Large-scale snake genome analyses provide insights into vertebrate development.

Snakes are a remarkable squamate lineage with unique morphological adaptations, especially those related to the evolution of vertebrate skeletons, organs, and sensory systems. To clarify the genetic underpinnings of snake phenotypes, we assembled and analyzed 14 de novo genomes from 12 snake families. We also investigated the genetic basis of the morphological characteristics of snakes using functional experiments. We identified genes, regulatory elements, and structural variations that have potentially contributed to the evolution of limb loss, an elongated body plan, asymmetrical lungs, sensory systems, and digestive adaptations in snakes. We identified some of the genes and regulatory elements that might have shaped the evolution of vision, the skeletal system and diet in blind snakes, and thermoreception in infrared-sensitive snakes. Our study provides insights into the evolution and development of snakes and vertebrates.

Why does understanding the biology of fibroblasts in immunity really matter?

Fibroblasts are known for their ability to make and modify the extracellular matrix. However, there is more to them than meets the eye. It is now clear that they help define tissue microenvironments and support immune responses in organs. As technology advances, we have started to uncover the secrets of fibroblasts. In this Essay, we present fibroblasts as not only the builders and renovators of tissue environments but also the rheostat cells for immune circuits. Although they perform location-specific functions, they do not have badges of fixed identity. Instead, they display a spectrum of functional states and can swing between these states depending on the needs of the organ. As fibroblasts participate in a range of activities both in health and disease, finding the key factors that alter their development and functional states will be an important goal to restore homeostasis in maladapted tissues.

Epidemiology of nasopharyngeal carcinoma: current insights and future outlook.

Nasopharyngeal carcinoma (NPC) is characterised by its remarkable geographical and ethnic distribution. The interplay between genetic susceptibility, environmental exposures, and Epstein-Barr virus (EBV) infections is indicated in the development of NPC. Exposure to tobacco smoking, dietary factors, and inhalants has been associated with the risk of NPC. Genetic association studies have revealed NPC-associated susceptibility loci, including genes involved in immune responses, xenobiotic metabolism, genome maintenance, and cell cycle regulation. EBV exposure timing and strain variation might play a role in its carcinogenicity, although further investigations are required. Other factors including medical history and oral hygiene have been implicated in NPC. Prevention strategies, including primary prevention and secondary prevention through early detection, are vital in reducing mortality and morbidity of NPC. The current review discusses the global and regional distribution of NPC incidences, the risk factors associated with NPC, and the public health implications of these insights. Future investigations should consider international, large-scale prospective studies to elucidate the mechanisms underlying NPC pathogenesis and develop individualized interventions for NPC.

Predicting lncRNA-disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation.

Recent studies have revealed that long noncoding RNAs (lncRNAs) are closely linked to several human diseases, providing new opportunities for their use in detection and therapy. Many graph propagation and similarity fusion approaches can be used for predicting potential lncRNA-disease associations. However, existing similarity fusion approaches suffer from noise and self-similarity loss in the fusion process. To address these problems, a new prediction approach, termed SSMF-BLNP, based on organically combining selective similarity matrix fusion (SSMF) and bidirectional linear neighborhood label propagation (BLNP), is proposed in this paper to predict lncRNA-disease associations. In SSMF, self-similarity networks of lncRNAs and diseases are obtained by selective preprocessing and nonlinear iterative fusion. The fusion process assigns weights to each initial similarity network and introduces a unit matrix that can reduce noise and compensate for the loss of self-similarity. In BLNP, the initial lncRNA-disease associations are employed in both lncRNA and disease directions as label information for linear neighborhood label propagation. The propagation was then performed on the self-similarity network obtained from SSMF to derive the scoring matrix for predicting the relationships between lncRNAs and diseases. Experimental results showed that SSMF-BLNP performed better than seven other state of-the-art approaches. Furthermore, a case study demonstrated up to 100% and 80% accuracy in 10 lncRNAs associated with hepatocellular carcinoma and 10 lncRNAs associated with renal cell carcinoma, respectively. The source code and datasets used in this paper are available at: https://github.com/RuiBingo/SSMF-BLNP.

Viscerosensory signalling to the nucleus accumbens via the solitary tract nucleus.

The nucleus of the solitary tract (NTS) receives direct viscerosensory vagal afferent input that drives autonomic reflexes, neuroendocrine function and modulates behaviour. A subpopulation of NTS neurons project to the nucleus accumbens (NAc); however, the function of this NTS-NAc pathway remains unknown. A combination of neuroanatomical tracing, slice electrophysiology and fibre photometry was used in mice and/or rats to determine how NTS-NAc neurons fit within the viscerosensory network. NTS-NAc projection neurons are predominantly located in the medial and caudal portions of the NTS with 54 ± 7% (mice) and 65 ± 3% (rat) being TH-positive, representing the A2 NTS cell group. In horizontal brainstem slices, solitary tract (ST) stimulation evoked excitatory post-synaptic currents (EPSCs) in NTS-NAc projection neurons. The majority (75%) received low-jitter, zero-failure EPSCs characteristic of monosynaptic ST afferent input that identifies them as second order to primary sensory neurons. We then examined whether NTS-NAc neurons respond to cholecystokinin (CCK, 20 µg/kg ip) in vivo in both mice and rats. Surprisingly, there was no difference in the number of activated NTS-NAc cells between CCK and saline-treated mice. In rats, just 6% of NTS-NAc cells were recruited by CCK. As NTS TH neurons are the primary source for NAc noradrenaline, we measured noradrenaline release in the NAc and showed that NAc noradrenaline levels declined in response to cue-induced reward retrieval but not foot shock. Combined, these findings suggest that high-fidelity afferent information from viscerosensory afferents reaches the NAc. These signals are likely unrelated to CCK-sensitive vagal afferents but could interact with other sensory and higher order inputs to modulate learned appetitive behaviours.

PGD: Shared gene linking polycystic ovary syndrome and endometrial cancer, influencing proliferation and migration through glycometabolism.

The relationship among polycystic ovary syndrome (PCOS), endometrial cancer (EC), and glycometabolism remains unclear. We explored shared genes between PCOS and EC, using bioinformatics to unveil their pathogenic connection and influence on EC prognosis. Gene Expression Omnibus datasets GSE226146 (PCOS) and GSE196033 (EC) were used. A protein-protein interaction (PPI) network was constructed to identify the central genes. Candidate markers were screened using dataset GSE54250. Differences in marker expression were confirmed in mouse PCOS and human EC tissues using RT-PCR and immunohistochemistry. The effect of PGD on EC proliferation and migration was explored using Ki-67 and Transwell assays. PGD's impact on the glycometabolic pathway within carbon metabolism was assessed by quantifying glucose content and lactic acid production. R software identified 31 common genes in GSE226146 and GSE196033. Gene Ontology functional classification revealed enrichment in the "purine nucleoside triphosphate metabolism process," with key Kyoto Encyclopedia of Genes and Genomes pathways related to "carbon metabolism." The PPI network identified 15 hub genes. HK2, NDUFS8, PHGDH, PGD, and SMAD3 were confirmed as candidate markers. The RT-PCR analysis validated distinct HK2 and PGD expression patterns in mouse PCOS ovarian tissue and human EC tissue, as well as in normal and EC cells. Transfection experiments with Ishikawa cells further confirmed PGD's influence on cell proliferation and migration. Suppression of PGD expression impeded glycometabolism within the carbon metabolism of EC cells, suggesting PGD as a significant PCOS risk factor impacting EC proliferation and migration through modulation of single carbon metabolism. These findings highlight PGD's pivotal role in EC onset and prognosis.

Targeting OXCT1-mediated ketone metabolism reprograms macrophages to promote antitumor immunity via CD8+ T cells in hepatocellular carcinoma.

BACKGROUND & AIMS: The liver is the main organ of ketogenesis, while ketones are mainly metabolized in peripheral tissues via the critical enzyme 3-oxoacid CoA-transferase 1 (OXCT1). We previously found that ketolysis is reactivated in hepatocellular carcinoma (HCC) cells through OXCT1 expression to promote tumor progression; however, whether OXCT1 regulates antitumor immunity remains unclear. METHODS: To investigate the expression pattern of OXCT1 in HCC in vivo, we conducted multiplex immunohistochemistry experiments on human HCC specimens. To explore the role of OXCT1 in mouse HCC tumor-associated macrophages (TAMs), we generated LysMcreOXCT1f/f (OXCT1 conditional knockout in macrophages) mice. RESULTS: Here, we found that inhibiting OXCT1 expression in tumor-associated macrophages reduced CD8+ T-cell exhaustion through the succinate-H3K4me3-Arg1 axis. Initially, we found that OXCT1 was highly expressed in liver macrophages under steady state and that OXCT expression was further increased in TAMs. OXCT1 deficiency in macrophages suppressed tumor growth by reprogramming TAMs toward an antitumor phenotype, reducing CD8+ T-cell exhaustion and increasing CD8+ T-cell cytotoxicity. Mechanistically, high OXCT1 expression induced the accumulation of succinate, a byproduct of ketolysis, in TAMs, which promoted Arg1 transcription by increasing the H3K4me3 level in the Arg1 promoter. In addition, pimozide, an inhibitor of OXCT1, suppressed Arg1 expression as well as TAM polarization toward the protumor phenotype, leading to decreased CD8+ T-cell exhaustion and slower tumor growth. Finally, high expression of OXCT1 in macrophages was positively associated with poor survival in patients with HCC. CONCLUSIONS: In conclusion, our results demonstrate that OXCT1 epigenetically suppresses antitumor immunity, suggesting that suppressing OXCT1 activity in TAMs could be an effective approach for treating liver cancer. IMPACT AND IMPLICATIONS: The intricate metabolism of liver macrophages plays a critical role in shaping hepatocellular carcinoma progression and immune modulation. Targeting macrophage metabolism to counteract immune suppression presents a promising avenue for hepatocellular carcinoma treatment. Herein, we found that the ketogenesis gene OXCT1 was highly expressed in tumor-associated macrophages (TAMs) and promoted tumor growth by reprogramming TAMs toward a protumor phenotype. Pharmacological targeting or genetic downregulation of OXCT1 in TAMs enhances antitumor immunity and slows tumor growth. Our results suggest that suppressing OXCT1 activity in TAMs could be an effective approach for treating liver cancer.

Cryptic bacterial pathogens of diatoms peak during senescence of a winter diatom bloom.

Diatoms are globally abundant microalgae that form extensive blooms in aquatic ecosystems. Certain bacteria behave antagonistically towards diatoms, killing or inhibiting their growth. Despite their crucial implications to diatom blooms and population health, knowledge of diatom antagonists in the environment is fundamentally lacking. We report systematic characterisation of the diversity and seasonal dynamics of bacterial antagonists of diatoms via plaque assay sampling in the Western English Channel (WEC), where diatoms frequently bloom. Unexpectedly, peaks in detection did not occur during characteristic spring diatom blooms, but coincided with a winter bloom of Coscinodiscus, suggesting that these bacteria likely influence distinct diatom host populations. We isolated multiple bacterial antagonists, spanning 4 classes and 10 bacterial orders. Notably, a diatom attaching Roseobacter Ponticoccus alexandrii was isolated multiple times, indicative of a persistent environmental presence. Moreover, many isolates had no prior reports of antagonistic activity towards diatoms. We verified diatom growth inhibitory effects of eight isolates. In all cases tested, these effects were activated by pre-exposure to diatom organic matter. Discovery of widespread 'cryptic' antagonistic activity indicates that bacterial pathogenicity towards diatoms is more prevalent than previously recognised. Finally, examination of the global biogeography of WEC antagonists revealed co-occurrence patterns with diatom host populations in marine waters globally.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. METHODS: Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). RESULTS: The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). CONCLUSIONS: Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

Auranofin inhibits the occurrence of colorectal cancer by promoting mTOR-dependent autophagy and inhibiting epithelial-mesenchymal transformation.

Colorectal cancer (CRC) is one of the world's most common and deadly cancers. According to GLOBOCAN2020's global incidence rate and mortality estimates, CRC is the third main cause of cancer and the second leading cause of cancer-related deaths worldwide. The US Food and Drug Administration has approved auranofin for the treatment of rheumatoid arthritis. It is a gold-containing chemical that inhibits thioredoxin reductase. Auranofin has a number of biological activities, including anticancer activity, although it has not been researched extensively in CRC, and the mechanism of action on CRC cells is still unknown. The goal of this research was to see how Auranofin affected CRC cells in vivo and in vitro . The two chemical libraries were tested for drugs that make CRC cells more responsive. The CCK-8 technique was used to determine the cell survival rate. The invasion, migration, and proliferation of cells were assessed using a transwell test and a colony cloning experiment. An electron microscope was used to observe autophagosome formation. Western blotting was also used to determine the degree of expression of related proteins in cells. Auranofin's tumor-suppressing properties were further tested in a xenograft tumor model of human SW620 CRC cells. Auranofin dramatically reduced the occurrence of CRC by decreasing the proliferation, migration, and invasion of CRC cells, according to our findings. Through a mTOR-dependent mechanism, auranofin inhibits the epithelial-mesenchymal transition (EMT) and induces autophagy in CRC cells. Finally, in-vivo tests revealed that auranofin suppressed tumor growth in xenograft mice while causing no harm. In summary, auranofin suppresses CRC cell growth, invasion, and migration. Auranofin inhibits the occurrence and progression of CRC by decreasing EMT and inducing autophagy in CRC cells via a mTOR-dependent mechanism. These findings suggest that auranofin could be a potential chemotherapeutic medication for the treatment of human CRC.

Assembly of Copper Alkynyl Clusters into Dimensionally Diverse Coordinated Polymers Mediated by Pyridine Ligands.

Surface ligands play crucial roles in modifying the properties of metal nanoclusters and stabilizing atomically precise structures, and also serve as vital linkers for constructing cluster-based coordination polymers. In this study, we present the results of the solvothermal synthesis of eight novel copper alkynyl clusters incorporating pyridine ligands using a one-pot method. The resulting compounds underwent characterization through elemental analysis, Fourier transform infrared (FT-IR) spectroscopy, powder X-ray diffraction (PXRD), and single-crystal X-ray diffraction (SCXRD). Our observations revealed that distinct pyridine ligands with varying lengths and coordination sites exert significant influence on the structure and dimensionality of the clusters. The structural diversity of these clusters led to the formation of one-dimensional (1D), two-dimensional (2D), or dimer arrangements linked by seven pyridine bridging ligands. Remarkably, these complexes exhibited unique UV-vis absorption and photoluminescence properties, which were influenced by the specific bridging ligand and structural framework. Furthermore, density functional theory (DFT) calculations demonstrated the capability of the conjugated system in the pyridine ligand to impact the band gap of clusters. This study not only unveils the inherent structural diversity in coordination polymers based on copper alkynyl clusters but also offers valuable insights into harnessing ligand engineering for structural and property modulation.

Hierarchical Hollow TiO2@Bi2WO6 with Light-Driven Excited Bi(3-x)+ Sites for Efficient Photothermal Catalytic CO2 Reduction.

Converting CO2 into valuable chemicals via sustainable energy sources is indispensable for human development. Photothermal catalysis combines the high selectivity of photocatalysis and the high yield of thermal catalysis, which is promising for CO2 reduction. However, the present photothermal catalysts suffer from low activity due to their poor light absorption ability and fast recombination of photogenerated electrons and holes. Here, a TiO2@Bi2WO6 heterojunction photocatalyst featuring a hierarchical hollow structure was prepared by an in situ growth method. The visible light absorption and photothermal effect of the TiO2@Bi2WO6 photocatalyst is promoted by a hierarchical hollow structure, while the recombination phenomenon is significantly mitigated due to the construction of the heterojunction interface and the existence of excited Bi(3-x)+ sites. Such a catalyst exhibits excellent photothermal performance with a CO yield of 43.7 µmol h-1 g-1, which is 15 and 4.7 times higher than that of pure Bi2WO6 and that of physically mixed TiO2/Bi2WO6, respectively. An in situ study shows that the pathway for the transformation of CO2 into CO over our TiO2@Bi2WO6 proceeds via two important intermediates, including COO- and COOH-. Our work provides a new idea of excited states for the design and synthesis of highly efficient photothermal catalysts for CO2 conversion.

CircPRELID2 functions as a promoter of renal cell carcinoma through the miR-22-3p/ETV1 cascade.

BACKGROUND: Emerging evidence has indicated that a number of circular RNAs (circRNAs) participate in renal cell carcinoma (RCC) carcinogenesis. Nevertheless, the activity and molecular process of circPRELID2 (hsa_circ_0006528) in RCC progression remain unknown. METHODS: CircPRELID2, miR-22-3p and ETS variant 1 (ETV1) levels were gauged by qRT-PCR. Effect of the circPRELID2/miR-22-3p/ETV1 axis was evaluated by detecting cell growth, motility, and invasion. Immunoblotting assessed related protein levels. The relationships of circPRELID2/miR-22-3p and miR-22-3p/ETV1 were confirmed by RNA immunoprecipitation (RIP), luciferase reporter or RNA pull-down assay. RESULTS: CircPRELID2 was up-regulated in RCC. CircPRELID2 silencing suppressed RCC cell growth, motility and invasion. Moreover, circPRELID2 silencing weakened M2-type macrophage polarization in THP1-induced macrophage cells. CircPRELID2 sequestered miR-22-3p, and circPRELID2 increased ETV1 expression through miR-22-3p. Moreover, the inhibitory impact of circPRELID2 silencing on RCC cell malignant behaviors was mediated by the miR-22-3p/ETV1 axis. Furthermore, circPRELID2 knockdown in vivo hampered growth of xenograft tumors. CONCLUSION: Our study demonstrates that circPRELID2 silencing can mitigate RCC malignant development through the circPRELID2/miR-22-3p/ETV1 axis, highlighting new therapeutic targets for RCC treatment.

Fractal Design of Hierarchical PtPd with Enhanced Exposed Surface Atoms for Highly Catalytic Activity and Stability.

Hierarchical assembly of arc-like fractal nanostructures not only has its unique self-similarity feature for stability enhancement but also possesses the structural advantages of highly exposed surface-active sites for activity enhancement, remaining a great challenge for high-performance metallic nanocatalyst design. Herein, we report a facile strategy to synthesize a novel arc-like hierarchical fractal structure of PtPd bimetallic nanoparticles (h-PtPd) by using pyridinium-type ionic liquids as the structure-directing agent. Growth mechanisms of the arc-like nanostructured PtPd nanoparticles have been fully studied, and precise control of the particle sizes and pore sizes has been achieved. Due to the structural features, such as size control by self-similarity growth of subunits, structural stability by nanofusion of subunits, and increased numbers of exposed active atoms by the curved homoepitaxial growth, h-PtPd displays outstanding electrocatalytic activity toward oxygen reduction reaction and excellent stability during hydrothermal treatment and catalytic process.

[Prediction of quality markers of Angong Niuhuang Pills based on LC-MS and pull-down with SPR chips].

Elucidating the quality markers(Q-markers) of traditional Chinese medicines is essential for understanding the mechanisms of action and promoting the rational use of traditional Chinese medicines as well as for developing traditional Chinese medicine-derived drugs. Studies have shown that surface plasmon resonance(SPR) is promising in this field. This study proposed a method based on pull-down with SPR chips to predict the Q-markers of Angong Niuhuang pills(AGNHP). Firstly, 71 main chemical components of AGNHP were analyzed by UPLC-Q-TOF-MS, and then network pharmacology was employed to predict the potential targets of AGNHP against stroke. Secondly, the STAT3 protein chip was constructed, and the extract of AGNHP was recovered by pull-down of the SPR system for STAT3 ligand. The potential active ingredients were collected, enriched, and identified as coptisine, palmatine, epiberberine, berberine, worenine, demethyleneberberine, jatrorrhizine, tetrahydrocoptisine, baicalein, and baicalin methyl ester. Next, the affinity constants of the 10 active ingredients were determined as 44.7, 44, 58.1, 51.3, 39.7, 32.1, 49.2, 69.1, 19.7, and 24.9 µmol·L~(-1), respectively. The molecular docking results showed that the 10 compounds could compete for binding with STAT3. This is the first report that SPR combined with UPLC-Q-TOF-MS is reliable and feasible for determining the active ingredients of AGNHP at the molecular level from complex systems. STAT3 could be used as a potential target for the biological quality evaluation of AGNHP.

Chiral Canoe-Like Pd0 or Pt0 Alloyed Copper Alkynyl Nanoclusters Display Near-Infrared Luminescence.

Alloying nanoclusters (NCs) has emerged as a widely explored and versatile strategy for tailoring tunable properties, facilitating in-depth atomic-level investigations of structure-property correlations. In this study, we have successfully synthesized six atomically precise copper NCs alloyed with Group 10 metals (Pd or Pt). Notably, the Pd0 or Pt0 atom situated at the center of the distorted hexagonal antiprism Pd0/Pt0@Cu12 cage, coordinated with twelve Cu+ and two tBuC≡C- ligands. Moreover, ligand exchange strategies demonstrated the potential for Cl- and Br- to replace one or two alkynyl ligands positioned at the top or side of the NCs. The chirality exhibited by these racemic NCs is primarily attributed to the involvement of halogens and a chiral (Pd/Pt)@Cu18 skeleton. Furthermore, all the NCs exhibit near-infrared (NIR) luminescence, characterized by emission peaks at 705-755 nm, lifetimes ranging from 6.630 to 9.662 µs, and absolute photoluminescence quantum yields (PLQYs) of 1.75 %-2.52 % in their crystalline state. The experimental optical properties of these NCs are found to be in excellent agreement with the results of theoretical calculations. These alloy NCs not only offer valuable insights into the synthesis of Pd0/Pt0-Cu alloy NCs, but also bridge the gap in understanding the structure-luminescence relationships of Pd0/Pt0-Cu molecules.

Down-regulation of HuR inhibits pathological angiogenesis in oxygen-induced retinopathy.

HuR (also known as ELAV1), a ubiquitous RNA-binding protein, is implicated in the pathogenesis of diverse diseases via the mechanism of post-transcriptional regulation. Whether it is involved in pathological angiogenesis in oxygen-induced retinopathy is not clear. In this study, we detected HuR expression was increased in the retina of mouse model of oxygen-induced retinopathy (OIR) as well as in vascular endothelial cells exposed to hypoxia. With gain-of-function and loss-of-function studies using adenovirus infection, we found HuR over-expression promoted while HuR knockdown inhibited the migration, proliferation and tube formation of vascular endothelial cells. Moreover, HuR regulated the expression of VEGFA in vascular endothelial cells. We also found the retinal pathological angiogenesis in mouse OIR model was greatly reduced with HuR knockdown using recombinant AAV expressing HuR specific shRNA which was administered by intravitreal injection. The results of this study suggest HuR is involved in pathological angiogenesis via regulating angiogenic behaviors of endothelial cells, providing a potential target for the treatment of retinopathy of prematurity.

LUNCRW: Prediction of potential lncRNA-disease associations based on unbalanced neighborhood constraint random walk.

Accumulating evidence suggests that long non-coding RNAs (lncRNAs) are associated with various complex human diseases. They can serve as disease biomarkers and hold considerable promise for the prevention and treatment of various diseases. The traditional random walk algorithms generally exclude the effect of non-neighboring nodes on random walking. In order to overcome the issue, the neighborhood constraint (NC) approach is proposed in this study for regulating the direction of the random walk by computing the effects of both neighboring nodes and non-neighboring nodes. Then the association matrix is updated by matrix multiplication for minimizing the effect of the false negative data. The heterogeneous lncRNA-disease network is finally analyzed using an unbalanced random walk method for predicting the potential lncRNA-disease associations. The LUNCRW model is therefore developed for predicting potential lncRNA-disease associations. The area under the curve (AUC) values of the LUNCRW model in leave-one-out cross-validation and five-fold cross-validation were 0.951 and 0.9486 ± 0.0011, respectively. Data from published case studies on three diseases, including squamous cell carcinoma, hepatocellular carcinoma, and renal cell carcinoma, confirmed the predictive potential of the LUNCRW model. Altogether, the findings indicated that the performance of the LUNCRW method is superior to that of existing methods in predicting potential lncRNA-disease associations.