Effect of electroacupuncture of "Zusanli" (ST36) combined with capeOX on apoptosis and ferroptosis in nude mice with colorectal cancer. / 电针"足三里"联合capeOXæ–¹æ¡ˆå¯¹ç»“ç›´è‚ ç™Œè£¸é¼ è‚¿ç˜¤ç»†èƒžå‡‹äº¡å’Œé“æ­»äº¡çš„å½±å“.

OBJECTIVES: To investigate the impact of combined treatment of colorectal cancer (CRC) with electroacupuncture (EA) and capeOX (combined administration of fluorouracil, oxaliplatin and capecitabine) on the tumor volume, weight, spleen coefficient, apoptosis and ferroptosis of tumor tissue, and liver and kidney functions in nude mice with CRC, so as to explore its mechanisms underlying inhibiting CRC and alleviating toxic reactions of capeOX. METHODS: Female Balb/c nude mice were randomly assigned to 3 groups：model, capeOX, and EA+capeOX, with 8 nude mice in each group. The CRC model was established by subcutaneous injection of colon cancer cells at the right inguinal region. Nude mice of the capeOX group received intraperitoneal injection of oxaliplatin for 1 day and gavage of capecitabine from day 2 to day 7. EA (1 mA, 2 Hz/100 Hz) was applied to bilateral "Zusanli" (ST36) for 20 min, once daily for 7 days. During the interven-tion, the tumor volume and weight were measured every day, and at the end of intervention, the weight of the tumor tissue and spleen were measured, with tumor volume difference and spleen coefficient calculated. The proportion of apoptotic cells was measured by flow cytometry, and the contents of serum malondialdehyde (MDA), alanine aninotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), and creatinine (Cr) were detected using ELISA. The expression level of glutathione peroxidase 4 (GPX4, a key regulator for ferroptosis) protein of the tumor tissue was determined using Western blot. RESULTS: Compared to the model group, both the capeOX group and EA+capeOX group showed a decrease in the tumor volume (on day 3 and 4 in the capeOX group, and from day 2 to 7 in the EA+capeOX group) and body weight (P<0.05, on day 3 to 7 in the EA+capeOX group and on day 2 to 7 in the capeOX group), being evidently lower in the tumor volume on day 7 in the EA+capeOX than in the capeOX group (P<0.05), and evidently higher in the body weight on day 6 and 7 in the EA+capeOX group than in the capeOX group (P<0.05). In comparison with the model group, the tumor volume difference, tumor weight and spleen coefficient in both capeOX and EA+capeOX groups were significantly decreased (P<0.05), and MDA content in EA+capeOX group was significantly decreased (P<0.05), while the contents of ALT, BUN and Cr in the capeOX group, the proportion of apoptotic cells in both capeOX and EA+capeOX groups, and the GPX4 expression level in the EA+capeOX group were all significantly increased (P<0.05). The tumor volume difference, tumor weight, and contents of MDA, ALT, AST, BUN and Cr in the EA+capeOX group were markedly lower than in the capeOX group (P<0.05), while the spleen coefficient, proportion of apoptotic cells and GPX4 expression level in the EA+capeOX group were markedly higher than those in the capeOX group (P<0.05). CONCLUSIONS: EA of ST36 can enhance the effect of capeOX in inhibiting colorectal cancer growth in nude mice with CRC, which may be related with its functions in promoting tumor cell apoptosis, inhibiting ferroptosis, and modulating immune tolerance. In addition, EA can lower the side effects of capeOX in hematopoietic and immune, liver, and kidney functions.

[Research on land use structure optimization based on nonpoint source dissolved nitrogen load estimation in Shuaishui watershed].

Regional Nutrient Management (ReNuMa) was applied to estimate dissolved nitrogen (DN) load and perform source apportionment in Shuaishui watershed during 2000-2010. Satisfactory performance of ReNuMa was revealed by the E(ns) and R2 of greater than 0.9 in calibrating and validating streamflow and DN. The average nonpoint DN load in this watershed was 1.11 x 10(3) t x a(-1), with the load intensity of (0.75 +/- 0.22) t x km(-2). Among all the land uses, paddy field had the largest DN load intensity [28.60 kg x (hm2 x a)(-1)], while forest had the least [2.71 kg x (hm2 x a)(-1)]. Agricultural land (including paddy, grain, cash crop, tea plant and orchard) contributed most to DN load in Shuaishui watershed, indicating that the human dominated agricultural activities was the major contributor of nonpoint source pollution. Land use structure optimization for Shuaishui watershed in 2015 was conducted under the rule of reducing pollutants loads and maximizing the agricultural output value. The results demonstrated that agricultural monetary growth was accompanied with the increasing DN load at the optimal level, although output increment was higher than that of DN load.

Computational identification and analysis of the key biosorbent characteristics for the biosorption process of reactive black 5 onto fungal biomass.

The performances of nine biosorbents derived from dead fungal biomass were investigated for their ability to remove Reactive Black 5 from aqueous solution. The biosorption data for removal of Reactive Black 5 were readily modeled using the Langmuir adsorption isotherm. Kinetic analysis based on both pseudo-second-order and Weber-Morris models indicated intraparticle diffusion was the rate limiting step for biosorption of Reactive Black 5 on to the biosorbents. Sorption capacities of the biosorbents were not correlated with the initial biosorption rates. Sensitivity analysis of the factors affecting biosorption examined by an artificial neural network model showed that pH was the most important parameter, explaining 22%, followed by nitrogen content of biosorbents (16%), initial dye concentration (15%) and carbon content of biosorbents (10%). The biosorption capacities were not proportional to surface areas of the sorbents, but were instead influenced by their chemical element composition. The main functional groups contributing to dye sorption were amine, carboxylic, and alcohol moieties. The data further suggest that differences in carbon and nitrogen contents of biosorbents may be used as a selection index for identifying effective biosorbents from dead fungal biomass.

Cloning and expression in E. coli of an organic solvent-tolerant and alkali-resistant glucose 1-dehydrogenase from Lysinibacillus sphaericus G10.

The gene gdh encoding an organic solvent-tolerant and alkaline-resistant NAD(P)-dependent glucose 1-dehydrogenase (LsGDH) was cloned from Lysinibacillus sphaericus G10 and expressed in Escherichia coli. The recombinant LsGDH exhibited maximum activity at pH 9.5 and 50 °C. LsGDH displayed high stability at a wide pH ranging from 6.5 to 10.0 and was stable after incubation at 30 °C for 1 week in 25 mM sodium phosphate buffer (pH 6.5) in the absence or presence of NaCl. The activity of LsGDH was enhanced by Li+, Na+, K+, NH4+, Mg2+, and EDTA at pH 8.0. LsGDH exhibited high tolerance to 60% DMSO, 30% acetone, 30% methanol, 30% ethanol, 10% n-propanol, 30% isopropanol, 60% n-hexanol and 30% n-hexane. The relationship between stability and chain length of the alcohols fit a Gaussian distribution model (R2≥0.94), and demonstrated lowest enzyme stability in C4-alcohol. The results suggested that LsGDH was potentially useful for coenzyme regeneration in organic solvents or under alkaline conditions.

[Normal alkanes characteristic parameters of Jinzhou Bay surface sediments].

The concentration, composition and characteristic parameters of 18 surface sediment samples collected from Jinzhou Bay were studied. The samples were soxhlet-extracted with a mixture of 1: 1 (V/V) dichloromethane-hexane and analyzed by GC-MS after purification and concentration. Concentrations of n-alkanes vary from 1.9 to 4.2 microg x g(-1) with an average value of 2.6 microg x g(-1) dry weight. n-Alkanes distribution patterns of all positions were characterized by double peak-cluster, which means double sources from terrestrial and marine origin. The sum of nC25 to nC31 accounts for 20%-32% of the total n-alkanes, while the average value of L/H, C31/C19, TAR ratio are 0.67, 3.06, 2.02, respectively. All of these three indices suggest that the terrestrial contributions are higher than marine sources, especially for No. 2, 3 and 7 stations, which were influenced by riverinput nearby. Carbon Preference Index (CPI) ranges from 1.19 to 2.63 with an average value of 1.73, which is close to 1; the ratio of Pristane/Phytane (Pr/Ph) and unresolved/resolved compounds (U/R) range from 0.91 to 1.28, 2.2 to 4.3, respectively. All of these three parameters indicate that No. 13 and 15 stations are influenced by petroleum pollution. Comprehensive analysis of various parameters shows that Jinzhou Bay is threatened by both terrestrial inputs and petroleum hydrocarbons contaminations, which may relate to river discharging and port shipping in Jinzhou Bay.