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We examined characteristics of chest CT during different time periods for patients with coronavirus disease 2019 (COVID-19) pneumonia in Huizhou, China. This study included 56 COVID-19 patients having abnormal CT acquired between January 22 and March 3, 2020. Scans of 56 patients were classified into 4 groups (Group 1-Group 4) based on the date on which scan was obtained at the 1st, 2nd, 3rd week and longer than 3 weeks after illness onset. Forty-five patients with follow-up scans were categorized into 4 groups according to extents that lesions reduced. GGO was prevalent in Groups 1-4 (58.1-82.6%). Consolidation was the more common in Group 2 (26.2%) and then declined in Group 3 and 4 (20.0%; 9.7%). The highest frequency of fibrous stripes occurred in Group 3 (46.7%) and then decreased to 35.5% in Group 4. CT scores were higher for Group 2 than others. Among 45 follow-up patients, 11 (24.4%) of them recovered with lesions reducing ≥75% and had shorter hospital durations compared with others. There were temporal patterns of lung abnormalities in COVID-19 patients, with the highest extent of lesion involvement occurring in the 2nd week. Isolation and review are required for COVID-19 patients who have been discharged from hospital.

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Kangtaizhi granule (KTZG) is a Chinese medicine compound prescription and has been proven to be effective in nonalcoholic fatty liver disease (NAFLD) treatment clinically. However, the underlying mechanisms under this efficacy are rather elusive. In the present study, network pharmacology and HPLC analysis were performed to identify the chemicals of KTZG and related target pathways for NAFLD treatment. Network pharmacology screened 42 compounds and 79 related targets related to NAFLD; HPLC analysis also confirmed six compounds in KTZG. Further experiments were also performed. In an in vivo study, SD rats were randomly divided into five groups: control (rats fed with normal diet), NAFLD (rats fed with high-fat diet), and KTZG 0.75, 1.5, and 3 groups (NAFLD rats treated with KTZG 0.75, 1.5, and 3 g/kg, respectively). Serum lipids were biochemically determined; hepatic steatosis and lipid accumulation were evaluated with HE and oil red O staining. In an in vitro study, HepG2 cells were incubated with 1 mM FFA to induce lipid accumulation with or without KTZG treatment. MTT assay, intracellular TG level, oil red O staining, and glucose uptake in cells were detected. Western blotting and immunohistochemical and immunofluorescence staining were also performed to determine the expression of lipid-related genes PPAR-γ, SREBP-1, p-AKT, FAS, and SIRT1 and genes in the AMPK/mTOR signaling pathway. In high-fat diet-fed rats, KTZG treatment significantly improved liver organ index and serum lipid contents of TG, TC, LDL-C, HDL-C, ALT, and AST significantly; HE and oil red O staining also showed that KTZG alleviated hepatic steatosis and liver lipid accumulation. In FFA-treated HepG2 cells, KTZG treatment decreased the intracellular TG levels, lipid accumulation, and attenuated glucose uptake significantly. More importantly, lipid-related genes PPAR-γ, SREBP-1, p-AKT, FAS, and SIRT1 expressions were ameliorated with KTZG treatment in high-fat diet-fed rats and FFA-induced HepG2 cells. The p-AMPK and p-mTOR expressions in the AMPK/mTOR signaling pathway were also modified with KTZG treatment in high-fat diet-fed rats and HepG2 cells. These results indicated that KTZG effectively ameliorated lipid accumulation and hepatic steatosis to prevent NAFLD in high-fat diet-fed rats and FFA-induced HepG2 cells, and this effect was associated with the AMPK/mTOR signaling pathway. Our results suggested that KTZG might be a potential therapeutic agent for the prevention of NAFLD.

To verify the clinical therapeutic effects on shoulder joint pain of rotator cuff injury treated with electroacupuncture (EA) and Mulligan's mobilization.A total of 120 patients of shoulder joint pain of rotator cuff injury were randomized into an EA group, a rehabilitation group and a combined therapy group, 40 cases in each one. In the EA group, EA was applied to Jianzhen (SI 9), Jianliao (TE 14), Jianyu (LI 15), Tianzong (SI 11), Jianqian (extra) and Binao (LI 14) in the affected side. Of these acupoints, Jianliao (TE 14) and Jianyu (LI 15), Jianzhen (SI 9) and Tianzong (SI 11) were stimulated withVAS scores were all reduced, UCLA scores increased and ROM improved after treatment as compared with those before treatment in the patients of the three groups (allThe combined therapy of EA and Mulligan's mobilization relieves shoulder joint pain of rotator cuff injury, better than the simple application of either EA or Mulligan's mobilization.

In this paper, relations between a multiplicative consistent interval fuzzy preference relation and an additive consistent interval fuzzy preference relation are established. Based on the new relations, a new method (Algorithm 3) is proposed to derive interval weights by transforming a multiplicative consistent interval fuzzy preference relation into an additive consistent interval fuzzy preference relation, collecting additive consistent information (Algorithm 2), transforming back into multiplicative consistent information and calculating the interval weights by Eq. (20). Finally, two numerical examples are given to illustrate the new method.

A multiple attributes decision making model is wildly used and studied. The goal of multiple attributes decision making problems is to select a perfect alternative. The existed methods pay attention to rank the alternatives and suggest a best alternative to decision makers. However, there is risk hiding on the priority order. When accepting the order, decision makers undertake the risk at the same time. It is unknown for decision makers. To show the advantages and disadvantages for each alternative, and the risk of a selection, we propose a possibility priority degree analyzing model. With this model, decision makers can be aware of the possibility of priority degree, similar degree and the priority risk, and then make decision. It will effectively reduce the decision risk and improve the decision efficiency.

In this paper, a new method is proposed to obtain the interval weights from interval reciprocal comparison matrices. Firstly, some basic theorems about consistent interval reciprocal comparison matrix are presented. Then, based on the theorems, an algorithm is proposed to approximate a column of approximated intervals which contains all of the consistent information. Furthermore, another algorithm is presented to obtain the interval weights based on the column of intervals. Finally, two examples are provided to illustrate the validity and practicality of the proposed method.