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Zhiqing Zhong,1,* Hongyan Li,2,* Hongzhen Zhong,1 Tianbiao Zhou1 1Department of Nephrology, The Second Affiliated Hospital, Shantou University Medical College, 515041 Shantou, China; 2Department of Nephrology, Huadu District People’s Hospital of Guangzhou, Southern Medical University, 510800 Guangzhou, China *These authors contributed equally to this work Background: Long-term treatment programs with low toxicity represent a therapeutic challenge in lupus nephritis (LN). Although a therapeutic benefit of rituximab (RTX) has been reported in LN patients who have failed conventional treatment, the results are controversial. We aimed to assess the clinical efficacy and safety of RTX as a new immunosuppressive medicine in the treatment of LN with a meta-analysis. Methods: Based on predetermined criteria, PubMed, Embase, and Cochrane Library were used to identify the eligible studies. Cochrane Review Manager version 5.3 was applied to pool the data extracted from individual investigations and provide summary effect estimates. Results: Twenty-four studies with 940 patients were analyzed. In case series trials with specific LN assessment, the complete remission (CR) rate at 12 months was 35.9% (95% CI: 24.2%–49.5%), and total remission (TR: CR plus partial remission) was 73.4% (95% CI: 66.0%–79.7%). In controlled trials, RTX was associated with a higher probability of TR (OR =2.02, 95% CI: 1.23–3.32, P0.05). Additionally, RTX treatment significantly decreased proteinuria (mean difference: -2.79, 95% CI: -3.95 to -1.62, P

Prime compilation, i.e., the generation of all prime implicates or implicants (primes for short) of formulae, is a prominent fundamental issue for AI. Recently, the prime compilation for non-clausal formulae has received great attention. The state-of-the-art approaches generate all primes along with a prime cover constructed by prime implicates using dual rail encoding. However, the dual rail encoding potentially expands search space. In addition, constructing a prime cover, which is necessary for their methods, is time-consuming. To address these issues, we propose a novel two-phase method -- CoAPI. The two phases are the key to construct a cover without using dual rail encoding. Specifically, given a non-clausal formula, we first propose a core-guided method to rewrite the non-clausal formula into a cover constructed by over-approximate implicates in the first phase. Then, we generate all the primes based on the cover in the second phase. In order to reduce the size of the cover, we provide a multi-order based shrinking method, with a good tradeoff between the small size and efficiency, to compress the size of cover considerably. The experimental results show that CoAPI outperforms state-of-the-art approaches. Particularly, for generating all prime implicates, CoAPI consumes about one order of magnitude less time.