Towards Graph-Aware Diffusion Modeling for Collaborative Filtering

Recovering masked feedback with neural models is a popular paradigm in recommender systems. Seeing the success of diffusion models in solving ill-posed inverse problems, we introduce a conditional diffusion framework for collaborative filtering that iteratively reconstructs a user's hidden preferences guided by its historical interactions. To better align with the intrinsic characteristics of implicit feedback data, we implement forward diffusion by applying synthetic smoothing filters to interaction signals on an item-item graph. The resulting reverse diffusion can be interpreted as a personalized process that gradually refines preference scores. Through graph Fourier transform, we equivalently characterize this model as an anisotropic Gaussian diffusion in the graph spectral domain, establishing both forward and reverse formulations. Our model outperforms state-of-the-art methods by a large margin on one dataset and yields competitive results on the others.Comment: 13 pages, 6 figure

Heparanase contributes to psoriatic lesions through crosstalk with IL-17 pathway

Psoriasis is a chronic inflammatory disease that is considered by a network of immunocytes and cytokines. Among all, Th17 cells–derived IL-17 is a critical driving factor in the pathogenesis of psoriasis. Recently, disruption of the extracellular matrix was found to be related to psoriasis progression. In the present study, we aimed to investigate the role of heparanase (HPSE) in psoriasis and the crosstalk with the IL-17 signalling pathway. Skin tissues from non-affected areas and psoriatic lesion areas before and after 12 weeks of IL-17 monoclonal antibody treatment of 30 psoriasis patients were collected. HaCaT cells were treated with different concentrations of IL-17 antibody, and HPSE in cells and medium were measured with Western blotting assay as well as enzyme-linked immunosorbent assay (ELISA). In the imiquimod (IMQ)-induced psoriasis model, IL-17 protein and mRNA expression levels were measured, and changes in the proportion of Th17 cells were detected via flow cytometry. Our data showed that HPSE is upregulated in lesion tissues isolated from psoriasis patients, and was inhibited by anti-IL-17 treatment. In cutaneous cells and IMQ-induced psoriasis model, IL-17 promoted the synthesis of HPSE. Inversely, HPSE was also found to increase the percentage of Th17 cells derived from CD4+ T cells. Finally, we found that the combined treatments of HPSE inhibitor and IL-17 monoclonal antibody produced therapeutic effects on IMQ-induced psoriasis model. Our findings revealed the new role of HPSE in the pathogenesis of psoriasis and also provided a target for combined treatment of psoriasis

Gut microbiota in preterm infants with late-onset sepsis and pneumonia: a pilot case-control study

Abstract Background Late-onset sepsis (LOS) and pneumonia are common infectious diseases, with high morbidity and mortality in neonates. This study aimed to investigate the differences in the gut microbiota among preterm infants with LOS, or pneumonia, and full-term infants. Furthermore, this study aimed to determine whether there is a correlation between intestinal pathogenic colonization and LOS. Methods In a single-center case‒control study, 16 S rRNA gene sequencing technology was used to compare gut microbiota characteristics and differences among the LOS group, pneumonia group, and control group. Results Our study revealed that the gut microbiota in the control group was more diverse than that in the LOS group and pneumonia group (P  0.05). Compared with the control group, the abundances of Akkermansia, Escherichia/Shigella, and Enterococcus increased, while the abundances of Bacteroides and Stenotrophomonas decreased in the LOS and pneumonia groups. The pathogenic bacteria in infants with LOS were consistent with the distribution of the main bacteria in the intestinal microbiota. An increase in Escherichia/Shigella abundance may predict a high risk of LOS occurrence, with an area under the curve (AUC) of 0.773. Conclusion Changes in the gut microbiota composition were associated with an increased risk of LOS and pneumonia. The dominant bacteria in the gut microbiota of the LOS group were found to be associated with the causative pathogen of LOS. Moreover, preterm infants exhibiting an elevated abundance of Escherichia/Shigella may be considered potential candidates for predicting the onset of LOS

Identification of HBV-MLL4 Integration and Its Molecular Basis in Chinese Hepatocellular Carcinoma

<div><p>To gain molecular insights of HBV integration that may contribute to HCC tumorigenesis, we performed whole transcriptome sequencing and whole genome copy number profiling of hepatocellular carcinoma (HCC) samples from 50 Chinese patients. We identified a total of 33 HBV-human integration sites in 16 of 44 HBV-positive HCC tissues, which were enriched in HBV genotype C-infected patients. In addition, significantly recurrent HBV-MLL4 integration (18%; 8/44) was found in this cohort of patients. Using long-range PCR and Sanger sequencing, we comprehensively characterized gDNA and cDNA sequences that encode for the HBV-MLL4 transcripts, and we revealed that HBV integration into <i>MLL4</i> exons led to much higher mRNA expression of <i>MLL4</i> than the integration into <i>MLL4</i> introns due to an alternative splicing mechanism. Moreover, the HBV-MLL4 integration occurred almost exclusively in <i>CTNNB1</i> and <i>TP53</i> wild-type patients. The integration was also associated with a distinct gene expression profile. In conclusion, this is the first report on the molecular basis of the <i>MLL4</i> integration driving <i>MLL4</i> over-expression. HBV-MLL4 integration occurred frequently in Chinese HCC patients, representing a unique molecular segment for HCC with HBV infection.</p></div

cDNA structure of HBV integration.

<p>Cartoon illustrating HBV-integrated cDNA structures. Full-length (315T, 316T, and 328T) and partially inserted cDNA sequences are shown for each sample, noted with alternative splicing isoforms for each transcript.</p

Genomic structures of HBV integration.

<p>HBV insertions are shown as circles marked with insertion positions. <i>MLL4</i> insertion sites are marked as purple (upstream) and blue arrows (downstream), noted with the exact integration position on human gene <i>MLL4</i>.</p

Clinical Characteristics of HCC Samples.

<p>Note:</p><p>^# Some patients’ clinic information is not complete, like HBV infection type, tumor size, tumor number, AFP level.</p><p>*P-value is significant. All P-values were calculated by fisher exact test between genotype C and B group.</p><p>Clinical Characteristics of HCC Samples.</p