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Long non-coding RNAs (lncRNAs) have been reported to participate in regulating gene expression and are related to tumor progression. FGD5 antisense RNA 1 (FGD5-AS1) facilitates the progression of various tumors. However, the expression and function of FGD5-AS1 in ovarian cancer (OC) and its mechanism of action are not yet clear. Real-time polymerase chain reaction (RT-PCR) was employed to explore the expression levels of FGD5-AS1 and miR-142-5p in OC. The relationship between the expression of FGD5-AS1 and clinicopathological indicators of OC patients was analyzed by χ2 test. CCK-8 assay, BrdU assay, and Transwell assay were carried out to detect cell proliferation, migration, as well as invasion, respectively. Subcutaneous tumorigenesis experiment and lung metastasis model were used to examine the biological effects of FGD5-AS1 in OC in vivo. Dual luciferase reporter gene assay or RIP experiment was employed to explore the targeting relationship between FGD5-AS1 and miR-142-5p, as well as miR-142-5p and PD-L1 3′UTR. First, we found that FGD5-AS1 was markedly up-regulated in OC. Moreover, its high expression level was associated with positive local lymph node metastasis and higher T stage in OC patients. Gain-of-function and loss-of-function assays demonstrated that FGD5-AS1 facilitated the proliferation, migration, as well as invasion of OC cells. Mechanistically, it was revealed that FGD5-AS1 targeted miR-142-5p to repress its expression and function. Furthermore, miR-142-5p has a binding site for 3’ UTR of PD-L1, and FGD5-AS1 could positively regulate PD-L1 expression via repressing miR-142-5p. The present study reports that FGD5-AS1/miR-142-5p/PD-L1 axis is involved in regulating OC progression.Graphic abstract

Hydraulic systems are critical components of mechanical equipment, and effective fault diagnosis is essential for minimizing maintenance costs and enhancing system reliability. In practical applications, data from hydraulic systems are collected with varying sampling frequencies, coupled with complex interdependencies within the data, which poses challenges for existing fault diagnosis algorithms. To solve the above problems, this paper proposes an intelligent fault diagnosis of a hydraulic system based on a multiscale one-dimensional convolution neural network with a multiattention mechanism (MA-MS1DCNN). The proposed method first extracts features from multirate data samples using a parallel 1DCNN with different receptive fields. Next, a Hybrid Attention Module (HAM) is proposed, consisting of two submodules: the Correlation Attention Module (CAM) and the Importance Attention Module (IAM), which aim to meticulously and comprehensively model the complex relationships between channel features. Subsequently, to effectively utilize the feature information of different frequencies, the HAM is integrated into the 1DCNN to form the MA-MS1DCNN. Finally, the proposed method is evaluated and experimentally compared using the UCI hydraulic system dataset. The results demonstrate that, compared to existing methods such as Shapelet, MCIFM, and CNNs, the proposed method shows superior diagnostic performance.

Background/Aims: In this study, we aimed to investigate how MORC family CW-type zinc finger 2 (MORC2) affects tumor progression of lung cancer. Methods: The MORC2 level was analyzed by real-time RT-PCR and immunohistochemistry (IHC) in normal control tissues and lung cancers. LL/2 cells overexpressing MORC2 were used to study how MORC2 expression influences lung cancer progression. The effects of MORC2 on cell viability, migration and invasion were assessed by MTT assay, Western blotting, and transwell assays, respectively. Afterwards, the effects of MORC2 on the activation of the Wnt/β-catenin pathway were explored by Western blotting. The effects of MORC2 on tumor-associated macrophages (TAM) were determined by immunofluorescence (IF) staining, real-time RT-PCR and Western blotting. Results: Our results showed that MORC2 was upregulated in lung cancers relative to adjacent tissues. The results also demonstrated that MORC2 promoted lung cancer tumor growth in vivo. Additionally, MORC2 overexpression stimulated the upregulation of vascular endothelial growth factor (VEGF), driving angiogenesis. MORC2 overexpression in LL/2 also increased the amount of aldehyde dehydrogenase-1 (ALDH1) protein, indicating that MORC2 increased cancer stem cell features. We further determined that MORC2 activated Wnt/β-catenin signaling in lung cancer cells. Upregulation of macrophage-recruiting genes including VEGF and Macrophage-specific colony stimulating factor (CSF-1) recruits TAMs to the tumor site, which has the net effect of promoting additional tumor growth and metastasis. Conclusion: Our data suggest that MORC2 overexpression can drive lung cancer growth by stimulating the recruitment of TAMs in addition to angiogenesis and that activation of Wnt/β-signaling may be a key pathway underlying this phenotype that is amenable to pharmacological intervention.

Background The dry root or stem bark of Fraxinus chinensis is a famous herb Qin Pi which is known for its anti-inflammatory, analgesic, anti-tumor, liver protective and diuretic pharmacological effects, the fundamental chemical components are coumarin, phenylethanol glycosides and flavonoids. However, it is difficult to clarify the secondary metabolite synthesis pathway and key genes involved in the pathway because of lack genome information of Fraxinus chinensis . Objective To generate a complete transcriptome of Fraxinus chinensis and to clarify the differentially expressed genes (DEGs) in leaves and stem barks. Methods In this study, full-length transcriptome analysis and RNA-Seq were combined to characterize Fraxinus chinensis transcriptome. Results A total of 69,145 transcripts were acquired and regarded as reference transcriptome, 67,441 transcripts (97.47%) were annotated to NCBI non-redundant protein (Nr), SwissProt, the Kyoto Encyclopedia of Genes and Genomes (KEGG) and eukaryotic orthologous groups (KOG) databases. A total of 18,917 isoforms were annotated to KEGG database and classified to 138 biological pathways. In total, 10,822 simple sequence repeat (SSRs) and 11,319 resistance (R) gene were classified to 18 types, and 3947 transcription factors (TFs) were identified in full-length transcriptome analysis. Additionally, 15,095 DEGs were detected by RNA-seq in leaves and barks, including 4696 significantly up-regulated and 10,399 significantly down-regulated genes. And 254 transcripts were annotated into phenylpropane metabolism pathway containing 86 DEGs and ten of these enzyme genes were verified by qRT-PCR. Conclusion It laid the foundation for further exploration of the biosynthetic pathway of phenylpropanoids and related key enzyme genes.

ChatGPT (OpenAI) has shown great potential in clinical diagnosis and could become an excellent auxiliary tool in clinical practice. This study investigates and evaluates ChatGPT in diagnostic capabilities by comparing the performance of GPT-3.5 and GPT-4.0 across model iterations. This study aims to evaluate the precise diagnostic ability of GPT-3.5 and GPT-4.0 for colon cancer and its potential as an auxiliary diagnostic tool for surgeons and compare the diagnostic accuracy rates between GTP-3.5 and GPT-4.0. We precisely assess the accuracy of primary and secondary diagnoses and analyze the causes of misdiagnoses in GPT-3.5 and GPT-4.0 according to 7 categories: patient histories, symptoms, physical signs, laboratory examinations, imaging examinations, pathological examinations, and intraoperative findings. We retrieved 316 case reports for intestinal cancer from the Chinese Medical Association Publishing House database, of which 286 cases were deemed valid after data cleansing. The cases were translated from Mandarin to English and then input into GPT-3.5 and GPT-4.0 using a simple, direct prompt to elicit primary and secondary diagnoses. We conducted a comparative study to evaluate the diagnostic accuracy of GPT-4.0 and GPT-3.5. Three senior surgeons from the General Surgery Department, specializing in Colorectal Surgery, assessed the diagnostic information at the Chinese PLA (People's Liberation Army) General Hospital. The accuracy of primary and secondary diagnoses was scored based on predefined criteria. Additionally, we analyzed and compared the causes of misdiagnoses in both models according to 7 categories: patient histories, symptoms, physical signs, laboratory examinations, imaging examinations, pathological examinations, and intraoperative findings. Out of 286 cases, GPT-4.0 and GPT-3.5 both demonstrated high diagnostic accuracy for primary diagnoses, but the accuracy rates of GPT-4.0 were significantly higher than GPT-3.5 (mean 0.972, SD 0.137 vs mean 0.855, SD 0.335; t =5.753; P<.001). For secondary diagnoses, the accuracy rates of GPT-4.0 were also significantly higher than GPT-3.5 (mean 0.908, SD 0.159 vs mean 0.617, SD 0.349; t =-7.727; P<.001). GPT-3.5 showed limitations in processing patient history, symptom presentation, laboratory tests, and imaging data. While GPT-4.0 improved upon GPT-3.5, it still has limitations in identifying symptoms and laboratory test data. For both primary and secondary diagnoses, there was no significant difference in accuracy related to age, gender, or system group between GPT-4.0 and GPT-3.5. This study demonstrates that ChatGPT, particularly GPT-4.0, possesses significant diagnostic potential, with GPT-4.0 exhibiting higher accuracy than GPT-3.5. However, GPT-4.0 still has limitations, particularly in recognizing patient symptoms and laboratory data, indicating a need for more research in real-world clinical settings to enhance its diagnostic capabilities.

Plants utilize energy from sunlight to perform photosynthesis in chloroplast, an organelle that could be damaged by solar UV radiation. The ultraviolet-B (UV-B) photoreceptor UVR8 is required for UV-B perception and signal transduction. However, little is known about how UVR8 influence chloroplast development under UV-B radiation. Here, we characterized tomato UVR8 gene ( SlUVR8 ) and our results indicated that SlUVR8 facilitate plant acclimation to UV-B stress by orchestrating expression of the UVB-responsive genes ( HY5 and CHS ) and accumulating UV-absorptive compounds. In addition, we also discovered that SlUVR8 promotes fruit chloroplast development through enhancing accumulation of transcription factor GOLDEN2-LIKE2 (SlGLK2) which determines chloroplast and chlorophyll levels. Furthermore, UV-B radiation could increase expression of SlGLK2 and its target genes in fruits and leaves. SlUVR8 is required for UVB-induced SlGLK2 expression. Together, our work not only identified the conserved functions of SlUVR8 gene in response to UV-B stress, but also uncovered a novel role that SlUVR8 could boost chloroplast development by accumulating SlGLK2 proteins.

The flavonoid compounds are important secondary metabolites with versatile human nutritive benefits and fulfill a multitude of functions during plant growth and development. The abundance of different flavonoid compounds are finely tuned with species-specific pattern by a ternary MBW complex, which consists of a MYB, a bHLH, and a WD40 protein, but the essential role of SlAN11, which is a WD40 protein, is not fully understood in tomato until now. In this study, a tomato WD40 protein named as SlAN11 was characterized as an effective transcription regulator to promote plant anthocyanin and seed proanthocyanidin (PA) contents, with late flavonoid biosynthetic genes activated in 35S::SlAN11 transgenic lines, while the dihydroflavonol flow to the accumulation of flavonols or their glycosylated derivatives was reduced by repressing the expression of SlFLS in this SlAN11 -overexpressed lines. The above changes were reversed in 35S::SlAN11-RNAi transgenic lines except remained levels of flavonol compounds and SlFLS expression. Interestingly, our data revealed that SlAN11 gene could affect seed dormancy by regulating the expressions of abscisic acid (ABA) signaling-related genes SlABI3 and SlABI5 , and the sensitivity to ABA treatment in seed germination is conversely changed by SlAN11 -overexpressed or -downregulated lines. Yeast two-hybrid assays demonstrated that SlAN11 interacted with bHLH but not with MYB proteins in the ternary MBW complex, whereas bHLH interacted with MYB in tomato. Our results indicated that low level of anthocyanins in tomato fruits, with low expression of bHLH ( SlTT8 ) and MYB ( SlANT1 and SlAN2 ) genes, remain unchanged upon modification of SlAN11 gene alone in the transgenic lines. These results suggest that the tomato WD40 protein SlAN11, coordinating with bHLH and MYB proteins, plays a crucial role in the fine adjustment of the flavonoid biosynthesis and seed dormancy in tomato. Tomatoes: a protein control for flavonoids Insights into the production of important nutrients called flavonoids are revealed by a molecular and genetic study of tomatoes. Flavonoids are a diverse group of chemicals with a variety of metabolic functions, and which contribute to the characteristic colors of many fruits and vegetables. They have been linked with health benefits due to their antioxidant, anti-inflammatory, and immune-regulating activities. Researchers in China, led by Yinan Yao at Southwest University of Science and Technology, explored the activity of a protein known as  SlAN11. They found that the protein interacts with other proteins to regulate the activity of specific genes, increasing the production of flavonoids called anthocyanins. SlAN11 also regulates the dormancy process in tomato seeds. Geneticists may use the results to generate new breeds of tomato plants enriched in flavonoids to promote good health.

Mastitis is one of the most significant diseases affecting the development of the dairy industry and has traditionally been associated with pathogenic infections. However, emerging evidence highlights that ruminal microbial homeostasis also plays a crucial role in the pathogenesis of mastitis. Specifically, cows with mastitis exhibit reduced alpha diversity and altered microbial composition in the rumen. Inducing ruminal dysbiosis through a high-concentrate diet has been shown to trigger mastitis in cows, and transplantation of ruminal microbiota from mastitis-affected cows to recipient mice can induce mastitis in mice. Mechanistically, ruminal dysbiosis increases gastrointestinal inflammation and compromises the integrity of the gastrointestinal barrier, thereby facilitating the translocation of harmful bacterial components, metabolites, and pathobionts into the bloodstream. This disruption impairs blood-milk barrier function, leading to systemic inflammation and the development of mastitis. In this review, we summarize recent advances in understanding how ruminal dysbiosis induces mastitis and explore potential prevention and control strategies targeting the modulation of ruminal microbiota.

With the proliferation of Knowledge Graphs (KGs), knowledge graph completion (KGC) has attracted much attention. Previous KGC methods focus on extracting shallow structural information from KGs or in combination with external knowledge, especially in commonsense concepts (generally, commonsense concepts refer to the basic concepts in related fields that are required for various tasks and academic research, for example, in the general domain, “Country” can be considered as a commonsense concept owned by “China”), to predict missing links. However, the technology of extracting commonsense concepts from the limited database is immature, and the scarce commonsense database is also bound to specific verticals (commonsense concepts vary greatly across verticals, verticals refer to a small field subdivided vertically under a large field). Furthermore, most existing KGC models refine performance on public KGs, leading to inapplicability to actual KGs. To address these limitations, we proposed a novel Scalable Formal Concept-driven Architecture (SFCA) to automatically encode factual triples into formal concepts as a superior structural feature, to support rich information to KGE. Specifically, we generate dense formal concepts first, then yield a handful of entity-related formal concepts by sampling and delimiting the appropriate candidate entity range via the filtered formal concepts to improve the inference of KGC. Compared with commonsense concepts, KGC benefits from more valuable information from the formal concepts, and our self-supervision extraction method can be applied to any KGs. Comprehensive experiments on five public datasets demonstrate the effectiveness and scalability of SFCA. Besides, the proposed architecture also achieves the SOTA performance on the industry dataset. This method provides a new idea in the promotion and application of knowledge graphs in AI downstream tasks in general and industrial fields.

In this article, we researched the existence of the solution to the fractional Navier-Stokes equations with the Coriolis force under initial data, which belong to the Lei-Lin-Gevrey spaces. Moreover, we showed a blow-up criterion, i.e., when the maximal time of existence is finite, we proved that the norm of this same solution, in a specific Lei-Lin-Gevrey space, goes to infinity, as time tends to the maximal time of its existence.