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Objective Contrast-enhanced computed tomography (CECT) improves lesion contrast with surrounding tissues through the injection of contrast agents. This enhancement allows for more precise lesion characterization, aiding in the early diagnosis of clear cell renal cell carcinoma (ccRCC). This meta-analysis aims to assess the diagnostic efficacy of CECT in ccRCC and to provide an ideal imaging examination method for the preoperative diagnosis of ccRCC. Methods We conducted a comprehensive search across six major online databases: PubMed, Web of Science, Cochrane Library, WANFANG DATA, China National Knowledge Infrastructure, and Chinese BioMedical Literature Database (CBM). The objective was to collate and analyze studies that evaluate the diagnostic utility of CECT in the identification of ccRCC. Meta-disc 1.4 and Stata 16.0 were used to conduct a meta-analysis and evaluate the diagnostic accuracy of CECT for ccRCC. Results The meta-analysis included 17 relevant studies investigating the diagnostic value of CECT for ccRCC. The combined sensitivity and specificity of CECT were 0.88 (95% confidence interval: 0.83–0.91) and 0.82 (95%CI: 0.75–0.87), respectively. Positive diagnostic likelihood ratio = 4.87 (95%CI: 3.47–6.84), negative diagnostic likelihood ratio = 0.15 (95%CI: 0.11–0.21), and diagnostic odds ratio = 32.67 (95%CI: 18.21–58.61). In addition, the area under the ROC curve was 0.92 (95%CI: 0.89–0.94), indicating that CECT has a decent discriminative ability in diagnosing ccRCC. Conclusions CECT is recognized as a highly effective imaging tool for diagnosing ccRCC. It provides valuable guidance in the preoperative assessment and planning of surgical strategies for patients with ccRCC.

Notification systems that convey urgency without adding cognitive burden are crucial in human–computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing desirable levels of urgency depending on the application. High-risk applications require an evaluation of the urgency level elicited during critical notifications. Traditional evaluations of perceived urgency rely on subjective self-reporting and performance metrics, which, while useful, are not real-time and can be distracting from the task at hand. In contrast, EEG technology offers a direct, non-intrusive method of assessing the user’s cognitive state. Leveraging deep learning, this study introduces a novel approach to evaluate perceived urgency from single-trial EEG data, induced by vibration stimuli on the upper body, utilizing our newly collected urgency-via-vibration dataset. The proposed model combines a 2D convolutional neural network with a temporal convolutional network to capture spatial and temporal EEG features, outperforming several established EEG models. The proposed model achieves an average classification accuracy of 83% through leave-one-subject-out cross-validation across three urgency classes (not urgent, urgent, and very urgent) from a single trial of EEG data. Furthermore, explainability analysis showed that the prefrontal brain region, followed by the central brain region, are the most influential in predicting the urgency level. A follow-up neural statistical analysis revealed an increase in event-related synchronization (ERS) in the theta frequency band (4–7 Hz) with the increased level of urgency, which is associated with high arousal and attention in the neuroscience literature. A limitation of this study is that the proposed model’s performance was tested only the urgency-via-vibration dataset, which may affect the generalizability of the findings.

The anti-tumor function of T cells in the ovarian cancer (OC) microenvironment influences the prognosis of OC. Previous studies have indicated that metabolic competition among microenvironmental cells regulates the function of immune cells. Recent research has shown that NAD + metabolism plays a significant role in modulating immune cell activity, and increasing NAD + levels is a promising therapeutic strategy to enhance the effector functions of immune cells. However, the regulatory mechanisms of NAD + metabolism on the anti-tumor function of T cells in the OC microenvironment remain unclear. This study found that exogenous supplementation of NAM to increase NAD + levels in T cells significantly activates the endogenous p-STING axis and downstream interferon signaling within T cells, thereby enhancing T cell activation and anti-tumor effects. Concurrently, we discovered that elevated NAD + levels promote the retention of STING on the Golgi apparatus. Mechanistically, we elucidated that the increase in NAD + levels mediated by NAM downregulates the expression of SURF4 protein through ubiquitination and degradation, subsequently activating the p-STING axis in T cells. Furthermore, exogenous NAM supplementation can further enhance the activation of the T cell STING axis by PARP inhibitor (PARPi)-treated OC cells, and the combination of PARPi and NAM significantly augments the anti-tumor function of T cells, inhibiting the progression of OC. Our findings provide a molecular basis for the regulation of T cell anti-tumor function by NAD + , highlighting the potential strategy of targeting T cell metabolic reprogramming for the treatment of OC.

The red imported fire ant (Solenopsis invicta) is a dangerous invasive insect. These ants rely on releasing an alarm pheromone, mainly composed of 2-ethyl-3,6-dimethylptrazine (EDMP), to warn nestmates of danger and trigger group defense or escape behaviors. This study found two NPC2 proteins in the ant antennae: SinvNPC2a and SinvNPC2b. SinvNPC2a was highly expressed in the antennae; phylogenetic analysis also suggests that SinvNPC2 likely possesses conserved olfactory recognition functions. By knocking down the SinvNPC2a gene, we found that the electrophysiological response of ant antennae to EDMP became weaker. More importantly, ants lacking SinvNPC2a showed significantly reduced movement range and speed when exposed to EDMP, compared to normal ants not treated with RNAi. These ants did not spread out quickly. Furthermore, tests showed that the purified SinvNPC2a protein could directly bind to EDMP molecules. Computer modeling also showed that they fit together tightly. These findings provide direct evidence that the SinvNPC2a protein plays a key role in helping fire ants detect the EDMP alarm pheromone. It enables the ants to sense this chemical signal, allowing ant colonies to respond quickly. Understanding this mechanism improves our knowledge of how insects smell things. It also suggests a potential molecular target for developing new methods to control fire ants, such as using RNAi to block its function.

Background The heterogeneity of sepsis poses challenges for the individualized treatment of vasoactive drugs. Methods This study used data from ICUs in MIMIC-IV (2008–2019) and eICU (2014–2015) databases, identified sepsis by sepsis-3 criteria, and stratified sepsis into phenotypes by consensus K-means. The norepinephrine equivalence (NEE) formula balance treatment of different vasoactive drugs, with NEE captured hourly for up to 72 h to record both time of use and dosage. The logistic regression model, including phenotype–dosage–time interactions, examined heterogeneous treatment effects on hospital mortality. To address confounding, three models were fitted: Model 1 unadjusted, Model 2 adjusted for age and sex, and Model 3 additionally included 7 clinical variables identified via machine learning and directed acyclic graph. Nonlinear dosage was further analyzed based on restricted cubic splines. P values and P for interaction were Bonferroni-adjusted. Results A total of 54,673 sepsis patients were included for phenotype identification, and 8,803 patients were further analyzed to evaluate heterogeneous treatment effect of vasoactive drugs. Four sepsis phenotypes were identified: A, B, C and D. Phenotype D was the most severe subgroup, followed by phenotype C, while phenotypes A and B were mild subgroups. In Model 3, each 0.05 μg/kg/min increase in NEE dosage was linked to higher hospital mortality (OR 1.328, 95% CI 1.314–1.342; p  < 0.001). Longer NEE time of use also significantly increased mortality risk (OR 1.006, 95% CI 1.005–1.007; p  < 0.001). In addition, these associations varied significantly by phenotype ( P for interaction < 0.001). In RCS model, phenotype A consistently showed higher mortality than the other phenotypes at NEE dosages of 0.1–0.5 µg/kg/min, with this gap increasing over time, showing a clear dosage–time dependence. Phenotype B displayed lower overall mortality but the steepest relative risk of hospital mortality increased as dosage and time (OR of dosage: 1.309; OR of time: 1.005) in Model 3. Phenotype C reached the highest mortality risk when dosages exceeded 0.5 µg/kg/min, which was dosage dependence. Finally, phenotype D followed a U-shaped curve in RCS model, and minimum mortality was around 20% at 0.03–0.05 µg/kg/min. Conclusions Sepsis phenotypes differ significantly in their treatment effects of vasoactive drug dosage and time of use, indicating the need for phenotype-specific treatment strategies to improve outcomes.

Insects have highly developed olfactory systems in which cytochrome P450s (CYPs) were involved as odor-degrading enzymes throughout the olfactory recognition of odor compounds by insects to avoid continuous stimulation of signaling molecules and thus damage to the olfactory nervous. To understand whether the highly expressed CYPs in the antennae play an olfactory function in Solenopsis invicta worker, in this study, we find six highly expressed antennal CYPs from the transcriptome of S. invicta. Multiple sequence alignment and phylogenetic analysis divided them into two families: the CYP3 family (SinvCYP6K1, SinvCYP6K1-1) and the CYP4 family (SinvCYP4C1, SinvCYP4C1-1, SinvCYP4C1-2, SinvCYP4V2). The expression patterns of these six CYPs were analyzed by RT-qPCR, which revealed that SinvCYP6K1 and SinvCYP4V2 were only highly expressed in the antennae of adult workers. The expression of SinvCYP6K1 and SinvCYP4V2 in workers was markedly diminished after feeding with dsRNA. The electroantennography (EAG) assay demonstrated that the silencing of either SinvCYP6K1 or SinvCYP4V2 resulted in a notable reduction in the EAG response of workers to 2-ethyl-3,6(5)-dimethylpyrazine (EDMP). Furthermore, the trajectory behavior assay showed that the worker’s range and speed of movement in response to EDMP significant decreased after the silencing of SinvCYP6K1 and SinvCYP4V2. The findings indicated that both SinvCYP6K1 and SinvCYP4V2 were implicated in the recognition of EDMP by S. invicta.

Drought is a major environmental constraint that causes substantial reductions in plant growth and yield. Expression of stress-related genes is largely regulated by transcription factors (TFs), including in soybean [ Glycine max (L.) Merr.]. In this study, 301 GmAP2/ERF genes that encode TFs were identified in the soybean genome. The TFs were divided into five categories according to their homology. Results of previous studies were then used to select the target gene GmAP2/ERF144 from among those up-regulated by drought and salt stress in the transcriptome. According to respective tissue expression analysis and subcellular determination, the gene was highly expressed in leaves and encoded a nuclear-localized protein. To validate the function of GmAP2/ERF144 , the gene was overexpressed in soybean using Agrobacterium -mediated transformation. Compared with wild-type soybean, drought resistance of overexpression lines increased significantly. Under drought treatment, leaf relative water content was significantly higher in overexpressed lines than in the wild-type genotype, whereas malondialdehyde content and electrical conductivity were significantly lower than those in the wild type. Thus, drought resistance of transgenic soybean increased with overexpression of GmAP2/ERF144 . To understand overall function of the gene, network analysis was used to predict the genes that interacted with GmAP2/ERF144 . Reverse-transcription quantitative PCR showed that expression of those interacting genes in two transgenic lines was 3 to 30 times higher than that in the wild type. Therefore, GmAP2/ERF144 likely interacted with those genes; however, that conclusion needs to be verified in further specific experiments.

For small target objects on fast-moving conveyor belts, traditional vision detection algorithms equipped with conventional robotic arms struggle to capture the long and short-range pixel dependencies crucial for accurate detection. This leads to high miss rates and low precision. In this study, we integrate the traditional EMA (efficient multi-scale attention) algorithm with the c2f (channel-to-pixel) module from the original YOLOv8, alongside a Faster-Net module designed based on partial convolution concepts. This fusion results in the Faster-EMA-Net module, which greatly enhances the ability of the algorithm and robotic technologies to extract pixel dependencies for small targets, and improves perception of dynamic small target objects. Furthermore, by incorporating a small target semantic information enhancement layer into the multiscale feature fusion network, we aim to extract more expressive features for small targets, thereby boosting detection accuracy. We also address issues with training time and subpar performance on small targets in the original YOLOv8 algorithm by improving the loss function. Through experiments, we demonstrate that our attention-based visual detection algorithm effectively enhances accuracy and recall rates for fast-moving small targets, meeting the demands of real industrial scenarios. Our approach to target detection using industrial robotic arms is both practical and cutting-edge.

Background This study aimed to investigate the underlying molecular mechanisms of TRIM58 in the development of colorectal cancer (CRC). CRC is one of the most common cancers of the digestive tract worldwide. The ubiquitin–proteasome system regulates many oncogenic or tumor-suppressive proteins. TRIM58, an E3 ubiquitin ligase and a member of the tripartite motif protein family, is a potential prognostic marker that indicates poor prognosis in cancer. Currently, the precise molecular mechanisms for the TRIM58-mediated CRC progression remain unclear. Methods To examine the effects of TRIM58 on cell viability, cell cycle progression, and apoptosis in CRC, Cell Counting Kit-8 and flow cytometry assays were employed. The AKT inhibitor LY294002 was used to examine the effects of AKT signaling on TRIM58-mediated cell viability, cell cycle progression, and apoptosis in CRC. Additionally, Co-IP and ubiquitination assays were used to examine the correlation between TRIM58 and RECQL4. Results TRIM58 overexpression inhibited CRC cell viability and promoted cell cycle arrest and apoptosis, in which the TRIM58 knockdown demonstrated inversed effects via the AKT signaling pathway. TRIM58 inhibited RECQL4 protein levels through its ubiquitin ligase activity, and RECQL4 overexpression inhibited TRIM58 overexpression-mediated CRC cell viability, cell cycle progression, and apoptosis. The downregulation of TRIM58 and upregulation of RECOL4 were observed in human CRC tissue, and TRIM58 demonstrated antitumor effects in CRC-induced tumor growth in a mouse model. Conclusions TRIM58 acts as a tumor suppressor in CRC through the promotion of RECQL4 ubiquitination and inhibition of the AKT signaling pathway and may be investigated for the successful treatment of CRC.

Tumor microenvironment (TME) is emerging as an essential part of cervical cancer (CC) tumorigenesis and development, becoming a hotspot of research these years. However, comprehending the specific composition of TME is still facing enormous challenges, especially the immune and stromal components. In this study, we downloaded the RNA-seq profiles and somatic mutation data of 309 CC cases from The Cancer Genome Atlas (TCGA) database, which were analyzed by integrative bioinformatical methods. Initially, ESTIMATE computational method was employed to calculate the amount of immune and stromal components. Then, based on the high- and low-immunity cohorts, we recognized the differentially expressed genes (DEGs) as well as the differentially mutated genes (DMGs). Additionally, we conducted an intersection analysis of DEGs and DMGs, ultimately determining an immune-related prognostic signature, GTPase, IMAP Family Member 4 (GIMAP4). Moreover, sequential analyses demonstrated that GIMAP4 was a protective factor in CC, positively correlated with the overall survival (OS) and negatively with distant metastasis. Besides, we utilized the Gene Set Enrichment Analysis (GSEA) to explore the enrichment-pathways in high and low-expression cohorts of GIMAP4. The results indicated that the genes of the high-expression cohort had a high enrichment in immune-related biological processes and metabolic activities in the low one. Furthermore, CIBERSORT analysis was applied to evaluate the proportion of tumor-infiltrating immune cells (TICs), illustrating that several activated TICs were strongly associated with GIMAP4 expression, which suggested that GIMAP4 had the potential to be an indicator for the immune state in TME of CC. Hence, GIMAP4 contributed to predicting the CC patients’ clinical outcomes, such as survival rate, distant metastasis and immunotherapy response. Moreover, GIMAP4 could serve as a promising biomarker for TME remodeling, suggesting the possible underlying mechanisms of tumorigenesis and CC progression, which may provide different therapeutic perceptions of CC, and therefore improve treatment.