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Lactobacillus ruminis is a commensal motile lactic acid bacterium living in the intestinal tract of humans and animals. Although a few genomes of L. ruminis were published, most of them were animal derived. To explore the genetic diversity and potential niche-specific adaptation changes of L. ruminis, in the current work, draft genomes of 81 L. ruminis strains isolated from human, bovine, piglet, and other animals were sequenced, and comparative genomic analysis was performed. The genome size and GC content of L. ruminis on average were 2.16 Mb and 43.65%, respectively. Both the origin and the sampling distance of these strains had a great influence on the phylogenetic relationship. For carbohydrate utilization, the human-derived L. ruminis strains had a higher consistency in the utilization of carbon source compared to the animal-derived strains. L. ruminis mainly increased the competitiveness of niches by producing class II bacteriocins. The type of clustered regularly interspaced short palindromic repeats /CRISPR-associated (CRISPR/Cas) system presented in L. ruminis was mainly subtype IIA. The diversity of CRISPR/Cas locus depended on the high denaturation of spacer number and sequence, although cas1 protein was relatively conservative. The genetic differences in those newly sequenced L. ruminis strains highlighted the gene gains and losses attributed to niche adaptations.

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Cloud computing is significantly contributing to the development of smart Chinese medicine. The diagnosis and treatment of spleen and stomach diseases has been arousing great interest in smart Chinese medicine with cloud computing since many persons are suffering from spleen and stomach diseases. Currently, spleen and stomach diseases present some new characteristics with the dramatic changes in natural climate, social environment, and human living habits. Recently, deep learning, together with cloud computing techniques, has successfully used in medical image analysis and therefore it is the most promising model for diagnosing spleen and stomach disease in smart Chinese medicine. In this paper, we present a survey on deep learning models in medical image analysis for computer-aided diagnosis in modern medicine. Afterwards, we summarize the syndrome types of spleen and stomach diseases and furthermore analyze the causes and pathogenesis for each syndrome. Finally, we discuss the open challenges and research directions of deep learning models applicable to the computer-aided diagnosis of spleen and stomach diseases, which is expected to contribute to the development of smart Chinese medicine with cloud computing. KEYWORDS cloud computing, deep learning, smart Chinese medicine, spleen and stomach 1 INTRODUCTION Recently, cloud computing has made a great progress as various powerful computing techniques have been combined with advanced communication techniques. 1-3 The major objective of cloud computing is to provide powerful computational functions to big data processing and machine learning models. Actually, it has become the fundamental computing infrastructure for big data processing and large-scale machine learning algorithms in the past few years. 4,5 For example, cloud computing has extensively used to store large-scale data and improve the efficiency of data mining techniques like the possibilistic c-means algorithm. Particularly, cloud computing, together with various big data analytics algorithms and machine learning models, is significantly contributing to the development of smart city, which involves smart transportation, smart industry, and smart medicine, etc. As an important part of smart medicine, smart Chinese medicine has been receiving a lot of attention from many researchers in the communities of artificial intelligence and traditional Chinese medicine. 6 In detail, smart Chinese medicine integrates the advanced artificial intelligence techniques such as deep learning into traditional Chinese medicine to enhance the diagnosis and treatment of many difficult and complicated diseases like spleen and stomach diseases. In this paper, we focus on deep learning models for diagnosing spleen and stomach diseases. The diagnosis and treatment of spleen and stomach disease is one of the core topics in smart Chinese medicine since a large number of people suffer from spleen and stomach diseases. Particularly, more than 25% of the population suffers from chronical stomach disorder. Spleen and stomach diseases...