional transcriptomic data and demonstrated high prognostic values and reproducibility. However, such a strategy has not been tested in other types of cancer with high ITH. We aimed to identify biomarkers from multi-regional data to prognostically stratify MPM patients. We generated a multiregional RNA-seq dataset for 78 tumor samples obtained from 26 MPM patients, each with one sample collected from a superior, lateral, and inferior region of the tumor. By integrating this dataset with the Cancer Genome Atlas MPM RNA-seq data, we selected 29 prognostic genes displaying high variability across different tumors but low ITH, which named PRACME (Prognostic Risk Associated Clonal Mesothelioma Expression). We evaluated PRACME in two independent MPM datasets and demonstrated its prognostic values. Patients with high signature scores are associated with poor prognosis after adjusting established clinical factors. Interestingly, the PRACME and the ORACLE signatures defined respectively from MPM and lung adenocarcinoma cross-predict prognosis between the two cancer types. Further investigation indicated that the cross-prediction ability might be explained by the high similarity between the two cancer types in their genomic regions with copy number variation, which host many clonal genes. Overall, our clonal signature PRACME provided prognostic stratification in MPM and this study emphasized the importance of multi-regional transcriptomic data for prognostic stratification based on clonal genes.

Abstract Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.

Abstract Retinoblastoma (RB) is the most prevalent ocular tumor of childhood, and its extraocular invasion significantly increases the risk of metastasis. Nevertheless, a single-cell characterization of RB local extension has been lacking. Here, we perform single-cell RNA sequencing on four RB samples (two from intraocular and two from extraocular RB patients), and integrate public datasets of five normal retina samples, four intraocular samples, and three extraocular RB samples to characterize RB local extension at the single-cell level. A total of 128,454 qualified cells are obtained in nine major cell types. Copy number variation inference reveals chromosome 6p amplification in cells derived from extraocular RB samples. In cellular heterogeneity analysis, we identified 10, 8, and 7 cell subpopulations in cone precursor like cells, retinoma like cells, and MKI67+ photoreceptorness decreased (MKI67+ PhrD) cells, respectively. A high expression level of SOX4 was detected in cells from extraocular samples, especially in MKI67+ PhrD cells, which was verified in additional clinical RB samples. These results suggest that SOX4 might drive RB local extension. Our study presents a single-cell transcriptomic landscape of intraocular and extraocular RB samples, improving our understanding of RB local extension at the single-cell resolution and providing potential therapeutic targets for RB patients.

Abstract The Retinoic acid-Inducible Gene I (RIG-I) like receptors (RLRs) are the major viral RNA sensors essential for the initiation of antiviral immune responses. RLRs are subjected to stringent transcriptional and posttranslational regulations, of which ubiquitination is one of the most important. However, the role of ubiquitination in RLR transcription is unknown. Here, we screen 375 definite ubiquitin ligase knockout cell lines and identify Ubiquitin Protein Ligase E3 Component N-Recognin 5 (UBR5) as a positive regulator of RLR transcription. UBR5 deficiency reduces antiviral immune responses to RNA viruses, while increases viral replication in primary cells and mice. Ubr5 knockout mice are more susceptible to lethal RNA virus infection than wild type littermates. Mechanistically, UBR5 mediates the Lysine 63-linked ubiquitination of Tripartite Motif Protein 28 (TRIM28), an epigenetic repressor of RLRs. This modification prevents intramolecular SUMOylation of TRIM28, thus disengages the TRIM28-imposed brake on RLR transcription. In sum, UBR5 enables rapid upregulation of RLR expression to boost antiviral immune responses by ubiquitinating and de-SUMOylating TRIM28.

The improvement of information sciences promotes the utilization of data for process monitoring. As the core of modern automation, time-stamped signals are used to estimate the system state and construct the data-driven model. Many recent studies claimed that the effectiveness of data-driven methods relies greatly on data quality. Considering the complexity of the operating environment, process data will inevitably be affected. This poses big challenges to estimating faults from data and delivers feasible strategies for electrical systems of industry. This paper addresses the missing data problem commonly in traction systems by designing a martingale posterior-based data generation method for the state-space model. Then, a data-driven approach is proposed for fault detection and estimation via the subspace identification technique. It is a general scheme using the Bayesian framework, in which the Dirichlet process plays a crucial role. The data-driven method is applied to a pilot-scale traction motor platform. Experimental results show that the method has good estimation performance.

Background: The fate and functions of RNAs are coordinately regulated by RNA-binding proteins (RBPs), which are often dysregulated in various cancers. Known as a splicing regulator, RNA-binding motif protein 6 (RBM6) harbors tumor-suppressor activity in many cancers; however, there is a lack of research on the molecular targets and regulatory mechanisms of RBM6. Methods: In this study, we constructed an RBM6 knock-down (shRBM6) model in the HeLa cell line to investigate its functions and molecular targets. Then we applied improved RNA immunoprecipitation coupled with sequencing (iRIP-seq) and whole transcriptome sequencing approaches to investigate the potential role and RNA targets of RBM6. Results: Using The Cancer Genome Atlas dataset, we found that higher expression of RBM6 is associated with a better prognosis in many cancer types. In addition, we found that RBM6 knockdown promoted cell proliferation and inhibited apoptosis, demonstrating that RBM6 may act as an anti-oncogenic protein in cancer cells. RBM6 can regulate the alternative splicing (AS) of genes involved in DNA damage response, proliferation, and apoptosis-associated pathways. Meanwhile, RBM6 knockdown activated type I interferon signaling pathways and inhibited the expression of genes involved in the cell cycle, cellular responses to DNA damage, and DNA repair pathways. The differentially expressed genes (DEGs) by shRBM6 and their involved pathways were likely regulated by the transcription factors undergoing aberrant AS by RBM6 knockdown. For iRIP-seq analysis, we found that RBM6 could interact with a large number of mRNAs, with a tendency for binding motifs GGCGAUG and CUCU. RBM6 bound to the mRNA of cell proliferation- and apoptosis-associated genes with dysregulated AS after RBM6 knockdown. Conclusions: In summary, our study highlights the important role of RBM6, as well as the downstream targets and regulated pathways, suggesting the potential regulatory mechanisms of RBM6 in the development of cancer.

Investigating oat tissue microflora during its different developmental stages is necessary for understanding its growth and anti-disease mechanism. In this study, 16S rDNA and ITS (Internally Transcribed Spacer) high-throughput sequencing technology were used to explore the microflora diversity of oat tissue. Twenty-seven samples of leaves, stems, and roots from three developmental stages, namely the seedling stage (SS), jointing stage (JS), and maturity stage (MS), underwent sequencing analysis. The analysis showed that 6480 operational taxonomic units (OTUs) were identified in the examined samples, of which 1698 were fungal and 4782 were bacterial. Furthermore, 126 OTUs were shared by fungi, mainly Ascomycota, Basidiomycota, and Mucoromycota at the phylum level, and 39 OTUs were shared by bacteria, mainly Actinobacteriota and Proteobacteria at the phylum level. The microbial diversity of oat tissue in the three developmental stages showed differences, and the α-diversity of the bacteria and β-diversity of the bacteria and fungi in the roots were higher than those of the stems and leaves. Among the bacteria species, Thiiopseudomonas, Rikenellaceae RC9 gut group, and Brevibacterium were predominant in the leaves, MND1 was predominant in the roots, and Lactobacillus was predominant in the stems. Moreover, Brevibacterium maintained a stable state at all growth stages. In the fungal species, Phomatospora was dominant in the leaves, Kondoa was dominant in the roots, and Pyrenophora was dominant in the stems. All species with a high abundance were related to the growth process of oats and antagonistic bacteria. Furthermore, connection modules were denser in bacterial than in fungal populations. The samples were treated with superoxide dismutase and peroxidase. There were 42 strains associated with SOD (Superoxide dismutase), 60 strains associated with POD (Peroxidase), and 38 strains in total, which much higher than fungi. The network analysis showed that bacteria might have more dense connection modules than fungi, The number of bacterial connections to enzymes were much higher than that of fungi. Furthermore, these results provide a basis for further mechanistic research.

Summary: Tissue-resident memory T cells (TRM) are a specialized T cell population residing in peripheral tissues. The presence and potential impact of TRM in the tumor immune microenvironment (TIME) remain to be elucidated. Here, we systematically investigated the relationship between TRM and melanoma TIME based on multiple clinical single-cell RNA-seq datasets and developed signatures indicative of TRM infiltration. TRM infiltration is associated with longer overall survival and abundance of T cells, NK cells, M1 macrophages, and memory B cells in the TIME. A 22-gene TRM–derived risk score was further developed to effectively classify patients into low- and high-risk categories, distinguishing overall survival and immune activation, particularly in T cell-mediated responses. Altogether, our analysis suggests that TRM abundance is associated with melanoma TIME activation and patient survival, and the TRM-based machine learning model can potentially predict prognosis in melanoma patients.

AbstractThe complete mitochondrial genome of Rhinogobius maculagenys Wu et al., (Perciformes,Gobiidae) was sequenced and annotated in this study. The circular mitogenome is 16,500 bp long and consists of 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes and two main non-coding regions (a putative control region and an L-strand replication origin). The overall base composition is 27.5% A, 25.5% T, 16.9% G, and 30.1% C. The gene order and composition are similar to those of other Gobionellinae species. Phylogenetic analysis revealed that R. maculagenys is closely related to Rhinogobius shennongensis in both the maximum likelihood tree and the Bayesian inference tree. The complete mitogenome of R. maculagenys will serve as a valuable resource for future studies on evolution, taxonomy, and genetic conservation of Rhinogobius.

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

Abstract Background Anaerobic fungi are effective fibre-degrading microorganisms in the digestive tract of horses. However, our understanding of their diversity and community structure is limited, especially in different parts of the gastrointestinal tract. Results For the first time, high-throughput sequencing technology was used to analyse and predict fungal microbial diversity in different parts of the gastrointestinal tract of Mongolian horses. The results revealed that the richness and diversity of fungi in the hindgut of Mongolian horses were much higher than those in the foregut. The foregut was dominated by Basidiomycota and Ascomycota, whereas the hindgut was dominated by Neocallimastigomycota and Basidiomycota. At the genus level, the relative abundance of many pathogenic fungi (Cryptococcus, Cladosporium, Alternaria, and Sarocladium) in the foregut was significantly higher than that in the posterior gut, indicating that Mongolian horses have strong disease resistance. The prediction of fungal function also showed significant differences in the fungal flora between the foregut and the hindgut. The fungi in Mongolian horses’ foreguts were mainly pathologically nutritive and contained many animal and plant pathogens, particularly in the small intestine (jejunum and ileum). This indicates that the foregut may be the most important immune site in the digestive system of Mongolian horses, which explains the high disease resistance of Mongolian horses. The number of unassigned functional groups in the posterior gut was significantly higher than that in the anterior gut, indicating that the functions of fungal groups in the posterior gut have not been fully explored, and further studies are required in the future. Conclusions Analysis of high-throughput sequencing results revealed that the fungal composition varied greatly among different gastrointestinal tract segments in Mongolian horses, whose hindgut contains many anaerobic fungi involved in plant cellulose degradation. This provides important basic data for studying fungal diversity in the digestive system of healthy horses, which can be used for the health assessment of horses and provides clues for further research on the disease resistance and digestive capacity of horses, as well as a reference for the early diagnosis of intestinal diseases and innovative treatment methods.

Lead (Pb) is a common environmental neurotoxicant that results in abnormal neurobehavior and impaired memory. Avicularin (AVL), the main dietary flavonoid found in several plants and fruits, exhibits neuroprotective and hepatoprotective properties. In the present study, the effects of AVL on Pb-induced neurotoxicity were evaluated using ICR mice to investigate the molecular mechanisms behind its protective effects. Our study has demonstrated that AVL treatment significantly ameliorated memory impairment induced by lead (Pb). Furthermore, AVL mitigated Pb-triggered neuroinflammation, ferroptosis, and oxidative stress. The inhibition of Pb-induced oxidative stress in the brain by AVL was evidenced by the reduction in malondialdehyde (MDA) levels and the enhancement of glutathione (GSH) and glutathione peroxidase (GPx) activities. Additionally, in the context of lead-induced neurotoxicity, AVL mitigated ferroptosis by increasing the expression of GPX4 and reducing ferrous iron levels (Fe2+). AVL increased the activities of glycogenolysis rate-limiting enzymes HK, PK, and PYG. Additionally, AVL downregulated TNF-α and IL-1β expression while concurrently enhancing the activations of AMPK, Nrf2, HO-1, NQO1, PSD-95, SNAP-25, CaMKII, and CREB in the brains of mice. The findings from this study suggest that AVL mitigates the memory impairment induced by Pb, which is associated with the AMPK/Nrf2 pathway and ferroptosis.

Land intensive use reflects the spatial structure, agglomeration characteristics, and internal mechanisms of urban economic, social, and ecological system development, significantly impacting urban resilience. Based on panel data from 287 cities in China from 2010 to 2020, this paper measures the levels of land intensive use and urban resilience, and empirically examines the impact mechanism of land intensive use on urban resilience through baseline regression and panel quantile regression. The results reveal that: (1) During the study period, China’s urban land intensive use level has significantly improved. The land intensive use level shows a trend of “the strong become stronger, and the weak are always weak” and “high in the east and low in the west” spatial differentiation, while the urban resilience level showed a trend of accelerated “catching up” of low-resilience cities towards high-resilience cities and “high in the east and low in the west” spatial differentiation as well. (2) Land intensive use significantly promotes effect on urban resilience, and the effect depends on different conditions. (3) Among all dimensions of land intensive use, both land input intensity and land use benefits significantly promote urban resilience, while land use intensity shows an insignificant effect. (4) The impact of land intensive use on urban resilience demonstrates significant scale heterogeneity and geographic regional heterogeneity. Based on these findings, the paper proposes relevant policy suggestions for land intensive use aimed at improving urban resilience, offering guidance for promoting high-quality land use and sustainable urban resilience development.

The contact between a traditional crop divider and sugarcane is unstable, and the sugarcane easily slides off of its surface. By analyzing the movement process of sugarcane, the influence of traditional spiral flightings on lifting performance was studied, and shortcomings were also found. Based on previous research and analysis, the variable spiral spike-toothed crop divider was designed by research groups. For sugarcane with different lodging states, the contact separation rule between the sugarcane and the spike tooth was studied, and the action time and angle of the spike tooth on sugarcane were obtained. At the same time, the interaction mechanism between sugarcane and the spike tooth was analyzed, and the conditions for lodged canes to be lifted were obtained. The influence of the spike tooth on the lifting performance was explored, and the working advantages were found for the spike-toothed crop divider. Then, a simulation test was conducted to obtain the contact force between the sugarcane and the crop divider. Finally, the crop divider was optimized and integrated into the harvester, and a field harvesting test was carried out to verify the working performance of the crop divider. This study was expected to provide a reference for the design of crop dividers and a theoretical basis for the analysis of the lifting process.

Abstract Posttranslational modification dramatically enhances protein complexity, but the function and precise mechanism of novel lysine acylation modifications remain unknown. Chemoresistance remains a daunting challenge to successful treatment. We found that lysine butyrylation (Kbu) is specifically upregulated in chemoresistant tumor cells and tissues. By integrating butyrylome profiling and gain/loss-of-function experiments, lysine 754 in HSP90 (HSP90 K754) was identified as a substrate for Kbu. Kbu modification leads to overexpression of HSP90 in esophageal squamous cell carcinoma (ESCC) and its further increase in relapse samples. Upregulation of HSP90 contributes to 5-FU resistance and can predict poor prognosis in cancer patients. Mechanistically, HSP90 K754 is regulated by the cooperation of KAT8 and HDAC11 as the writer and eraser, respectively; SDCBP increases the Kbu level and stability of HSP90 by binding competitively to HDAC11. Furthermore, SDCBP blockade with the lead compound V020-9974 can target HSP90 K754 to overcome 5-FU resistance, constituting a potential therapeutic strategy.

Abstract Circular RNA HIPK3 (circHIPK3) mediates the progression of multiple cancers, including bladder cancer, by regulating cell migration, autophagy and epithelial mesenchymal transition. However, the mechanism by which circHIPK3 regulates autophagy in bladder cancer cells remains unclear. Autophagy is a common self-protection mechanism in eukaryotic cells and is essential for cell survival and death regulation. However, it is unclear whether circHIPK3 affects the level of autophagy in bladder cancer through binding proteins, and the potential regulatory mechanism is unknown. Here, we found that circHIPK3 levels were significantly lower and autophagy-related proteins were significantly upregulated in bladder cancer cells and tissues compared to normal controls. CircHIPK3 downregulation promoted bladder cancer cell proliferation, while circHIPK3 overexpression inhibited proliferation. CircHIPK3 overexpression significantly suppressed autophagy in bladder cancer cells. Overexpression of circHIPK3 did not affect VCP protein expression but inhibited the VCP/Beclin 1 interaction. VCP also stabilized Beclin 1 and promoted autophagy in bladder cancer cells by downregulating ataxin-3. Thus, circHIPK3 may play an important role in bladder cancer by inhibiting VCP-mediated autophagy.

Context: The incidence of urolithiasis is increasing year by year. Ureteral stents are a popular treatment option for this condition. Efforts to improve the material and structure of stents to increase comfort and reduce complications have led to the introduction of magnetic stents. Objective: To evaluate differences in removal efficiency and safety for magnetic and conventional stents. Evidence acquisition: This study was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Data were extracted according to the PRISMA principles. We collected and combined data from randomized controlled trials on magnetic versus conventional stents to evaluate the efficiency of their removal and the associated effects. Data synthesis was performed using RevMan 5.4.1 and heterogeneity was evaluated using I2 tests. A sensitivity analysis was also performed. Key metrics included the stent removal time, Visual Analog Scale (VAS) pain scores, and Ureteral Stent Symptom Questionnaire (USSQ) scores for various domains. Evidence synthesis: Seven studies were included in the review. We found that magnetic stents had a shorter removal time (mean difference [MD] −8.28 min, 95% confidence interval [CI] −15.6 to −0.95; p = 0.03) and their removal was associated with less pain (MD −3.01 points, 95% CI −3.83 to −2.19; p

Abstract To investigate the association between clonal haematopoiesis (CH) and lung cancer risk, we identified CH mutations in 1 059 lung cancer cases and 899 controls using the blood whole‐exome sequencing data generated from the Integrative Analysis of Lung Cancer Etiology and Risk project of the International Lung Cancer Consortium (INTEGRAL‐ILCCO). Based on the variant allele frequency (VAF) of these mutations, we stratified CH carriers into two groups, low VAF (1%–10%) and high VAF (≥10%), respectively. We observed a significant association between the presence of CH mutations and the risk of lung cancer after adjusting for known risk factors (odd ratio, OR = 1.37, 95% confidence interval, CI = 1.02–1.85). Such an association was largely driven by CH mutations with high‐VAF, the OR for high‐VAF CH and low‐VAF CH were 2.54 (1.38–4.93) and 1.14 (0.82–1.6), respectively. Trend analysis indicated a significant dose–response relationship (P trend = 0.004). This association between high‐VAF CH and lung cancer risk remained consistent when subjects were stratified by risk factors or lung cancer histological subtypes. A combination of results from INTEGRAL‐ILCCO, UKBB, and MGBB cohorts resulted in a meta‐analysed OR of 1.36 (95% CI = 1.14–1.62) for all CH carriers and of 1.76 (95% CI = 1.34–2.31) for high‐VAF CH carriers, respectively. In conclusion, our analysis revealed a significant association between CH and increased risk of lung cancer as supported by three independent cohorts.

ABSTRACTRuminal microbiota is gradually established after birth, while microbiota maturation could be highly diverse because of varied solid dietary accessibility. However, how the ruminal microbiota accreted from postnatal hay diets alters rumen epithelial development, and how this affects animal health remains largely unknown. Here, neonatal lambs were introduced to starchy corn-soybean starter or corn-soybean starter + alfalfa hay (AH) to investigate the influences of early life ruminal microbiome on rumen epithelial development using integrated 16s rRNA sequencing-metagenome-transcriptome approaches. The results showed that AH introduction elevated average daily weight gain, rumen weight and volume, rumen epithelial papillae length, and rumen muscle layer thickness. Meanwhile, the relative abundance of fibrolytic bacteria (Christensenellaceae R-7 group, Prevotellaceae UCG-001, and Succinivibrio), acetate producer (Acetitomaculum and Mitsuokella), and propionate producer Succiniclasticum was increased in the rumen content by AH supplementation (P < 0.05). Moreover, AH introduction decreased the relative abundance of total CAZymes, CBM, and GH and increased the abundance of KO genes related to volatile fatty acid (VFA) generation in the rumen content. AH lambs had a higher relative abundance of Succiniclasticum, Megasphaera, Succinivibrio, and Suttonella (P < 0.05), while a lower relative abundance of Cloacibacillus, Desulfovibrio, Dialister, Intestinimonas, Parabacteroides, and Pseudoscardovia (P < 0.05) in the rumen epithelial samples. Furthermore, these alterations in ruminal microbial structure and function resulted in ruminal epithelial cell proliferation and development pathways activation. In summary, AH introduction benefited ruminal fiber degradation and VFA generation bacteria colonization and promoted ruminal epithelial development. These findings provide new insights into ruminal microbial–host interactions in the early life.IMPORTANCEWhile it is established that a fiber-rich diet promotes rumen development in lambs, further research is needed to investigate the precise response of rumen microbiota and epithelium to high-quality alfalfa hay. Here, we observed that the inclusion of alfalfa hay led to a discernible alteration in the developmental trajectory of the rumen. Notably, there was a favorable shift in the rumen's volume, morphology, and the development of rumen papillae. Furthermore, ruminal microbial structure and function resulted in ruminal epithelial cell proliferation and development pathways activation, collectively provide compelling evidence supporting the capacity of alfalfa hay to enhance rumen development and health through ruminal micrbiota-host crosstalks. Our findings elucidate the functional response of the rumen to alfalfa hay introduction, providing new insights into strategies for promoting healthy development of the rumen in young ruminants.

The myosin heavy chain 9 (MYH9) gene encodes the heavy chain of non-muscle myosin IIA (NMIIA), which belongs to the myosin II subfamily of actin-based molecular motors. Previous studies have demonstrated that abnormal expression and mutations of MYH9 were correlated with MYH9-related diseases and tumors. Furthermore, earlier investigations identified MYH9 as a tumor suppressor. However, subsequent research revealed that MYH9 promoted tumorigenesis, progression and chemoradiotherapy resistance. Note-worthily, MYH9 has also been linked to viral infections, like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Epstein-Barr virus, and hepatitis B virus, as a receptor or co-receptor. In addition, MYH9 promotes the development of hepatocellular carcinoma by interacting with the hepatitis B virus-encoding X protein. Finally, various findings highlighted the role of MYH9 in the development of these illnesses, especially in tumors. This review summarizes the involvement of the MYH9-regulated signaling network in tumors and virus-related diseases and presents possible drug interventions on MYH9, providing insights for the use of MYH9 as a therapeutic target for tumors and virus-mediated diseases.

Summary: Exploring the clinical relevance of diverse immune cell types within the tumor microenvironment is pivotal for unraveling cancer intricacies and developing treatments. Here, we present a protocol for using tumor immune microenvironment illustration based on gene pairs, an R package to deduce cell-cell interactions, unveiling the association between immune cell relative abundance and patient prognoses from bulk gene expression and survival data. We describe steps for harnessing cell-type markers derived from single-cell RNA sequencing data to map the tumor immune microenvironment across a spectrum of cancer types.For complete details on the use and execution of this protocol, please refer to Li et al. (2023).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Acute kidney injury is common among hospitalized individuals, particularly those exposed to certain medications, and is associated with substantial morbidity and mortality. In a pragmatic, open-label, National Institutes of Health-funded, parallel group randomized controlled trial (clinicaltrials.gov NCT02771977), we investigate whether an automated clinical decision support system affects discontinuation rates of potentially nephrotoxic medications and improves outcomes in patients with AKI. Participants included 5060 hospitalized adults with AKI and an active order for any of three classes of medications of interest: non-steroidal anti-inflammatory drugs, renin-angiotensin-aldosterone system inhibitors, or proton pump inhibitors. Within 24 hours of randomization, a medication of interest was discontinued in 61.1% of the alert group versus 55.9% of the usual care group (relative risk 1.08, 1.04 – 1.14, p = 0.0003). The primary outcome – a composite of progression of acute kidney injury, dialysis, or death within 14 days - occurred in 585 (23.1%) of individuals in the alert group and 639 (25.3%) of patients in the usual care group (RR 0.92, 0.83 – 1.01, p = 0.09). Trial Registration Clinicaltrials.gov NCT02771977.

Abstract Stage III non‐small cell lung cancer (NSCLC) encompasses a group of diseases with high heterogeneity. Such patients should actively receive comprehensive treatments. It is imperative for all stage III NSCLC patients to receive consultation with a multiple disciplinary team, which allows the development of a proposal for clinical diagnosis and treatment. In this consensus, stage III NSCLC is divided into two types (operable and inoperable) according to different clinical conditions. Resectable NSCLC is further subdivided into two conditions (with or without driver genes). For each clinical scenario, this consensus emphasizes that the foundation of any medical decisions regarding the optimal diagnostic or therapy procedure is scientific evidence from clinical research. Finally, based on the level of evidence and strength of recommendations, this consensus provides recommendations for the management of stage III NSCLC from six perspectives. The objective of this consensus is to help clinicians choose the best treatment and promote the standardization of stage III NSCLC diagnosis and treatment in China.

Abstract Despite mitochondrial DNA (mtDNA) mutations are common events in cancer, their global frequency and clinical impact have not been comprehensively characterized in patients with myelodysplastic neoplasia (also known as myelodysplastic syndromes, MDS). Here we performed whole-genome sequencing (WGS) on samples obtained before allogenic hematopoietic cell transplantation (allo-HCT) from 494 patients with MDS who were enrolled in the Center for International Blood and Marrow Transplant Research. We evaluated the impact of mtDNA mutations on transplantation outcomes, including overall survival (OS), relapse, relapse-free survival (RFS), and transplant-related mortality (TRM). A random survival forest algorithm was applied to evaluate the prognostic performance of models that include mtDNA mutations alone and combined with MDS- and HCT-related clinical factors. A total of 2666 mtDNA mutations were identified, including 411 potential pathogenic variants. We found that overall, an increased number of mtDNA mutations was associated with inferior transplantation outcomes. Mutations in several frequently mutated mtDNA genes (e.g., MT-CYB and MT-ND5) were identified as independent predictors of OS, RFS, relapse and/or TRM after allo-HCT. Integration of mtDNA mutations into the models based on the Revised International Prognostic Scores (IPSS-R) and clinical factors related to MDS and allo-HCT could capture more prognostic information and significantly improve the prognostic stratification efforts. Our study represents the first WGS effort in MDS receiving allo-HCT and shows that there may be clinical utility of mtDNA variants to predict allo-HCT outcomes in combination with more standard clinical parameters.

Abstract Background Immune checkpoint proteins play critical functions during the immune response to cancer and have been targeted by immune checkpoint blockade therapy. V‐domain Ig suppressor of T cell activation (VSIR) is one of these immune checkpoint genes and has been investigated extensively in recent years due to its conflicting roles in cancer immunity. Specifically, in acute myeloid leukemia (AML), the prognostic value of VSIR is debated. Results In both patient tumor samples and cancer cell lines we find that VSIR has the highest expression in AML out of all cancer types and, in AML, has the highest expression out of all other immune checkpoint genes. Survival analysis indicated that AML patients with higher VSIR expression have significantly shorter survival than those patients with lower expression, even within established AML subgroups (e.g., FAB subtypes). Importantly, VSIR expression is predictive of progression from myelodysplastic syndromes (MDS) patients into AML, suggesting its potential role during the very early stage of AML development and progression. In addition to AML, VSIR also demonstrates prognostic values in other cancer types, including multiple myeloma and mesothelioma. Conclusion In summary, our analyses revealed the prognostic value of VSIR and its potential as a target for immunotherapy, especially in AML.

The physical characteristics of chyme during gastrointestinal digestion are considered to significantly affect nutrient digestion and absorption (such as glucose diffusion), which has an impact on postprandial satiety. The present study aims to analyze the hydration rate (HR) and rheological properties of deacetylated konjac glucomannan (DKGM) at different degrees and then explore their effects on rice texture, digestive properties, and the subjects’ post-meal appetite. The present results show that, as the deacetylation degree (DD) of KGM increased, the intersection point of the viscoelastic modulus shifted to a high shear rate frequency, and as the swelling time of the DKGM was prolonged, its HR decreased significantly. The results of the in vitro gastrointestinal digestion tests show that the hardness and chewability of the rice in the fast-hydration group (MK1) were remarkably reduced. In contrast, the slow-hydration group (MK5) exhibited an outstanding ability to resist digestion. The kinetics of starch hydrolysis revealed that the HR of the rice in the fast-hydration group was 1.8 times faster than that of the slow-hydration group. Moreover, it was found that the subjects’ appetite after the meal was highly related to the HR of the MK. Their hunger (p < 0.001), desire to eat (p < 0.001), and prospective food consumption (p < 0.001) were significantly inhibited in the slow-hydration group (MK5) compared to the control. This study explored the nutritional effects of the hydration properties derived from the DKGM, which may contribute to modifying the high glycemic index food and provide ideas for the fabrication of food with enhanced satiating capacity.

Abstract Early diagnosis of gastrointestinal malignancies in patients with acute coronary syndrome (ACS) is often delayed. The present study aims to demonstrate the value of [68Ga]Ga‐FAPI‐04 PET imaging in ACS with suspected gastrointestinal malignancies. Twelve ACS patients with suspected gastrointestinal malignancies were enrolled, including ST‐elevation myocardial infarction (STEMI) (n = 5), non‐ST‐elevation myocardial infarction (NSTEMI) (n = 5), and unstable angina (UA) (n = 2). All patients underwent coronary angiography (CAG) and [68Ga]Ga‐FAPI‐04 PET/MR or PET/CT within 1 week. All five STEMI and five NSTEMI patients had high [68Ga]Ga‐FAPI‐04 uptake in the injured myocardium compared to remote area (TBR: 2.10 ± 0.72 vs. 0.62 ± 013; p < .001), correlated with peak cTnI level (R = .82, p = .004). No [68Ga]Ga‐FAPI‐04 in the myocardium was found in UA patients. NSTEMI displayed a similar myocardial [68Ga]Ga‐FAPI‐04 intensity as STEMI (p = .42). Compared with STEMI, NSTEMI patients had a significantly delayed door‐to‐balloon time for reperfusion treatment (p = .023). High uptake of [68Ga]Ga‐FAPI‐04 in the gastrointestinal tract was detected in three patients. Because of no myocardial [68Ga]Ga‐FAPI‐04 expression, they discontinued antiplatelet therapy and underwent endoscopy. The rectal, colon, and gastric cancer diagnoses were made by biopsy. The other nine patients showed no accumulation of [68Ga]Ga‐FAPI‐04 beyond the heart, and invasive tumor examinations were delayed. During a median 6‐month follow‐up, no tumor formation was observed. [68Ga]Ga‐FAPI‐04 PET imaging is valuable to assess injured myocardium, detect tumors, and guide invasive examinations in ACS patients with suspected gastrointestinal malignancies.

Abstract Angiotensin converting enzyme 2 (ACE2) played a critical role in regulating renin‐angiotensin‐aldosterone system (RAAS). In this research, 68Ga‐cyc‐DX600 was synthesized as PET tracer of ACE2 imaging. ACE2 positron emission tomography/magnetic resonance (PET/MR) was preliminary administered on twelve healthy volunteers, and the images were normalized and registered to establish the standard model of ACE2 PET. In diseased conditions, 68Ga‐cyc‐DX600 PET and 18F‐FDG PET were compared for COVID‐19 (one in acute phase and three in post‐COVID), anemia (n = 1) and malignancies (n = 2) to evaluate the diagnostic efficiency. 68Ga‐cyc‐DX600 PET was of a definite ACE2 dependence. For the tracer uptake of ACE2 PET/MR of female and male, differences existed in salivary glands, upper respiratory tract and kidneys, meanwhile, age, and body mass index (BMI) were also the confounding factors. RAAS‐related tissue and organs were of the relatively higher tracer uptake, such as SUVmean of cardiac chamber (3.786 ± 1.495), liver (5.342 ± 2.267), spleen (4.465 ± 2.508), and kidney (4.906 ± 1.619 for female and 8.431 ± 5.179 for male). For COVID‐19, ACE2 PET revealed ACE2 fluctuations, particularly in the susceptible organs, including liver, spleen and testis. In the case of anemia, the activated local RAS in the bone marrow was of diffuse high tracer uptake. ACE2 PET of malignancies added supplementary information to FDG PET. 68Ga‐cyc‐DX600‐based ACE2 PET models were established for visually monitoring of whole‐body ACE2 expression. The feasibility of ACE2 PET in supervising disease was primarily proved in COVID‐19, anemia and malignancies as providing a comprehensive view on the disease process and functional recovery.

Summary: Image-based AI has thrived as a potentially revolutionary tool for predicting molecular biomarker statuses, which aids in categorizing patients for appropriate medical treatments. However, many methods using hematoxylin and eosin-stained (H&E) whole-slide images (WSIs) have been found to be inefficient because of the presence of numerous uninformative or irrelevant image patches. In this study, we introduced the region of biomarker relevance (ROB) concept to identify the morphological areas most closely associated with biomarkers for accurate status prediction. We actualized this concept within a framework called saliency ROB search (SRS) to enable efficient and effective predictions. By evaluating various lung adenocarcinoma (LUAD) biomarkers, we showcased the superior performance of SRS compared to current state-of-the-art AI approaches. These findings suggest that AI tools, built on the ROB concept, can achieve enhanced molecular biomarker prediction accuracy from pathological images.

Virtual reality (VR) technology has been increasingly employed in human-robot interaction (HRI) research to enhance the immersion and realism of the interaction. However, the integration of VR into HRI also introduces new challenges, such as latency, mismatch between virtual and real environments and potential adverse effects on human users. Despite these challenges, the use of VR in HRI has the potential to provide numerous benefits, including improved communication, increased safety and enhanced training and education. Yet, little research has been done by scholars to review the state of the art of VR applications in human-robot interaction. To bridge the gap, this paper provides an overview of the challenges and benefits of using VR in HRI, as well as current research in the field and future directions for development. It has been found that robots are getting more personalized, interactive and engaging than ever; and with the popularization of virtual reality innovations, we might be able to foresee the wide adoption of VR in controlling robots to fulfill various tasks of hospitals, schools and factories. Still, there are several challenges, such as the need for more advanced VR technologies to provide more realistic and immersive experiences, the development of more human-like robot models to improve social interactions and the need for better methods of evaluating the effectiveness of VR in human-robot interaction.

Published data were gathered for a meta-analysis to determine the difference in sperm parameters before and after administration of different types of coronavirus disease 2019 (COVID-19) vaccines, because the reproductive toxicity of COVID-19 vaccines has not yet been evaluated in clinical trials and COVID-19 has been associated with decreases in sperm quality. The preferred procedures for systematic reviews and meta-analyses were followed in the conduct and reporting of this study. The average sperm parameters of all sperm donors' multiple sperm donations were compared before and after receiving various COVID-19 vaccinations. Semen volume, total sperm motility, total sperm count, morphological change, and sperm concentration were the primary outcome measures. We compiled and analyzed the results of six studies on total sperm motility, six studies on semen volume, six studies on sperm concentration, two studies on morphological change, and two studies on total sperm count. Parameter comparisons with patients who had and had not been vaccinated were only reported in one of the included studies. When different types of COVID-19 vaccine injections were compared, no discernible differences in parameters were observed. According to the available data, the parameters of semen are unaffected by inactivated or messenger RNA (mRNA) COVID-19 vaccinations. To support these findings, additional prospectively designed research is required.

Intelligent manufacturing (IM), sometimes referred to as smart manufacturing (SM), is the use of real-time data analysis, machine learning, and artificial intelligence (AI) in the production process to achieve the aforementioned efficiencies. Human-machine interaction technology has recently been a hot issue in smart manufacturing. The unique interactivity of virtual reality (VR) innovations makes it possible to create a virtual world and allow users to communicate with that environment, providing users with an interface to be immersed in the digital world of the smart factory. And virtual reality technology aims to stimulate the imagination and creativity of creators to the maximum extent possible for reconstructing the natural world in a virtual environment, generating new emotions, and transcending time and space in the familiar and unfamiliar virtual world. Recent years have seen a great leap in the development of intelligent manufacturing and virtual reality technologies, yet little research has been done to combine the two popular trends. To fill this gap, this paper specifically employs Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to conduct a systematic review of the applications of virtual reality in smart manufacturing. Moreover, the practical challenges and the possible future direction will also be covered.

This paper presents a novel teleoperation system using Electroencephalogram (EEG) to control the motion of a wheeled mobile robot (WMR). Different from the other traditional motion controlling method, the WMR is braked with the EEG classification results. Furthermore, the EEG will be induced by using the online BMI (Brain Machine Interface) system, and adopting the non-intrusion induced mode SSVEP (steady state visually evoked potentials). Then, user's motion intention can be recognized by canonical correlation analysis (CCA) classifier, which will be converted into motion commands of the WMR. Finally, the teleoperation technique is utilized to manage the information of the movement scene and adjust the control instructions based on the real-time information. Bezier curve is used to parameterize the path planning of the robot, and the trajectory can be adjusted in real time by EEG recognition results. A motion controller based on error model is proposed to track the planned trajectory by using velocity feedback control, providing excellent track tracking performance. Finally, the feasibility and performance of the proposed teleoperation brain-controlled WMR system are verified using demonstration experiments.