The morphology of the porous silicon was measured by scanning ele

The morphology of the porous silicon was measured by scanning electron microscopy (SEM) using a FEI XL30 SEM (FEI, Hillsboro, OR, USA) operating in secondary electron imaging mode. To avoid sample charging MGCD0103 price anomalies, the porous Si samples were metalized with a thin layer of gold prior to the SEM analysis. The pore size and the porosity oscillations of the rugate filter structure were evaluated with this analysis. Measurement of

porous silicon degradation The pSi degradation was studied using a custom-designed transparent flow cell system with a total volume of 4.5 mL (including connections). The 1:1 (v/v) ethanol 0.5 M carbonate/borate buffer solution (pH 10) was flowed in at the bottom of the sample using a peristaltic pump at a rate of 10 μL/s and room temperature (20 ± 1°C). Ethanol was included in the buffer to improve the permeation of solution into the pores and reduce the formation of bubbles that could affect the subsequent image analysis. The degradation of the fpSi and pSi-ch samples was monitored by obtaining reflectance spectra (spectrophotometer) and photographs P005091 cell line (digital camera) every 5 min through the front cover of the flow cell until after complete degradation had occurred (300 min). To obtain both measurements

repeatably during the same experiment, the optical paths for the reflectance probe and the camera were located in front of the flow cell along the sample surface normal as is shown in Figure 1. The sample was illuminated by means of a diffuse axial illuminator coupled to a Fiber-lite MI-150 (Dolan Jenner, Boxborough, MA, USA) light source with an approximate color temperature of 3,000 K mounted between the flow cell and the camera. A beam splitter (Thorlabs CM1-BS2

Cube-Mounted Non-Polarizing Beamsplitter, 50:50, 0.7 to 1.1 μm; Newton, NJ, USA) between the diffuse Amylase axial illuminator and the flow cell also allowed measurement of the reflectance spectrum over 400 to 1,000 nm with the reflectance probe of a fiber optic spectrophotometer (Ocean Optics USB-2000-VIS-NIR). The reflectance probe was rigidly fixed to the beamsplitter via lens tubes containing a focusing lens. Figure 1 Photograph of equipment for simultaneous acquisition of photographs and reflectance spectra. 1 flow cell containing pSi sample, 2 beam splitter, 3 reflectance probe connected to fiber-optic spectrophotometer, 4 diffuse axial illuminator with tungsten light source, 5 camera, 6 pSi sample, and 7 spectrophotometer. Inset: image of the pSi sample as captured by the digital camera. The reflectance spectrum acquisition was controlled by Spectrasuite software (Ocean Optics, Inc.). The position of the rugate reflectance peak and the FFT of the portion of each reflectivity spectrum that displayed Fabry-Perot interference fringes were calculated using custom routines in Igor (Wavemetrics, Inc., Portland, OR, USA).

Our findings could help establish a more personalized medicine-fo

Our findings could help establish a more personalized medicine-focused approach, where not only PSA, but also other novel and promising biomolecules will

contribute to the multifactorial repertoire of individualized PCa care. Conclusions In conclusion, our data offer the convincing evidence for the first time that that NUCB2 mRNA were upregulated in PCa tissues. Our study MGCD0103 datasheet revealed that NUCB2 is an independent prognostic factor for BCR-free survival in patients with PCa. High expression of NUCB2 in PCa is strongly correlated with preoperative PSA, gleason score, angiolymphatic invasion, and lymph node metastasis. These findings suggest that NUCB2 is a cancer-related gene associated with the aggressive progression and a BCR-free survival predictor of PCa P005091 purchase patients. However, these results, which are based on a Chinese cohort, should be further confirmed in other populations of patients with PCa. Our findings suggest that NUCB2 might be used as a new biomarker and a potential therapeutic target for PCa. Consent Written informed consent was obtained from the patient for publication of this report and any accompanying images. Acknowledgements This study was supported by the National Natural Science Foundation of China (NO: 81172451), Tianjin Major Anti-Cancer Project (12ZCDZSY17201), and Science Foundation

of Tianjin medical university (NO: 2009GSI18). References 1. Siegel R, Naishadham D, Jemal A: Cancer statistics, 2013. CA Cancer J Clin 2013, 63:11–30.PubMedCrossRef

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Trop Bryol 3:29–35 Cornelissen JHC, Ter Steege H (1989) Distribut

Trop Bryol 3:29–35 Cornelissen JHC, Ter Steege H (1989) Distribution and ecology of epiphytic bryophytes and selleckchem lichens in dry evergreen forest of Guyana. J Trop Ecol 5:131–150CrossRef Florschütz-de Waard J, Bekker JM (1987) A comparative study of the bryophyte flora of different forest types in West Suriname. Cryptogam Bryol Lichenol 8:31–45 Frahm J-P (1990) The ecology of epiphytic bryophytes of Mt. Kinabalu, Sabah (Malaysia). Nova Hedwigia 51:121–132 Frahm J-P, Gradstein SR (1991) An altitudinal zonation of tropical rain forests using bryophytes. J Biogeogr 18:669–678CrossRef Frego KA (2007) Bryophytes as potential indicators of forest integrity. Forest Ecol Manag 242:65–75CrossRef Gignac D (2001)

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tropical rain forest as an environment for bryophytes and lichens. In: Bates JW, Farmer AM (eds) Bryophytes Screening Library datasheet and lichens in changing environment. Clarendon Press, Oxford, pp 234–258 Gradstein SR (1992b) Threatened bryophytes of the neotropical rain forest: a status report. Trop Bryol 6:83–93 Gradstein SR (2008) Epiphytes of tropical montane forests—impact of deforestation and climate change. In: Gradstein SR, Homeier J, Gansert D (eds) The tropical montane forest—patterns and processes in a biodiversity hotspot. Biodiversity and ecology series, vol 2. University of Göttingen, pp 51–65 Gradstein SR, Pócs T (1989) Bryophytes. In: Lieth H, Werger MJA (eds) Tropical rainforest ecosystems. Elsevier, Amsterdam, pp 311–325 Gradstein SR, Churchill Afatinib research buy SP, Salazar AN (2001a) Guide to the bryophytes CHIR98014 datasheet of tropical

America. Mem NY Bot Gard 86:1–577 Gradstein SR, Griffin D, Morales MI et al (2001b) Diversity and habitat differentiation of mosses and liverworts in the cloud forest of Monteverde, Costa Rica. Caldasia 23:203–212 Gradstein SR, Tan BC, Zhu R-L et al (2005) Catalogue of the bryophytes of Sulawesi, Indonesia. J Hattori Bot Lab 98:213–257 Gravenhorst G, Ibroms A, Rauf A et al (2005) Climatological parameters in the research area—supporting measurements and regionalization. STORMA research report, University of Göttingen, Göttingen Hauck M (2003) Epiphytic lichen diversity and forest dieback: the role of chemical site factors. Bryologist 106:257–269CrossRef Herzog SK, Kessler M, Cahill TM (2002) Evaluation of a new rapid assessment method for estimating avian diversity in tropical forests. Auk 199:749–769CrossRef Hofstede RGM, Wolf J, Benzing DH (1994) Epiphytic biomass and nutrient status of a Colombian upper montane rain forest. Selbyana 14:37–45 Hölscher D, Köhler L, van Dijk IJM et al (2004) The importance of epiphytes to total rainfall interception by a tropical montane rain forest in Costa Rica. J Hydrol 292:308–322CrossRef Holz I (2003) Diversity and ecology of bryophytes and macrolichens in primary and secondary montane quercus forests, Cordillera da Talamanca, Costa Rica. Dissertation, University of Göttingen.

Mol Microbiol 1999, 33:1254–1266 PubMedCrossRef Authors’ contribu

Mol Microbiol 1999, 33:1254–1266.PubMedCrossRef Authors’ contributions SM, and SS carried out the elastase assay and lasB reporter assay. HI carried out cross-streak experiments. TK constructed lasB promoter-gfp reporter strains. SM synthesized FRET-AGLA, elastase substrate. MH synthesized acyl-HSLs. JO and NG conceived of the study, and participated click here in its design and coordination and helped to draft

the manuscript. All authors read and approved the final manuscript.”
“Background The procalcitonin (PCT), the precursor for the hormone calcitonin (CT), is composed of 116-aminoacids and has a molecular weight selleck kinase inhibitor of 13 kDa. PCT was discovered by Moya et al. in 1975, but its molecular structure was elucidated nine years later [1, 2]. The primary structure of whole PCT includes some relevant polycationic motifs (2–3 bibasic aminoacids within

a sequence of four) [1]. In sepsis, the marked increase of PCT concentration in serum has been reported [1, 3]. The role of PCT as mediator of the sepsis cascade received much less attention. A pro-inflammatory activity of PCT in the pathogenesis of sepsis has been suggested based on immune-neutralization findings in two animal species [3]. An anti-inflammatory effect of PCT has been reported in very few studies [4–6], where the scarcity of the models/outcomes used does not lead to any firm conclusion. When human recombinant PCT was added to endotoxin-stimulated human whole blood, there was a marked decrease of the pro-inflammatory cytokine TNFα [5]. Interestingly, a reduction in IL-1β by administration of PCT was observed in the same animal model, the septic hamster, used for the first experiment of PCT immune-neutralization [6]. Lipopolysaccharide (LPS), the

principal component of the outer leaflet of the outer membrane of Gram-negative bacteria, is recognized as the most potent microbial mediator implicated BCKDHB in the pathogenesis of sepsis sequelae and septic shock. Lipid A, the hydrophobic anchor of LPS, produces most of the responses after its detection by Toll-like receptor 4 (TLR-4). Some LPS such as Salmonella typhimurium (S. typhimurium) LPS and Escherichia coli (E. coli) LPS, are well known endotoxins of rough and smooth chemotype [7]. Lipid A of S. typhimurium and E. coli LPS is a β1′-6-linked disaccharide of glucosamine, phosphorylated at the 1 and 4′ positions and acylated at the 2, 3, 2′, and 3′ positions with R-3-hydroxymyristate [8]. Therapeutic strategies for the treatment of septic shock in humans are currently focused on neutralization of the LPS molecule and its many deleterious effects [9].

A dye-sensitized solar cell is composed of three main structures:

A dye-sensitized solar cell is composed of three main structures: (1) a dye sensitizer whose function is to harvest solar energy and generate excitons [7, 8], (2) a nanostructured metal oxide to transport electrons efficiently [9, 10], and (3) a redox electrolyte or hole-transporting material [11, 12]. The key element in a DSSC is the photoanode, which is composed of a thin film of TiO2 NPs. Though the nanoparticle thin film has a high specific surface area, electron percolation is hindered by limited interconnected NPs resulting in photoelectron loss due to recombination between the photoelectrons and the oxidized

dye molecules or electron-accepting species in the electrolyte. To solve this issue, mechanical compression of the Selleckchem Foretinib photoanode thin film was adopted to increase the PF-6463922 clinical trial effective interconnection between NPs. The optimal

thickness of the mechanically compressed TiO2 nanoparticle thin film was reported. this website Methods Experimental details Deposition of TiO2 thin film as photoanode TiO2 paste (10 wt%) was prepared by mixing nanocrystalline TiO2 nanoparticles (TG-P25, Degussa, Shinjuku, Tokyo, Japan; the average nanoparticle diameter was about 25 to 30 nm) with tert-butyl alcohol and deionized water. The TiO2 paste was then scraped on a transparent fluorine-doped tin oxide (FTO) glass of 8-Ω/sq resistivity by doctor blading method. The films were mechanically compressed with a pressure of 420 kg/cm2. After the compression, the films were annealed in air by two consecutive steps: 150°C for 90 min and 500°C for 30 min. The 150°C annealing is to decompose residual organic compounds, and the 500°C annealing is to assist the interconnection of TiO2 NPs. DSSC fabrication Figure 1 shows the structure of the dye-sensitized solar cell with

TiO2 NP thin film as photoanode. The compressed TiO2 NP thin films were immersed in 0.3 mM N3 dye (cis-bis(dithiocyanato)-bis(4,4′-dicarboxylic acid-2,2′-bipyridine) ruthenium(II)) for 5 h. Subsequently, they were rinsed in acetonitrile for a few seconds to wash out unbound dyes and then dried in the oven at 45°C. The Pt thin film as counter electrode was grown on an indium tin oxide (ITO) glass by an electroplating process. The Aprepitant FTO substrate with deposited compressed TiO2 NP thin film with adsorbed dyes was then bonded to the ITO glass with Pt counter electrode using a 50-μm-thick hot-melt polymer spacer. Sealing was accomplished by pressing the two electrodes together at about 115°C for a few seconds. The redox electrolyte, consisting of 0.5 M LiI, 0.05 M I2, 0.5 M 4-tert-butylpyridine (TBP), and 1 M 1-propy1-2,3-dimethylimidazolium (DMPII) mixed into 3-methoxypropionitrile (MPN), was injected into the cell by capillary forces through an injecting hole, previously made in the counter electrode using a drilling machine. Finally, the hole was covered and sealed with a piece of hot-melt polymer, preventing the leakage of the fluid-type electrolyte.

We expected to find the answer in existing land cover products A

We expected to find the answer in existing land cover products. As we shall now explain, these products are not sufficient for our needs. While GlobCover (ESA and UCLouvain 2010) maps croplands and urban areas, mosaics of croplands and natural areas and a variety of other ecosystems, it incorrectly evaluated

the extent of land conversion and subsequent availability of lion habitat. For example, an immense area, nearly 500 km from north to south and stretching over 4,000 km west to east across the entire map (and to areas further east of it), indicates no land use conversion (Fig. 1). Such an area would be of obvious conservation value if intact; however our mapping, using Google Earth imagery at an elevation of ~10 km, shows that people have converted virtually the entire area to cropland (Fig. 1). Fig. 1 In West Africa, there is a large overlap (purple) between Erismodegib in vivo GlobCover’s (ESA and UCLouvain 2010) mapping of anthropogenic land uses (i.e. croplands, cropland mosaics and urban

areas) with areas of user-identified land conversion. GlobCover, however, misses NSC23766 molecular weight large areas (shown in red) that it classifies as unmodified savannahs, but which show fine-grained, extensive conversion to crops when viewed in high-resolution imagery. At the bottom left is Google Earth imagery of a roughly 9 by 5 km area viewed at ~10 km above the surface. It shows an extensive mosaic of fields, even more apparent at lower elevation (bottom right). (Color figure online) Calibration of land use conversion with human population density Since GlobCover (ESA and UCLouvain 2010) is unsuitable for our purposes, we explored whether models of human population provided a better correlation with land conversion. The aim was to find an estimate of human population density that best matched extensive land conversion. We used four focus areas distributed throughout the African lion’s range to compare human population at various FAK inhibitor densities with a high-resolution satellite-based land conversion layer (Supplemental materials, Fig. S1). Figure 2 shows the proportion of overlap in areas between the

user-identified land conversion and people at varying densities across the four focus areas. We define overlap as being when the layers indicate both conversion and the Ribonucleotide reductase threshold for human population density is met, and also where there is no conversion and the threshold is not met. For all four areas, overlap peaks between 10 and 25 people per km2. (Details are in Supplemental materials, Table S2). This permitted us to use human population density as a proxy for land-use conversion for areas where we did not define the latter directly. When the user-identified land conversion layer was not available, we used a density of 25 people per km2 to constrain LCUs, a threshold we consider further in the “Discussion” section. Fig.

However, when Al was used as a substrate in our study, it absorbe

However, when Al was used as a substrate in our study, it absorbed OH− ions to form Al(OH)4 − on the surface, which adhered to the Zn2+-terminated (0001) surface and suppressed growth along the [0001] direction, resulting in lateral growth DMXAA concentration of

ZnO [25, 26]. Meanwhile, the precipitation of aluminum hydroxide (Al(OH)3) also reduced OH− concentration, supersaturating the growth solution. Owing to the influence of Al foils, 1D nanorods with the c-axis along the [0001] direction were not formed. In contrast, two-dimensional (2D) ZnO sheets were formed, which exhibited crooked nanoplate morphology instead of a freely stretched shape, this website suggesting that there was stress in the ZnO sheets. Figure 2 shows the ZnO sheet networks formed on an Al foil upon ultrasonication. As shown in Figure 2a, the ZnO sheet networks were destroyed after 20 min of ultrasonication and some sheets wrinkled. The high-magnification SEM images revealed more that some sheets began to curl (indicated by squares in Figure 2b). With the vibration time extended to 50 min, 1D ZnO nanostructures including nanorods and nanotubes were observed, as shown in Figure 2c,d,e. Because the ZnO sheets were connected

to each other, many remained connected when they transformed into 1D structures. Regardless of whether they were connected, it should be noted that the nanorods or nanotubes formed from the original ZnO sheets exhibited hexagon-like structures. The diameter and length of the formed nanorods or nanotubes Carnitine palmitoyltransferase II were around 200 to 300 nm and 2 to 3 μm, respectively, while the thickness of the nanotube walls was around 70 to 80 nm (as indicated by the square in Figure 2e). Figure 2f is the SEM image taken from the ZnO sample scraped off from the Al substrate and then added into ethanol to be dispersed by ultrasonication for 0.5 h. It is observed that all the original

ZnO Go6983 nanosheets have turned into hexagon-like nanotubes. It is believed that these 1D structures were formed by layer-by-layer winding of the nanosheets. In order to prove that the nanorods/tubes are formed during the ultrasonic process but not generated in the hydrothermal process that may be covered by nanosheets, the ZnO nanosheet-covered Al foil was bended and placed into the ultrasonic wave. Figure 2g,h showed the cross-sectional SEM images of the sample before and after ultrasonic treatment. Apparently, some layers of tiny nanosheets are stacked on the surface of substrate at the earlier stage of hydrothermal process, after which ZnO nanosheets with larger sizes were synthesized continuously. It is important to note that there are no nanorods or nanotubes hidden in the nanosheets.

Reverse transcription was carried out according to manufacturer’s

Comparisons of gene expressions via qPCR were performed by adopting the following primer designs: SOCS3 (5′-CAA ATG TTG CTT CCC CCT TA-3′ and 5′-ATC CTG GTG ACA TGC TCC TC-3′), SHIP1 (5′-TCC AGC AGT CTT CCT CAC CT-3′ and 5′-GCT TGG ACA CCA TGT TGA TG-3′), IRAK3 (5′-GGG TGC CTG TAG CAG AGA AG-3′


and 5′-TTG ATT TTG GAG GGA TCT CG-3′), TRAF6 (5′-CTG CAA AGC CTG CAT CAT AA-3′ and 5′-GGG GAC AAT CCA TAA GAG CA-3′), IRAK1 (5′-GGG TCC AGG TGC TTC TTG TA-3′ and 5′-TGC TAG AGA CCT TGG CTG GT-3′). After reverse transcription of mRNA, 5 μl of the reverse transcription product were added to a BioRad iCyclerTM PCR system containing 0.3 μM of each primer. One-fold QuantiTect SYBR Green MRT67307 PCR Master Mix was used as a fluorescent reporter (QuantiTect SYBR Green PCR, Qiagen). The condition was programmed as follows: (1) Denaturation at 94°C for 10 min; (2) Amplification for 40 cycles of denaturation at 94°C for 15 s, annealing at 55°C for 30 s, and extension at 72°C for 20 s. Cell viability assay 3-[4,5-dimethyl-2-thiazolyl]-2,5-diphenyl-2H-tetrazolium SPTBN5 bromide (MTT) assay, which is based on the cleavage of the tetrazolium salt by mitochondrial dehydrogenases in viable cells. In order to determine toxicity concentration, approximately 105 cells were plated onto each well of 96-well plates for 24 h, followed by treatment

with different probiotic FK228 agents for 6, 8, 10, 12 and 14 hours. After incubation, 200 mL of MTT solution (0.5 mg/mL) were added to each well for 4 h after washing by PBS. Finally, the supernatant was removed and 200 μL of dimethyl sulphoxide (DMSO) were added to each well to dissolve the dark blue formazan crystals. The absorbance was measured by ELISA plate reader (Jupiter, ASYS Hitech, Austria) at 570 nm. To compare the results, the relative cell viability was expressed as the mean percentage of viable cells compared with untreated cells (100%). Statistical analysis Each value is the mean of triplicate experiments in each group. Means comparison was carried out by Student’s t-test.


Health resource utilization and outcomes were compared between matched cohorts using the McNemar chi-square test for categorical variables and the paired t test for continuous variables. Total costs were determined by summation of each costing component and presented as the mean cost over the first and second year. Attributable hip fracture costs were determined by subtracting costs in the non-hip fracture cohort from the costs in the matched hip fracture cohort [24]. Variance estimation (95 % CI) was determined using bootstrapping with replacement [24]. All costs were stratified

by resource type (acute hospitalization, same day surgery, emergency department, complex continuing care, rehabilitation, LTC, home care, physician services, prescriptions Cytoskeletal Signaling inhibitor for osteoporosis, and pain medications), sex, age group (66–69, 70–74,

75–79, 80–84, 85–89, 90+), and residence check details status (community or LTC) at baseline. In an effort to determine costs attributed to death from hip fracture, we further evaluated costs among concordant pairs who survived or died within 1- and 2-years of follow-up. One-year attributable hip fracture costs in Canada were estimated by multiplying sex-specific attributable mean costs in Ontario by 30,000—the total number of hip fractures estimated to occur annually in Canada [4, 25]. Results We identified 36,253 hip fracture patients, of which 31,064 see more (86 %) were eligible. Exclusions were primarily as a result of prior hip fracture (56 % females and 30 % males) and a diagnosis of malignant neoplasm (34 % females, 52 % males), Appendix Fig. 1. After applying exclusion criteria and identifying suitable non-hip fracture matches, the final cohort included 30,029 matched pairs (22,418 females, 7,611 males).

selleck kinase inhibitor Mean age at hip fracture was 83.3 years (SD = 7.1) for females and 81.3 years (SD = 7.1) for males (Table 1). About one-fifth (21 % females, 18 % males) of patients resided in LTC at the time of fracture. The sex-specific matched fracture and non-hip fracture cohorts were well balanced on matched variables, as well as on prior osteoporosis diagnosis. However, more hip fracture patients had been dispensed an osteoporosis medication or incurred a non-hip fracture in the year prior to fracture. Fig. 1 Study flow diagram for hip and non-hip fracture cohort inclusion. RPDB means registered persons database. Exclusions are not mutually exclusive and thus will not add to 100 % Table 1 Baseline characteristics of hip fracture cohort and matched non-hip fracture cohort Variable Value Females Males Hip fracture (N = 22,418) Non-hip fracture (N = 22,418) SD Hip fracture (N =7,611) Non-hip fracture (N = 7,611) SD N % N % N % N % Age Mean ± STD 83.3 ± 7.1 83.3 ± 7.1 0 81.3 ± 7.1 81.3 ± 7.1 0 66–69 869 3.9 869 3.9 0 483 6.3 483 6.3 0 70–74 1,893 8.4 1,893 8.4 0 940 12.4 940 12.4 0 75–79 3,564 15.9 3,564 15.9 0 1,624 21.3 1,624 21.

A strong correlation (r = 0 94) was found between relative expres

A strong correlation (r = 0.94) was found between relative expression levels obtained by microarray or qRT-PCR analysis (Figure 1). In addition, qRT-PCR experiments performed with RNA extracted from H99 cells FLC-treated at 37°C demonstrated that

expression of the target genes also including AFR1 was comparable to that obtained when H99 cells were pre-treated with FLC at 30°C (Figure 2). Figure 1 Scatter plot of the results by microarray and quantitative RT-PCR analyses for ten selected differentially regulated genes in H99 cells FLC-treated (H99F) compared to untreated control cells. Figure 2 Results of qRT-PCR analysis performed with RNAs extracted from H99 cells FLC-treated (H99F) at 30°C and 37°C. The values, which are means of three separated experiments, represent the increase in gene expression relative to untreated control cells (set Selonsertib in vitro at 1.00). Error bars show standard deviations The genes listed in Table 1 were categorized in 10 main groups by functional profiles as described in Methods.

The category with the largest number of genes was “”transport”" with 31 genes, followed by categories that include genes (n = 18) involved in carbohydrate metabolism or protein processes (i.e. biosynthesis, modification, LCZ696 clinical trial transport and GDC-0941 chemical structure degradation). While up- or down-regulated genes were distributed homogenously within almost all the function groups, some categories included more up-regulated genes

(ergosterol biosynthesis) or down-regulated genes (TCA cycle). As it will be discussed below, the finding of a large number of genes differentially regulated adds support to the concept that azole activity is beyond the inhibition of the lanosterol demethylase target encoded by ERG11 [32], whose overexpression has been associated with fungal resistance [33]. To further classify the genes regulated by FLC exposure, we performed GO term analysis. As expected, GO analysis of genes induced by FLC revealed a significant Branched chain aminotransferase enrichment of genes involved in sterol metabolism, particularly ergosterol biosynthetic process (Table 2). Enrichment of genes repressed by FLC was observed in processes involving metabolism of amino acids and derivatives (Table 2). Table 2 Gene Ontology (GO) term analysis for the C. neoformans FLC response GO group GO subgroup P-value Up-regulated genes     Oxidation reduction   5.26e-10 Small molecule metabolic process 1.34e-06   Alcohol metabolic process 4.74e-07   Sterol metabolic process 4.41e-07 Steroid metabolic process   7.81e-07   Phytosteroid metabolic process 1.47e-09   Steroid biosynthetic process 9.08e-07   Ergosterol biosynthetic process 3.57e-08 Transmembrane transport   0.00076 Down-regulated genes     Oxidation reduction   1.31e-12 Small molecule metabolic process 2.50e-11   Alcohol metabolic process 0.00037   Cellular ketone metabolic process 1.