With rapid advancements in machine learning and statistical models, ensuring the reliability of these models through accurate evaluation has become imperative. Traditional evaluation methods often ...rely on fully labeled test data, a requirement that is becoming increasingly impractical due to the growing size of datasets. In this work, we address this issue by extending existing work on active testing (AT) methods which are designed to sequentially sample and label data for evaluating pre-trained models. We propose two novel estimators: the Actively Improved Levelled Unbiased Risk (AILUR) and the Actively Improved Inverse Probability Weighting (AIIPW) estimators which are derived from nonparametric smoothing estimation. In addition, a model recalibration process is designed for the AIIPW estimator to optimize the sampling probability within the AT framework. We evaluate the proposed estimators on four real-world datasets and demonstrate that they consistently outperform existing AT methods. Our study also shows that the proposed methods are robust to changes in subsample sizes, and effective at reducing labeling costs.
Depicting the heterogeneity and functional characteristics of the tumor microenvironment (TME) is necessary to achieve precision medicine for bladder cancer (BLCA). Although classical molecular ...subtypes effectively reflect TME heterogeneity and characteristics, their clinical application is limited by several issues.
In this study, we integrated the Xiangya cohort and multiple external BLCA cohorts to develop a novel 5-methylcytosine (5mC) regulator-mediated molecular subtype system and a corresponding quantitative indicator, the 5mC score. Unsupervised clustering was performed to identify novel 5mC regulator-mediated molecular subtypes. The principal component analysis was applied to calculate the 5mC score. Then, we correlated the 5mC clusters (5mC score) with classical molecular subtypes, immunophenotypes, clinical outcomes, and therapeutic opportunities in BLCA. Finally, we performed pancancer analyses on the 5mC score.
Two 5mC clusters, including 5mC cluster 1 and cluster 2, were identified. These novel 5mC clusters (5mC score) could accurately predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic opportunities of BLCA. 5mC cluster 1 (high 5mC score) indicated a luminal subtype and noninflamed phenotype, characterized by lower anticancer immunity but better prognosis. Moreover, 5mC cluster 1 (high 5mC score) predicted low sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy, but high sensitivity to antiangiogenic therapy and targeted therapies, such as blocking the β-catenin, FGFR3, and PPAR-γ pathways.
The novel 5mC regulator-based subtype system reflects many aspects of BLCA biology and provides new insights into precision medicine in BLCA. Furthermore, the 5mC score may be a generalizable predictor of immunotherapy response and prognosis in pancancers.
Linear IgA bullous dermatosis (LABD) is an acquired autoimmune subepidermal blistering disorder. Diagnosis always relies on skin pathology and direct immunofluorescence (DIF), with typical linear ...deposits of IgA along the basement membrane zone (BMZ). The typical clinical manifestation is tense bullae arranged like the “string of pearls” companied with severe pruritus. Dapsone is often considered first-line therapy for LABD, and it is necessary to test the HLA-B*1301 gene to prevent the occurrence of dapsone-induced hypersensitivity syndrome (DHS). Here we report a case of LABD resistant to corticosteroid and sulfasalazine, while waiting for HLA-B*1301 gene test results, dupilumab was used to control severe pruritus.
Emerging preclinical findings have indicated that steroid hormone receptor signaling plays an important role in bladder cancer outgrowth. In particular, androgen-mediated androgen receptor signals ...have been shown to correlate with the promotion of tumor development and progression, which may clearly explain some sex-specific differences in bladder cancer. This review summarizes and discusses the available data, suggesting the involvement of androgens and/or the androgen receptor pathways in urothelial carcinogenesis as well as tumor growth. While the precise mechanisms of the functions of the androgen receptor in urothelial cells remain far from being fully understood, current evidence may offer chemopreventive or therapeutic options, using androgen deprivation therapy, in patients with bladder cancer.
YTH N6-methyladenosine RNA binding protein 1 (YTHDF1) has been indicated proven to participate in the cross-presentation of tumor antigens in dendritic cells and the cross-priming of CD8+ T cells. ...However, the role of YTHDF1 in prognosis and immunology in human cancers remains largely unknown.
All original data were downloaded from TCGA and GEO databases and integrated
R 3.2.2. YTHDF1 expression was explored with the Oncomine, TIMER, GEPIA, and BioGPS databases. The effect of YTHDF1 on prognosis was analyzed
GEPIA, Kaplan-Meier plotter, and the PrognoScan database. The TISIDB database was used to determine YTHDF1 expression in different immune and molecular subtypes of human cancers. The correlations between YTHDF1 expression and immune checkpoints (ICP), tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human cancers were analyzed
the SangerBox database. The relationships between YTHDF1 expression and tumor-infiltrated immune cells were analyzed
the TIMER and GEPIA databases. The relationships between YTHDF1 and marker genes of tumor-infiltrated immune cells in urogenital cancers were analyzed for confirmation. The genomic alterations of YTHDF1 were investigated with the c-BioPortal database. The differential expression of YTHDF1 in urogenital cancers with different clinical characteristics was analyzed with the UALCAN database. YTHDF1 coexpression networks were studied by the LinkedOmics database.
In general, YTHDF1 expression was higher in tumors than in paired normal tissue in human cancers. YTHDF1 expression had strong relationships with prognosis, ICP, TMB, MSI, and neoantigens. YTHDF1 plays an essential role in the tumor microenvironment (TME) and participates in immune regulation. Furthermore, significant strong correlations between YTHDF1 expression and tumor immune-infiltrated cells (TILs) existed in human cancers, and marker genes of TILs were significantly related to YTHDF expression in urogenital cancers. TYHDF1 coexpression networks mostly participated in the regulation of immune response and antigen processing and presentation.
YTHDF1 may serve as a potential prognostic and immunological pan-cancer biomarker. Moreover, YTHDF1 could be a novel target for tumor immunotherapy.
In order to fully use Internet of things to solve the agricultural fine production, fertilizer, fine and precise control, full traceability and other bottlenecks, and to solve the quality safety of ...agricultural products from the source and agriculture environmental pollution, a networking application system for modern agriculture is constructed, and networking intelligent gateway based on open source hardware is designed and developed, which realizes the video monitoring function based on motion detection. In addition, basic cloud platform system for modern agriculture network monitoring system is designed and achieved. Based on the RESTful interface service system provided by cloud platform, ExtJs client technology and WeChat re applied in the development and realization of the Demo system of an application layer. As a result, it shows part of application assumption of agricuture network monitoring system, and designs the big data processing and analysis module. What’s more, the Hadoop platform is used to achieve massive data processing produced by applications of Internet of things, and combined with machine learning technology, the corresponding model is established. It is concluded that the best solution is given such as crop variety selection, production and cultivation management and time to market.
Pemphigus foliaceus (PF) is a superficial form of pemphigus. Treatment options for PF resemble pemphigus vulgaris, including glucocorticosteroids, immunosuppressive agents and rituximab et al. These ...treatment approaches can effectively improve the condition but may also be accompanied by high risks of side effects. Therefore, it is crucial to find a safe and effective treatment options for patients with PF. It will not only benefit/be necessary for patients who refuse glucocorticosteroids or immunosuppressive agents treatments, but also for patients who cannot be treated with glucocorticosteroids or immunosuppressive agents. Herein, we reported a case of PF that was treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. A 54-year-old woman presented with itchy erythema and erosions on the trunk for more than 1 month. The patient applied mometasonefuroate cream without improvement for a duration of two weeks. The past history of diabetes mellitus and atrophic gastritis was reported. Physical examination revealed scattered erythematous macules and erosions on the trunk. No mucosal involvement was observed. The condition was assessed by the pemphigus disease area index and numerical rating scale, with baseline scores of 7 and 8, respectively. Histopathological examination showed acantholysis and intraepithelial blister. Direct immunofluorescence revealed the presence of IgG and Complement 3 deposition between the acanthocytes with the reticular distribution. Based on enzyme-linked immunosorbent assay results, the levels of Dsg1 and Dsg3 antibodies were 28.18 and 0.26 kU/L respectively. The diagnosis of PF was made. This patient was successfully treated with apremilast without systemic glucocorticosteroids or immunosuppressive agents. The patient has continued with apremilast 30mg once daily for maintenance and no adverse events related to apremilast such as gastrointestinal side effects were observed during the 9-month follow-up period. In conclusion, apremilast therapy without systemic glucocorticosteroids nor immunosuppressive agents might provide an effective alternative to management of mild PF without obvious side effect.
Sub-cohort sampling designs such as a case-cohort study play a key role in studying biomarker-disease associations due to their cost effectiveness. Time-to-event outcome is often the focus in cohort ...studies, and the research goal is to assess the association between the event risk and risk factors. In this paper, we propose a novel goodness-of-fit two-phase sampling design for time-to-event outcomes when some covariates (e.g., biomarkers) can only be measured on a subgroup of study subjects.
Assuming that an external model, which can be the well-established risk models such as the Gail model for breast cancer, Gleason score for prostate cancer, and Framingham risk models for heart diseases, or built from preliminary data, is available to relate the outcome and complete covariates, we propose to oversample subjects with worse goodness-of-fit (GOF) based on an external survival model and time-to-event. With the cases and controls sampled using the GOF two-phase design, the inverse sampling probability weighting method is used to estimate the log hazard ratio of both incomplete and complete covariates. We conducted extensive simulations to evaluate the efficiency gain of our proposed GOF two-phase sampling designs over case-cohort study designs.
Through extensive simulations based on a dataset from the New York University Women's Health Study, we showed that the proposed GOF two-phase sampling designs were unbiased and generally had higher efficiency compared to the standard case-cohort study designs.
In cohort studies with rare outcomes, an important design question is how to select informative subjects to reduce sampling costs while maintaining statistical efficiency. Our proposed goodness-of-fit two-phase design provides efficient alternatives to standard case-cohort designs for assessing the association between time-to-event outcome and risk factors. This method is conveniently implemented in standard software.
The life-science community faces a major challenge in handling "big data", highlighting the need for high quality infrastructures capable of sharing and publishing research data. Data preservation, ...analysis, and publication are the three pillars in the "big data life cycle". The infrastructures currently available for managing and publishing data are often designed to meet domain-specific or project-specific requirements, resulting in the repeated development of proprietary solutions and lower quality data publication and preservation overall.
e!DAL is a lightweight software framework for publishing and sharing research data. Its main features are version tracking, metadata management, information retrieval, registration of persistent identifiers (DOI), an embedded HTTP(S) server for public data access, access as a network file system, and a scalable storage backend. e!DAL is available as an API for local non-shared storage and as a remote API featuring distributed applications. It can be deployed "out-of-the-box" as an on-site repository.
e!DAL was developed based on experiences coming from decades of research data management at the Leibniz Institute of Plant Genetics and Crop Plant Research (IPK). Initially developed as a data publication and documentation infrastructure for the IPK's role as a data center in the DataCite consortium, e!DAL has grown towards being a general data archiving and publication infrastructure. The e!DAL software has been deployed into the Maven Central Repository. Documentation and Software are also available at: http://edal.ipk-gatersleben.de.
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