Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, β-catenin, PPAR-γ, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.

Observations of extreme spatial rates of change of ionospheric electron content and the characterization strategy for mitigation applied by the U.S. local area augmentation system are shown. During extreme ionospheric activity, the gradient suffered by a global navigation satellite system user a few kilometers away from a ground reference station may reach as high as 425 mm of delay (at the GPS L1 frequency) per km of user separation. The method of data analysis that produced these results is described, and a threat space that parameterizes these possible threats to user integrity is defined. Certain configurations of user, reference station, global navigation satellite system satellite, and ionospheric storm-enhanced density may inhibit detection of the anomalous ionosphere by the reference station.

We investigate the generalization of semi-supervised learning (SSL) to diverse pixel-wise tasks. Although SSL methods have achieved impressive results in image classification, the performances of applying them to pixel-wise tasks are unsatisfactory due to their need for dense outputs. In addition, existing pixel-wise SSL approaches are only suitable for certain tasks as they usually require to use task-specific properties. In this paper, we present a new SSL framework, named Guided Collaborative Training (GCT), for pixel-wise tasks, with two main technical contributions. First, GCT addresses the issues caused by the dense outputs through a novel flaw detector. Second, the modules in GCT learn from unlabeled data collaboratively through two newly proposed constraints that are independent of task-specific properties. As a result, GCT can be applied to a wide range of pixel-wise tasks without structural adaptation. Our extensive experiments on four challenging vision tasks, including semantic segmentation, real image denoising, portrait image matting, and night image enhancement, show that GCT outperforms state-of-the-art SSL methods by a large margin. Our code available at: https://github.com/ZHKKKe/PixelSSL (i) .

Myasthenia gravis (MG) is an autoimmune-mediated disorder, the etiology of which involves both environmental factors and genetics. While the exact factors responsible for predisposition to MG remain elusive, it is hypothesized that gut microbiota play a critical role in the pathogenesis of MG. This study investigated whether gut microbiota are altered in MG patients by comparing the fecal microbiota profiles of MG patients to those of age- and sex-matched healthy controls. Phylotype profiles of gut microbial populations were generated using hypervariable tag sequencing of the V4 region of the 16S ribosomal RNA gene. Fecal short-chain fatty acids (SCFAs) were assessed by gas chromatographic analyses. The results demonstrated that, compared to the healthy cohort, the gut microbiota of the MG group was changed in terms of the relative abundances of bacterial taxa, with sharply reduced microbial richness, particularly in the genus Clostridium. The fecal SCFA content was significantly lower in the MG group. Furthermore, microbial dysbiosis was closely related to the levels of inflammatory biomarkers in the sera of MG patients.

Preeclampsia (PE) is one of the pregnancy metabolic diseases. Since Gut microbiota play important roles in the hosts' metabolism, it is necessary to investigate the gut microbiota in PE patients, so that some intestinal dysbiosis might be detected as a biomarker for PE early diagnosis or as a target for intervention. One hundred subjects were categorized into four groups: 26 PE patients in late pregnancy, healthy individuals in early, middle, and late pregnancy (26/24/24 women). Gut microbiota were analyzed by sequencing the V4 region of the 16S rDNA gene using Illuminal MiSeq. Data were analyzed by multivariate statistics. Bacteroidetes was the dominant bacterium (47.57-52.35%) in the pregnant women in South China. Tenericutes increased while Verrucomicrobia almost disappeared in late pregnancy. In the PE patients, there was an overall increase in pathogenic bacteria, Clostridium perfringens (p = 0.03) and Bulleidia moorei (p = 0.00) but a reduction in probiotic bacteria Coprococcus catus (p = 0.03). Our research suggests that there is a significant structural shift of the gut microbiota in PE patients, which might be associated with the occurrence and development of the disease. However, further studies are required to understand the underlying mechanisms.