Unique features of conventional and nonconventional introns in Euglena gracilis.

BACKGROUND: Nuclear introns in Euglenida have been understudied. This study aimed to investigate nuclear introns in Euglenida by identifying a large number of introns in Euglena gracilis (E. gracilis), including cis-spliced conventional and nonconventional introns, as well as trans-spliced outrons. We also examined the sequence characteristics of these introns. RESULTS: A total of 28,337 introns and 11,921 outrons were identified. Conventional and nonconventional introns have distinct splice site features; the former harbour canonical GT/C-AG splice sites, whereas the latter are capable of forming structured motifs with their terminal sequences. We observed that short introns had a preference for canonical GT-AG introns. Notably, conventional introns and outrons in E. gracilis exhibited a distinct cytidine-rich polypyrimidine tract, in contrast to the thymidine-rich tracts observed in other organisms. Furthermore, the SL-RNAs in E. gracilis, as well as in other trans-splicing species, can form a recently discovered motif called the extended U6/5' ss duplex with the respective U6s. We also describe a novel type of alternative splicing pattern in E. gracilis. The tandem repeat sequences of introns in this protist were determined, and their contents were comparable to those in humans. CONCLUSIONS: Our findings highlight the unique features of E. gracilis introns and provide insights into the splicing mechanism of these introns, as well as the genomics and evolution of Euglenida.

Detection of circulating tumor DNA in plasma of patients with primary CNS lymphoma by digital droplet PCR.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) are rare mature B-cell lymphoproliferative diseases characterized by a high incidence of MYD88 L265P and CD79B Y196 hotspot mutations. Diagnosis of PCNSL can be challenging. The aim of the study was to analyze the detection rate of the MYD88 L265P and CD79B Y196 mutation in cell free DNA (cfDNA) in plasma of patients with PCNSL. METHODS: We analyzed by digital droplet PCR (ddPCR) to determine presence of the MYD88 L265P and CD79B Y196 hotspot mutations in cfDNA isolated from plasma of 24 PCNSL patients with active disease. Corresponding tumor samples were available for 14 cases. Based on the false positive rate observed in 8 healthy control samples, a stringent cut-off for the MYD88 L265P and CD79B Y196 mutation were set at 0.3% and 0.5%, respectively. RESULTS: MYD88 L265P and CD79B Y196 mutations were detected in 9/14 (64%) and 2/13 (15%) tumor biopsies, respectively. In cfDNA samples, the MYD88 L265P mutation was detected in 3/24 (12.5%), while the CD79B Y196 mutation was not detected in any of the 23 tested cfDNA samples. Overall, MYD88 L265P and/or CD79B Y196 were detected in cfDNA in 3/24 cases (12.5%). The detection rate of the combined analysis did not improve the single detection rate for either MYD88 L265P or CD79B Y196. CONCLUSION: The low detection rate of MYD88 L265P and CD79B Y196 mutations in cfDNA in the plasma of PCNSL patients argues against its use in routine diagnostics. However, detection of MYD88 L265P by ddPCR in cfDNA in the plasma could be considered in challenging cases.

Effect of Reduced Graphene Oxide on Microwave Absorbing Properties of Al1.5Co4Fe2Cr High-Entropy Alloys.

The microwave absorption performance of high-entropy alloys (HEAs) can be improved by reducing the reflection coefficient of electromagnetic waves and broadening the absorption frequency band. The present work prepared flaky irregular-shaped Al1.5Co4Fe2Cr and Al1.5Co4Fe2Cr@rGO alloy powders by mechanical alloying (MA) at different rotational speeds. It was found that the addition of trace amounts of reduced graphene oxide (rGO) had a favorable effect on the impedance matching, reflection loss (RL), and effective absorbing bandwidth (EAB) of the Al1.5Co4Fe2Cr@rGO HEA composite powders. The EAB of the alloy powders prepared at 300 rpm increased from 2.58 GHz to 4.62 GHz with the additive, and the RL increased by 2.56 dB. The results showed that the presence of rGO modified the complex dielectric constant of HEA powders, thereby enhancing their dielectric loss capability. Additionally, the presence of lamellar rGO intensified the interfacial reflections within the absorber, facilitating the dissipation of electromagnetic waves. The effect of the ball milling speed on the defect concentration of the alloy powders also affected its wave absorption performance. The samples prepared at 350 rpm had the best wave absorption performance, with an RL of -16.23 and -17.28 dB for a thickness of 1.6 mm and EAB of 5.77 GHz and 5.43 GHz, respectively.

DeTAL: Open-Vocabulary Temporal Action Localization with Decoupled Networks.

Pre-trained visual-language (ViL) models have demonstrated good zero-shot capability in video understanding tasks, where they were usually adapted through fine-tuning or temporal modeling. However, in the task of open-vocabulary temporal action localization (OV-TAL), such adaption reduces the robustness of ViL models against different data distributions, leading to a misalignment between visual representations and text descriptions of unseen action categories. As a result, existing methods often strike a trade-off between action detection and classification. Aiming at this issue, this paper proposes DeTAL, a simple but effective two-stage approach for OV-TAL. DeTAL decouples action detection from action classification to avoid the compromise between them, and the state-of-the-art methods for close-set action localization can be handily adapted to OV-TAL, which significantly improves the performance. Meanwhile, DeTAL can easily tackle the scenario where action category annotations are unavailable in the training dataset. In the experiments, we propose a new cross-dataset setting to evaluate the zero-shot capability of different methods. And the results demonstrate that DeTAL outperforms the state-of-the-art methods for OV-TAL on both THUMOS14 and ActivityNet1.3. Code and data are publicly available at https://github.com/vsislab/DeTAL.

Post-stroke cognitive impairment: exploring molecular mechanisms and omics biomarkers for early identification and intervention.

Post-stroke cognitive impairment (PSCI) is a major stroke consequence that has a severe impact on patients' quality of life and survival rate. For this reason, it is especially crucial to identify and intervene early in high-risk groups during the acute phase of stroke. Currently, there are no reliable and efficient techniques for the early diagnosis, appropriate evaluation, or prognostication of PSCI. Instead, plenty of biomarkers in stroke patients have progressively been linked to cognitive impairment in recent years. High-throughput omics techniques that generate large amounts of data and process it to a high quality have been used to screen and identify biomarkers of PSCI in order to investigate the molecular mechanisms of the disease. These techniques include metabolomics, which explores dynamic changes in the organism, gut microbiomics, which studies host-microbe interactions, genomics, which elucidates deeper disease mechanisms, transcriptomics and proteomics, which describe gene expression and regulation. We looked through electronic databases like PubMed, the Cochrane Library, Embase, Web of Science, and common databases for each omics to find biomarkers that might be connected to the pathophysiology of PSCI. As all, we found 34 studies: 14 in the field of metabolomics, 5 in the field of gut microbiomics, 5 in the field of genomics, 4 in the field of transcriptomics, and 7 in the field of proteomics. We discovered that neuroinflammation, oxidative stress, and atherosclerosis may be the primary causes of PSCI development, and that metabolomics may play a role in the molecular mechanisms of PSCI. In this study, we summarized the existing issues across omics technologies and discuss the latest discoveries of PSCI biomarkers in the context of omics, with the goal of investigating the molecular causes of post-stroke cognitive impairment. We also discuss the potential therapeutic utility of omics platforms for PSCI mechanisms, diagnosis, and intervention in order to promote the area's advancement towards precision PSCI treatment.

Recent advances of fermented fruits: A review on strains, fermentation strategies, and functional activities.

Fruits are recognized as healthy foods with abundant nutritional content. However, due to their high content of sugar and water, they are easily contaminated by microorganisms leading to spoilage. Probiotic fermentation is an effective method to prevent fruit spoilage. In addition, during fermentation, the probiotics can react with the nutrients in fruits to produce new derived compounds, giving the fruit specific flavor, enhanced color, active ingredients, and nutritional values. Noteworthy, the choice of fermentation strains and strategies has a significant impact on the quality of fermented fruits. Thus, this review provides comprehensive information on the fermentation strains (especially yeast, lactic acid bacteria, and acetic acid bacteria), fermentation strategies (natural or inoculation fermentation, mono- or mixed-strain inoculation fermentation, and liquid- or solid-state fermentation), and the effect of fermentation on the shelf life, flavor, color, functional components, and physiological activities of fruits. This review will provide a theoretical guidance for the production of fermented fruits.

MotionTrack: Learning motion predictor for multiple object tracking.

Significant progress has been achieved in multi-object tracking (MOT) through the evolution of detection and re-identification (ReID) techniques. Despite these advancements, accurately tracking objects in scenarios with homogeneous appearance and heterogeneous motion remains a challenge. This challenge arises from two main factors: the insufficient discriminability of ReID features and the predominant utilization of linear motion models in MOT. In this context, we introduce a novel motion-based tracker, MotionTrack, centered around a learnable motion predictor that relies solely on object trajectory information. This predictor comprehensively integrates two levels of granularity in motion features to enhance the modeling of temporal dynamics and facilitate precise future motion prediction for individual objects. Specifically, the proposed approach adopts a self-attention mechanism to capture token-level information and a Dynamic MLP layer to model channel-level features. MotionTrack is a simple, online tracking approach. Our experimental results demonstrate that MotionTrack yields state-of-the-art performance on datasets such as Dancetrack and SportsMOT, characterized by highly complex object motion.

NLCECA score: a serum inflammatory-tumor biomarker score to predict survival of advanced perihilar cholangiocarcinoma after hepatic arterial infusion chemotherapy.

Prognostic features in advanced perihilar cholangiocarcinoma (pCCA) patients who received first-line hepatic arterial infusion chemotherapy (HAIC) are unknown. The purpose of our study was to develop an applicable score based on serum inflammatory-tumor biomarkers to predict the survival of advanced pCCA patients who received first-line HAIC. In total, 106 advanced pCCA patients were enrolled as the training cohort. The optimal cutoff values of baseline variables were defined by the receiver operating characteristic method or according to previous publications. According to the results of Cox regression analysis, baseline neutrophil-to-lymphocyte ratio (NLR) > 3.19, carcinoembryonic antigen (CEA) > 10 ng/mL, and carbohydrate antigen 19-9 (CA19-9) > 200 U/mL were identified as independent survival predictors, which were used to develop the NLCECA score (NLR, CEA, and CA19-9). When including the NLCECA score in the multivariate analysis, the NLCECA score was the only independent predictor of survival. The risk of survival decreased by 111.9% for each 1-point increase in the NLCECA score. Additionally, the NLCECA score could also predict survival in another 33 patients in the validation cohort (P < 0.001). In summary, the NLCECA score is a potential biomarker system for predicting the survival of advanced pCCA patients who received first-line HAIC.

Passive trapping of biomolecules in hotspots with all-dielectric terahertz metamaterials.

Electromagnetic metamaterials feature the capability of squeezing photons into hotspot regions of high intensity near-field enhancement for strong light-matter interaction, underpinning the next generation of emerging biosensors. However, randomly dispersed biomolecules around the hotspots lead to weak interactions. Here, we demonstrate an all-silicon dielectric terahertz metamaterial sensor design capable of passively trapping biomoleculars into the resonant cavities confined with powerful electric field. Specifically, multiple controllable high-quality factor resonances driven by bound states in the continuum (BIC) are realized by employing longitudinal symmetry breaking. The dielectric metamaterial sensor with nearly 15.2 experimental figure-of-merit enabling qualitative and quantitative identification of different amino acids by delivering biomolecules to the hotspots for strong light-matter interactions. It is envisioned that the presented strategy will enlighten high-performance meta-sensors design from microwaves to visible frequencies, and serve as a potential platform for microfluidic sensing, biomolecular capture, and sorting devices.

Extrachromosomal circular DNA (eccDNA) characteristics in the bile and plasma of advanced perihilar cholangiocarcinoma patients and the construction of an eccDNA-related gene prognosis model.

Extrachromosomal DNAs (eccDNAs) frequently carry amplified oncogenes. This investigation aimed to examine the occurrence and role of eccDNAs in individuals diagnosed with advanced perihilar cholangiocarcinoma (pCCA) who exhibited distinct prognostic outcomes. Five patients with poor survival outcomes and five with better outcomes were selected among patients who received first-line hepatic arterial infusion chemotherapy from June 2021 to June 2022. The extracted eccDNAs were amplified for high-throughput sequencing. Genes associated with the differentially expressed eccDNAs were analyzed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The differentially expressed bile eccDNA-related genes were used to construct a prognostic model. Across all 10 patients, a total of 19,024 and 3,048 eccDNAs were identified in bile and plasma, respectively. The concentration of eccDNA detected in the bile was 9-fold higher than that in plasma. The chromosome distribution of the eccDNAs were similar between bile and matched plasma. GO and KEGG pathway analyses showed enrichment in the mitogen-activated protein kinase (MAPK) and Wnt/ß-catenin pathways in patients with poor survival outcomes. According to the prognostic model constructed by eccDNA-related genes, the high-risk group of cholangiocarcinoma patients displayed significantly shorter overall survival (p < 0.001). Moreover, the degree of infiltration of immunosuppressive cells was higher in patients in the high-risk group. In conclusion, EccDNA could be detected in bile and plasma of pCCA patients, with a higher concentration. A prognostic model based on eccDNA-related genes showed the potential to predict the survival and immune microenvironment of patients with cholangiocarcinoma.

Inhibition of GLUD1 mediated by LASP1 and SYVN1 contributes to hepatitis B virus X protein-induced hepatocarcinogenesis.

Glutamate dehydrogenase 1 (GLUD1) is implicated in oncogenesis. However, little is known about the relationship between GLUD1 and hepatocellular carcinoma (HCC). In the present study, we demonstrated that the expression levels of GLUD1 significantly decreased in tumors, which was relevant to the poor prognosis of HCC. Functionally, GLUD1 silencing enhanced the growth and migration of HCC cells. Mechanistically, the upregulation of interleukin-32 through AKT activation contributes to GLUD1 silencing-facilitated hepatocarcinogenesis. The interaction between GLUD1 and AKT, as well as α-ketoglutarate regulated by GLUD1, can suppress AKT activation. In addition, LIM and SH3 protein 1 (LASP1) interacts with GLUD1 and induces GLUD1 degradation via the ubiquitin-proteasome pathway, which relies on the E3 ubiquitin ligase synoviolin (SYVN1), whose interaction with GLUD1 is enhanced by LASP1. In hepatitis B virus (HBV)-related HCC, the HBV X protein (HBX) can suppress GLUD1 with the participation of LASP1 and SYVN1. Collectively, our data suggest that GLUD1 silencing is significantly associated with HCC development, and LASP1 and SYVN1 mediate the inhibition of GLUD1 in HCC, especially in HBV-related tumors.