Development of fecal microbial diagnostic marker sets of colorectal cancer using natural language processing method.

BACKGROUND: Cancer screening and early detection greatly increase the chances of successful treatment. However, most cancer types lack effective early screening biomarkers. In recent years, natural language processing (NLP)-based text-mining methods have proven effective in searching the scientific literature and identifying promising associations between potential biomarkers and disease, but unfortunately few are widely used. METHODS: In this study, we used an NLP-enabled text-mining system, MarkerGenie, to identify potential stool bacterial markers for early detection and screening of colorectal cancer. After filtering markers based on text-mining results, we validated bacterial markers using multiplex digital droplet polymerase chain reaction (ddPCR). Classifiers were built based on ddPCR results, and sensitivity, specificity, and area under the curve (AUC) were used to evaluate the performance. RESULTS: A total of 7 of the 14 bacterial markers showed significantly increased abundance in the stools of colorectal cancer patients. A five-bacteria classifier for colorectal cancer diagnosis was built, and achieved an AUC of 0.852, with a sensitivity of 0.692 and specificity of 0.935. When combined with the fecal immunochemical test (FIT), our classifier achieved an AUC of 0.959 and increased the sensitivity of FIT (0.929 vs. 0.872) at a specificity of 0.900. CONCLUSIONS: Our study provides a valuable case example of the use of NLP-based marker mining for biomarker identification.

What Works for Controlling Meningitis Outbreaks: A Case Study from China.

The meningococcal meningitis (MM) vaccine reduces the incidence of MM significantly; however, outbreaks still occur in communities with high vaccine coverage. We aimed to analyze the driving factors of infection from a community outbreak. A total of 266 children aged 9 to 15 years old from the three junior high schools of Tongzi county were identified. We documented infection cases using laboratory tests and analyzed attack rates, infection rates and risk factors for transmission. The index case in School A was identified, and the attack rate in School A was 0.03%. Children showed a significantly low infection rate of MenC in School A (13.2% vs. 19.5% in total children, p = 0.002), while exhibiting significantly high infection rates of MenA in School B (44.1% vs. 24.8% in total children, p < 0.001) and MenB in School C (11.1% vs. 4.1% in total children, p = 0.015). The infection rate of MenA for females (30.0%) was higher (p = 0.055) than for males (19.9%). In School A, 63.19% of children were vaccinated against MenC, while in School B the rate was 42.65% and in School C, it was 59.26%. Three male MenC infection cases were detected as breakthrough infection cases in addition to the index case. The findings suggest that the current full-course immunization has limited long-term effectiveness and is inefficient in preventing the transmission of MM among older children.

Two Stable Heterometal-MOFs as Highly Efficient and Recyclable Catalysts in the CO2 Coupling Reaction with Aziridines.

Two stable heterometal-organic frameworks, {Na[LnCo(DATP)2 (Ac)(H2 O)](NO3 )⋅DMA⋅11 H2 O}n (Ln=Er(1) and Yb(2)), have been prepared with H2 DATP (4'-(3,5-dicarboxyphenyl)-2,2':6',2'''-terpyridine) as organic building block. These two isostructural compounds featuring two-dimensional layer architectures possess outstanding thermal stabilities and excellent chemical stabilities in common organic solvents and different acid/base solutions with pH range changing from 1 to 13. Moreover, compounds 1 and 2 serving as heterogeneous catalysts can efficiently catalyse the CO2 fixation reaction with various aziridines to result in corresponding oxazolidinones at 70 °C. Importantly, a good recyclable performance of 1 for at least 10 cycles is observed based on the experimental results, which are further confirmed by PXRD, TGA and ICP analyses.

Solvent-dependent variations of both structure and catalytic performance in three manganese coordination polymers.

Three new manganese 4'-(3,5-dicarboxyphenyl)-2,2':6',2'''-terpyridine (H2DATP) metal-organic framework materials have been generated through regulating the ratios of a binary solvent mixture (DMA/H2O) under solvothermal conditions. Compound 1 {[Mn2(DATP)(HDATP)(H2O)4](OH)·10H2O}n displaying a one-dimensional (1D) chainlike structure was crystallized from the DMA/H2O mixture with a molar ratio of 1 : 1, while the two-dimensional (2D) layer species, {[Mn(DATP)(H2O)]·2H2O}n (2) was produced by increasing the ratio of DMA/H2O to 5 : 1. Interestingly, the crystallization in pure DMA yields a three-dimensional (3D) interpenetrating network {[Mn(DATP)]·4H2O}n (3), featuring higher solvent stability and pH stability than compounds 1 and 2. It is proved that solvent not only influences the structural transformation process of crystals but also has a significant effect on their properties. These three compounds present different catalytic performances in the CO2 cycloaddition to epoxides with various substituent groups into corresponding cyclic carbonates, and only 3 can serve as an efficient and recyclable catalyst at mild temperature.