A Novel Aging-Related Prognostic lncRNA Signature Correlated with Immune Cell Infiltration and Response to Immunotherapy in Breast Cancer.

Breast cancer (BC) is among the most universal malignant tumors in women worldwide. Aging is a complex phenomenon, caused by a variety of factors, that plays a significant role in tumor development. Consequently, it is crucial to screen for prognostic aging-related long non-coding RNAs (lncRNAs) in BC. The BC samples from the breast-invasive carcinoma cohort were downloaded from The Cancer Genome Atlas (TCGA) database. The differential expression of aging-related lncRNAs (DEarlncRNAs) was screened by Pearson correlation analysis. Univariate Cox regression, LASSO-Cox analysis, and multivariate Cox analysis were performed to construct an aging-related lncRNA signature. The signature was validated in the GSE20685 dataset from the Gene Expression Omnibus (GEO) database. Subsequently, a nomogram was constructed to predict survival in BC patients. The accuracy of prediction performance was assessed through the time-dependent receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, principal component analyses, decision curve analysis, calibration curve, and concordance index. Finally, differences in tumor mutational burden, tumor-infiltrating immune cells, and patients' response to chemotherapy and immunotherapy between the high- and low-risk score groups were explored. Analysis of the TCGA cohort revealed a six aging-related lncRNA signature consisting of MCF2L-AS1, USP30-AS1, OTUD6B-AS1, MAPT-AS1, PRR34-AS1, and DLGAP1-AS1. The time-dependent ROC curve proved the optimal predictability for prognosis in BC patients with areas under curves (AUCs) of 0.753, 0.772, and 0.722 in 1, 3, and 5 years, respectively. Patients in the low-risk group had better overall survival and significantly lower total tumor mutational burden. Meanwhile, the high-risk group had a lower proportion of tumor-killing immune cells. The low-risk group could benefit more from immunotherapy and some chemotherapeutics than the high-risk group. The aging-related lncRNA signature can provide new perspectives and methods for early BC diagnosis and therapeutic targets, especially tumor immunotherapy.

Virus Emissions from Toilet Flushing: Comparing Urine-Diverting to Mix Flush Toilets.

High levels of viruses can be found in human excrement from infected individuals, a fraction of which can be emitted from toilet flushing. Unlike the common mix flush toilet (MFT), the urine-diverting toilet (UDT) separates urine from the toilet water. Specific focus on urine-associated viruses is needed because the UDT can emit different levels of urine-associated and fecal-borne viruses and urine has different properties compared to feces that can affect emission levels (e.g., protein content). In this work, we quantified emission levels of surrogate bacteriophages for urine-associated and fecal-borne viruses, MS2 and T3, from flushing a UDT and an MFT, with and without protein in the water. Emission levels of viruses in the water of the UDT were lower than that of the MFT by up to 1.2-log10 and 1.3-log10 for T3 and MS2, respectively. If urine is completely diverted in the UDT, virus emissions can be reduced by up to 4-log10. Based on these results and typical levels in urine and feces, we estimate that up to 107 and 108 gene copies of human viruses per flush can be released from the UDT and MFT, respectively. Lower emissions observed with the UDT suggest reduced exposure to viruses from flushing the UDT.

On Optimal Differentially Private Mechanisms for Count-Range Queries.

While there is a large and growing body of literature on differentially private mechanisms for answering various classes of queries, to the best of our knowledge "count-range" queries have not been studied. These are a natural class of queries that ask "is the number of rows in a relation satisfying a given predicate between two integers θ1 and θ2?" Such queries can be viewed as a simple form of SQL "having" queries. We begin by developing a provably optimal differentially private mechansim for count-range queries for a single consumer. For count queries (in contrast to count-range queries), Ghosh et al. [9] have provided a differentially private mechanism that simultaneously maximizes utility for multiple consumers. This raises the question of whether such a mechanism exists for count-range queries. We prove that the answer is no - for count range queries, no such mechanism exists. However, perhaps surprisingly, we prove that such a mechanism does exist for "threshold" queries, which are simply count-range queries for which either θ1 = 0 or θ2 = +∞. Furthermore, we prove that this mechanism is a two-approximation for general count-range queries.

On Differentially Private Frequent Itemset Mining.

We consider differentially private frequent itemset mining. We begin by exploring the theoretical difficulty of simultaneously providing good utility and good privacy in this task. While our analysis proves that in general this is very difficult, it leaves a glimmer of hope in that our proof of difficulty relies on the existence of long transactions (that is, transactions containing many items). Accordingly, we investigate an approach that begins by truncating long transactions, trading off errors introduced by the truncation with those introduced by the noise added to guarantee privacy. Experimental results over standard benchmark databases show that truncating is indeed effective. Our algorithm solves the "classical" frequent itemset mining problem, in which the goal is to find all itemsets whose support exceeds a threshold. Related work has proposed differentially private algorithms for the top-k itemset mining problem ("find the k most frequent itemsets".) An experimental comparison with those algorithms show that our algorithm achieves better F-score unless k is small.