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Background Sarcopenia, a syndrome of progressive and generalised loss of skeletal muscle, which can increase the risk of postoperative complications of colorectal cancer, but its association with postoperative surgical site infections in colorectal cancer is still inconclusive. Objective To evaluate the association of abdominal CT-assessed sarcopenia with postoperative surgical site infections in patients undergoing colorectal cancer surgery. Methods Three hundred and twenty-eight colorectal cancer patients underwent radical surgery in Gastrointestinal Surgery, the First Affiliated Hospital of University of South China between July 2019 and December 2021 were selected. Clinical data were retrospectively collected through the electronic medical record system. Sarcopenia was diagnosed by the L3 skeletal muscle index (L3 SMI) assessed using abdominal CT. Surgical site infection was assessed using the Diagnostic Criteria of Nosocomial Infection (Trial) . Multivariate Logistic regression was applied to explore the influencing factors of postoperative surgical site infection. Results The incidence of surgical site infection in sarcopenia group was higher than that in non-sarcopenia group〔27.3% (12/44) vs 12.3% (35/284) 〕 (P

To determine the main factors affecting the migration, enrichment, and sources of arsenic in the shallow groundwater of the Pearl River Delta (PRD), clustering analysis was used to partition the study area and then analyze the abnormal distribution of arsenic and groundwater storage environment in each part area based on the data obtained from the investigation of groundwater pollution in the PRD region. The results showed, in the study area, arsenic was mainly represented by As(Ⅲ), and its concentration ranged from under the detection limit to 560 μg·L -1 . High-arsenic groundwater was mainly distributed in the plain area covered by Quaternary loose sediment, with the Shunde District in Foshan City having the highest, followed by Zhongshan City and central Guangzhou. The hydrochemical type of groundwater in the study area was mainly HCO 3 -Ca type water. The high-arsenic groundwater had the characteristics of high pH value; high concentrations of NH 4 + , Fe, and Mn; and a high permanganate index, in addition to a low concentration of NO 3 - . Based on scatter plot and factor analysis of various indicators of arsenic in groundwater and the impact of human activities on the groundwater environment of the PRD, it was concluded in this study that under the common influence of natural sedimentary environment and pollution input, a neutral or weak-alkaline-reducing environment, which was conducive to the occurrence of high-arsenic groundwater, was formed in the plain area. The role of microorganisms and the input of organic pollutants in the shallow groundwater led to the reduction and dissolution of arsenic-containing Fe-Mn oxide, resulting in the release of arsenic. The source of arsenic contamination in the groundwater was mainly the industrial pollution in Shunde and other areas in southern Foshan City.

Identification of chemical composition anomalies in groundwater is an important basis for establishing groundwater background values and quantifying the degree of influence of human activities. The main component anomaly identification by five kinds of hydrochemical diagrams has achieved good results in the past. However, this method is too complex to be used widely. In order to simplify the five kinds of hydrochemical diagrams, the Durov diagram was used to replace the five kinds of hydrochemical diagrams to identify the main component anomalies of groundwater, with the Liujiang basin employed as a verification example. The effects of seven kinds of anomaly identification methods combined by hydrochemical diagrams and mathematical statistics methods were compared, and the reliability of these methods were tested in the study. The result indicated that the combination of mathematical statistics and hydrochemical diagrams method can identify the groundwater anomalies better than either used alone. The method of the Pauta criterion+five kinds of hydrography diagrams and the Pauta criterion+the Durov diagram were the best to identify the major component anomalies of groundwater. This shows that the Durov diagram can effectively replace the five kinds of hydrochemical diagrams for anomaly recognition of groundwater, which not only preserves the scientificity of hydrochemical anomaly identification, but also greatly simplifies the process of calculation.