In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Input: Consider Input: Background: Clinical diagnosis of Japanese encephalitis is usually difficult due to non-specific signs at the early and acute stages of the infection. Virus isolation from peripheral blood is also not possible because of the short period and low level of transient viremia even in the acute stage of the disease. It is thus urgent to develop a feasible and convenient method for laboratory diagnosis of the infection. Objectives: To establish a newly designed molecular approach that can be used to detect intracellular Japanese encephalitis viral RNA in host cells. Study design: The method was firstly established and then was carried out to test its efficacy in cultured BHK-21 cells, subsequently in peripheral blood mononuclear cells (PBMCs) isolated from mice that have been inoculated with JE virus suspension. Results: In this study, in situ reverse-transcription loop-mediated isothermal amplification (in situ RT-LAMP) was established; which combines merits of recently developed loop-mediated isothermal amplification (LAMP) and in situ reverse-transcriptase polymerase chain reaction (in situ RT-PCR). Conclusions: The newly designed method can detect viral RNAs in peripheral blood mononuclear cells (PBMCs) in a short time with high sensitivity and efficiency. (W.-J. Chen). a These authors contributed equally to this study.

Output: In situ reverse-transcription loop-mediated isothermal amplification (in situ RT-LAMP) for detection of Japanese encephalitis viral RNA in host cells


Input: Consider Input: Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, using artificial neural network (ANN) method. The query protein sequence is dissected into overlapping short sequence segments. Ten different physicochemical features describe each amino acid; therefore nine residues long segment is represented as a point in a 90 dimensional space. The database of sequence segments with confirmed by experiments post-translational modification sites are used for training a set of ANNs. The efficiency of the classification for each type of modification and the prediction power of the method is estimated here using recall (sensitivity), precision values, the area under receiver operating characteristic (ROC) curves and leave-one-out tests (LOOCV). The significant differences in the performance for differently optimized neural networks are observed, yet the AMS 3.0 tool integrates those heterogeneous classification schemes into the single consensus scheme, and it is able to boost the precision and recall values independent of a PTM type in comparison with the currently available state-of-the art methods. The standalone version of AMS 3.0 presents an efficient way to indentify post-translational modifications for whole proteomes. The training datasets, precompiled binaries for AMS 3.0 tool and the source code are available at Additional file 1 Supplementary materials for the publication. Supplementary.xls contains detailed results of training and testing of AMS 3.0 tool in MS Excel file format. Additional file 2 PTM predictor software with training data. PTM_Archive.tar.gz includes the predictor software binaries together with all trained ANNs in tar.gz compressed form.

Output: AMS 3.0: prediction of post-translational modifications


Input: Consider Input: Previous studies indicated that fruit bats carry two betacoronaviruses, BatCoV HKU9 and BatCoV GCCDC1. To investigate the epidemiology and genetic diversity of these coronaviruses, we conducted a longitudinal surveillance in fruit bats in Yunnan province, China during 2009-2016. A total of 59 (10.63%) bat samples were positive for the two betacorona-viruses, 46 (8.29%) for HKU9 and 13 (2.34%) for GCCDC1, or closely related viruses. We identified a novel HKU9 strain, tentatively designated as BatCoV HKU9-2202, by sequencing the full-length genome. The BatCoV HKU9-2202 shared 83% nucleotide identity with other BatCoV HKU9 stains based on whole genome sequences. The most divergent region is in the spike protein, which only shares 68% amino acid identity with BatCoV HKU9. Quantitative PCR revealed that the intestine was the primary infection organ of BatCoV HKU9 and GCCDC1, but some HKU9 was also detected in the heart, kidney, and lung tissues of bats. This study highlights the importance of virus surveillance in natural reservoirs and emphasizes the need for preparedness against the potential spill-over of these viruses to local residents living near bat caves.


Output: Longitudinal Surveillance of Betacoronaviruses in Fruit Bats in Yunnan