Modulating Heat Shock Proteins 70 and 90 Expression by Low Power Laser Irradiation (635nm and 780nm) in Jurkat E6.1 T-lymphocyte Leukemia Cell Line

Introduction: Heat shock proteins (HSPs) are molecular chaperones involved in protein folding, stability and turnover, and due to their role in cancer progression, the effect of low power laser irradiation (LPLI) on the expression of HSP70 and HSP90 in Jurkat E6.1 T-lymphocyte leukemia (JELT) cell line was investigated in vitro.Methods: JETL cells were irradiated with LPLI at 635nm and 780m wavelengths (energy density 9.174 J/cm2), and assessed for the expression of HSP70 and HSP90 by flow cytometry after 24, 48 and 72 incubation time periods (ITPs).Results: At 24 hours ITP post-irradiation, control cultures showed that 10.7% of cells expressed HSP70, while LPLI cultures at 635nm and 780nm manifested a higher expression (32.1and 21.3%, respectively), and the difference was significant (P ≤ 0.05). However, at 48 hours ITP, the three means were decreased but approximated (5.6, 4.9 and 6.2%, respectively), while at 72 hours ITP, they were markedly increased (45.2, 76.5 and 66.7%, respectively). In contrast, HSP90 responded differently to LPLI. At 24 hours ITP, control cultures and 780nm cultures showed a similar expression (55.9 and 55.9%, respectively), but both means were significantly higher than that of 635nm cultures (24.0%). No such difference was observed at 48 hours ITP, and at 72 hours ITP, control cultures and 635nm cultures shared approximated means (31.7 and 35.6%, respectively); but both means were significantly higher than the observed mean in 780nm cultures (15.2%).Conclusion: The results highlighted that HSP70 and HSP90 expression responded differently to LPLI in JETL cells; an observation that may pave the way for further investigations in malignant cells

Cell Cycle Response to Low Power Laser Irradiation in Jurkat E6.1 T-lymphocyte Cell Line

Low-power laser irradiation (LPLI) effects on cell cycle progression in Jurkat E6.1 T-lymphocyte leukemia (JETL) cells were examined in vitro at 635nm (visible) and 780nm (near infrared) wavelengths. The cells were exposed to an energy density of 9.174 J/cm2, and then examined 24, 48 and 72 hours post-irradiation. Cell cycle analysis by flow cytometry at 24 hours post-irradiation revealed that the three phases (G0/G1, S and G2/M) of cultured JETL cells showed different percentages in LPLI (635nm and 780nm) and unirradiated cultures, but S phase cells were observed with significant increased percentages (55.6 and 55.7%, respectively) compared to controls (37.3%). At 48 hours, again cells at S phase were observed with much higher percentages than control cells (48.2 and 51.5% vs. 29.9%, respectively), and the difference was significant (P ? 0.05). At 72 hours, the S phase cells were also observed with much higher percentages than control cells (33.1 and 32.6% vs. 21.3%, respectively), and the difference was also significant (P ? 0.05). Keywords: Cell cycle, Jurkat E6.1 T-lymphocyte leukemia cell line, Low-power laser irradiation

Multiphoton fluorescence lifetime imaging microscopy reveals free-to-bound NADH ratio changes associated with metabolic inhibition

Measurement of endogenous free and bound NAD(P)H relative concentrations in living cells isa useful method for monitoring aspects of cellular metabolism, because the NADH/NAD⁺ reduction-oxidation pair is crucial for electron transfer through the mitochondrial electron transport chain. Variations of free and bound NAD(P)H ratio are also implicated in cellular bioenergetic and biosynthetic metabolic changes accompanying cancer. This study uses two-photon fluorescence lifetime imaging microscopy (FLIM) to investigate metabolic changes in MCF10A premalignant breast cancer cells treated with a range of glycolysis inhibitors: namely, 2 deoxy-D-glucose, oxythiamine, lonidamine, and 4-(chloromethyl) benzoyl chloride, as well as the mitochondrial membrane uncoupling agent carbonyl cyanide m-chlorophenylhydrazone. Through systematic analysis of FLIM data from control and treated cancer cells, we observed that all glycolytic inhibitors apart from lonidamine had a slightly decreased metabolic rate and that the presence of serum in the culture medium generally marginally protected cells from the effect of inhibitors. Direct production of glycolytic L-lactate was also measured in both treated and control cells. The combination of these two techniques gave valuable insights into cell metabolism and indicated that FLIM was more sensitive than traditional biochemical methods, as it directly measured metabolic changes within cells as compared to quantification of lactate secreted by metabolically active cells.13 page(s

Different bioindicators measured at different spatial scales vary in their response to agricultural intensity

Ecologically, potential bioindicator taxa operate at different scales within agricultural ecosystems, and thereby provide a means to investigate the influence of changing management practice on biological diversity at different scales within the agro-ecosystem. Surveys of grassland plant species at field level, parasitoid Hymenoptera at the field and farm scale, and bird populations and habitats at farm scale were carried out on 119 grass-based farms across three regions in the Republic of Ireland. In addition, habitat richness and aquatic macroinvertebrates were quantified at landscape scale. Agricultural intensity on the surveyed farms was quantified by mean farm stocking rate, calculated as livestock units per ha (LU/ha), and generalised linear mixed models used to evaluate relationships between stocking rate and the incidence of chosen bioindicator groups. Field scale bioindicators (plant species richness and parasitoid taxon richness and abundance) were negatively associated with mean farm stocking rate. Over much of its observed range, mean farm stocking rate was positively associated with total bird species richness and abundance, and the species richness and abundance of farmland bird indicator species recorded in the winter season. However, these relationships were quadratic, and above a relatively high upper limit of 2.5–3.5 LU/ha, further increase in farm stocking rate had a negative influence. Results demonstrate that different bioindicators measured at different spatial scales vary in their response to agricultural intensity. The lack of a consistent bioindicator response to farm stocking rate suggests that within predominantly farmed regions, maximising biodiversity requires a careful targeting and monitoring with bioindicator taxa that are informative of influences at relevant operational scales. The insights provided may then be much more informative for the design and implementation of agri-environment measures that maximise biodiversity within farmed landscapes.DG 19/11/201

Evolutionary success of prokaryotes

How can the evolutionary success of prokaryotes be explained ? How did they manage to survive conditions that have fluctuated, with drastic events over 3.5 billion years ? Which significant metabolisms and mechanisms have appeared over the course of evolution that have permitted them to survive the most inhospitable conditions from the physicochemical point of view ? In a 'Red Queen Race', prokaryotes have always run sufficiently fast to adapt to constraints imposed by the environment and the other living species with which they have established interactions. If the criterion retained to define the level of evolution of an organism is its capacity to survive and to yield the largest number of offsprings, prokaryotes must be considered highly evolved organisms