A priori analyses show that LI-WGS requires less sequencing compared with short insert WGS to achieve a target physical coverage, and that LI-WGS requires less sequence coverage to detect a heterozygous event with a power of 0.99. We thus developed an LI-WGS library preparation protocol based off of Illumina’s WGS library preparation protocol and illustrate the feasibility of performing LI-WGS. We additionally applied LI-WGS to three separate tumor/normal DNA pairs collected from patients diagnosed with different cancers to demonstrate our application of LI-WGS on actual patient samples for identification of somatic copy number alterations and translocations. With the evolution of sequencing technologies and bioinformatics analyses, we show that modifications to current approaches may improve our ability to interrogate cancer genomes.As next-generation sequencing continues to have an expanding presence in the clinic, the identification of the most cost-effective and robust strategy for identifying copy number changes and translocations in tumor genomes is needed. We hypothesized that performing shallow whole genome sequencing (WGS) of 900–1000-bp inserts  improves our ability to detect these events, compared with shallow WGS of 300–400-bp inserts.  Next-generation sequencing (NGS) has allowed for the rapid characterization of genomes, exomes and transcriptomes. Such advances have been applied to personalized oncology, represent a promising approach for identifying therapeutic options for cancer patients who do not respond to standard treatments and are key to improving our understanding of tumorigenesis . HoweverOne option for evaluating larger regions in whole genome data using sequencing by synthesis (SBS) technology is the use of Illumina’s mate pair library preparation protocol. The standard protocol requires 10 µg of genomic DNA and supports the evaluation of regions spanning up to ∼2–5 kb. However, owing to the limited amount of DNA that is typically available from tumor biopsies, this approach is not a viable option for sequencing. Illumina also recently released a new Nextera Mate Pair Sample Preparation Kit that requires 1–4 µg of genomic DNA. However, this approach retains transposome-mediated fragmentation that results in an enzymatic footprint that requires trimming of sequencing data, and still requires circularization and biotin pull-down, and thus decreases the ease of library preparation. An alternative user-friendly strategy that requires lower inputs, that does not require post-sequencing trimming and that allows for increased physical coverage and analysis of regions greater than that accomplished by short insert (SI) sequencing is thus needed.a priori analyses, and subsequently developed a long insert (LI) whole genome library preparation protocol that retains the entire insert in the final library, as opposed to mate pair protocols that enzymatically remove central insert sequences. We then applied this approach to tumor/normal DNA pairs collected from three separate patients diagnosed with different malignancies including metastatic basal cell carcinoma of the skin, metastatic papillary renal carcinoma and metastatic bronchial neuroendocrine cancer. We demonstrate both the feasibility of LI-WGS and its application in simultaneously identifying copy number alterations and translocations, key events that characterize cancer genomes.We hypothesized that performing shallow WGS using longer inserts that are ∼900–1000-bp long increases our power for identifying breakpoints, and thereby copy number alterations and translocations, compared with shallow SI WGS of 300–400-bp inserts, which was used by the MI-ONCOSEQ (Michigan Oncology Sequencing Project) study as the solution for identifying structural variants and copy number changes  sequencing)      G = size of human genome      I = inter-read base pair (bp) distance for PE sequencing such that the insert size equals 2L + I       To evaluate the relationship between insert size and physical coverage, we outlined a model for determining physical coverage. Physical coverage can be calculated by using the following equation :  wher  where The earlier equation can be condensed to the following:K as a constant value. Physical coverage increases as the distance between reads increases.Because the approximate number of aligned reads is typically consistent across human genomes for a given aligner and the size of the human genome does not change, we treat P = power  Where a = frequency of event       C = physical coverage/number of anomalous reads       We performed power analyses using the following equation:Fragmentation—For each sample 1.1 µg of DNA was fragmented on the Covaris E210 to a target size of 900–1000 bp . 100 ng of the sample was run on a 1% Tris acetate EDTA (TAE) gel to verify fragmentation.End repair—This step is performed according to the manufacturer’s protocol.End repair purification—100 µl of AMPure XP beads were added directly to end repair products for purification. A 1:1 bead volume:sample volume is used and 300 µl of 80% ethanol was used for two total washes. Aside from these exceptions, the manufacturer’s protocol was followed.Adenylation and ligation—These steps are performed according to the manufacturer’s protocol.Ligation purification—42.5 µl nuclease-free water is used to resuspend the dried bead pellet. Following mixing, a 2 min incubation at room temperature and a 2 min incubation on a magnet, 40 µl of supernatant is aspirated for ligation. Steps 14–26 are removed from the ‘Clean up ALP’ step in the manufacturer’s protocol.Size selection—A 400 ml 1.5% TAE gel is used for size selection instead of a 150 ml 2% gel. Multiple gel punches can be taken. Punches are placed in separate Bio-Rad Freeze ‘N Squeeze columns for purification. Columns are placed at −20°C for 5 min and centrifuged at maximum speed for 3 min—this process is performed 5×. The final eluate is purified using AMPure beads. The same purification protocol is used as is described in the ‘Clean up IMP’ section (under ‘Perform End Repair’) with the following minor edits: a 1:1 ratio of bead volume:sample volume is used during purification, the final sample is resuspended in 22.5 µl nuclease-free water and 20 µl of the supernatant is used for enrichment polymerase chain reaction (PCR).98°C for 30 s98°C for 10 s60°C for 30 s72°C for 1 minCycle to step 2 eight more times72°C for 10 min4°C holdPCR purification—The manufacturer’s protocol is followed for this step aside from the following: 40 µl beads are added to the PCR product for a 1:1 sample to bead ratio, the final dried pellet is resuspended in 26.5 µl resuspension buffer and 25 µl of the final supernatant is removed as the final library.Enrichment PCR—A modified PCR is used:Development and optimization of LI whole genome library preparation was performed using Roche human genomic DNA  and Illumina’s TruSeq DNA Sample Prep Kit . The final protocol is as follows:Final libraries were quantified by Qubit and library sizes determined using the Agilent Bioanalyzer. The LI test library was clustered and sequenced on a single flowcell lane on the Illumina HiSeq to evaluate clustering efficiency. Based on the total and pass filter (PF) cluster densities, the loaded library concentration was adjusted to 18–20 pM for future samples.The study was conducted in accordance with the Declaration of Helsinki and was approved by the Western Institutional Review Board (Protocol #20101288) (NCT01443390). Patients must be age ≥18 and willing to undergo a biopsy or surgical procedure to obtain tissue, unless a frozen tumor collected <8 weeks prior was available. Interested participants were made aware that obtaining a new biopsy may not be a part of the patient’s routine care for their malignancy. Other eligibility criteria included baseline laboratory data indicating acceptable bone marrow reserve, liver and renal function, Karnofsky performance status ≥80% and life expectancy >3 months. All eligible patients had fresh frozen tumor sample collected and sent for analyses. Normal DNA was obtained from peripheral blood mononuclear cells. Direct visualization of patient 1 and 2’s was performed by a board certified pathologist to determine tumor cellularity.Tissue was disrupted and homogenized in RNeasy lysis buffer (Buffer RLT) plus (Qiagen AllPrep DNA/RNA Mini Kit) using the Bullet Blender™ and transferred to a tube containing Buffer RLT plus and stainless steel beads. Blood leukocytes were isolated from whole blood by centrifugation at room temperature and resuspended in Buffer RLT plus. All samples were homogenized and centrifuged, and DNA were isolated following the AllPrep protocol. Each sample was evaluated by gel electrophoresis, analyzed using the Nanodrop to evaluate absorbance ratios and quantified using Invitrogen’s Qubit Fluorometer.1.1 µg genomic DNA of each sample was used to create SI whole genome libraries using Illumina’s TruSeq DNA Sample Kit per manufacturer’s protocol. One modification is that size-selected products were purified using Bio-Rad Freeze ‘N Squeeze gel purification columns and AMPure XP beads. Products were PCR enriched and purified following the manufacturer’s protocol. LI libraries were prepared and indexed using Illumina’s TruSeq DNA Sample Kit with modifications listed previously. Final libraries were quantified and library sizes determined using the Bioanalyzer and Qubit.98°C for 2 min98°C for 20 s65°C for 30 s72°C for 30 sCycle to step 2 five more times72°C for 5 min4°C holdExome libraries were prepared using 3 µg of genomic DNA for the same tumor and normal samples that were whole genome sequenced. Genomic DNA was fragmented to an approximate target size of 150–200 bp on the Covaris E210. For each sample, 100 ng of each fragmented product was run on 2% TAE gel to verify fragmentation. Library preparation was performed using New England Biolab’s (NEB) NEBNext DNA Sample Prep Master Mix Kit, Illumina Multiplexing Oligonucleotide Kit, Agilent SureSelect Human All Exon 50 Mb Kit and Agilent Herculase II Fusion DNA Polymerase. End repair was performed using NEBNext End Repair Buffer (10×), End Repair Enzyme Mix and the fragmented DNA samples. End repair products were purified using AMPure XP beads: 180 µl of resuspended beads were used for cleaning each sample, two 70% ethanol washes were performed and samples were dried for 20 min at room temperature before resuspension in 44 µl of warm elution buffer. For each sample, 42 µl of cleaned end repaired samples are input into adenylation which was performed using NEBNext dA-tailing Buffer (10×) and NEBNext Klenow fragment (3′→5′ exo). Adenylated products were cleaned using AMPure XP beads as previously described but 90 µl of beads are used for cleaning and the final samples are eluded with 15 µl of nuclease-free water. Each adenylated sample was used for indexed adapter ligation. This step is performed using the NEBNext Ligation Buffer (5×), NEBNext T4 ligase and Index PE adapter oligonucleotide mix from Illumina’s Multiplexing Oligonucleotide Kit. Reactions were purified using AMPure XP beads and enrichment PCR was performed using InPE1.0 forward PCR primer (Illumina Multiplexing Oligonucleotide Kit), SureSelect Indexing Pre-cap PCR primer, Herculase II 5× reaction buffer, Herculase dNTP mix and Herculase II polymerase. The following PCR program was used:PCR products were purified using AMPure XP beads. Each sample was run on the Agilent Bioanalyzer using the Agilent DNA 1000 assay and quantified using the Qubit. 500 ng of each sample was used for capture. From hybridization onward, Agilent’s SureSelect Target Enrichment System for Illumina Paired-End Multiplexed Sequencing protocol (version 1.2) was followed.Libraries were used to generate clusters on HiSeq Paired End v3 flowcells on the Illumina cBot using Illumina’s TruSeq PE Cluster Kit v3. One exception is that for patient 1, three lanes of SI normal and three lanes of SI tumor whole genomes were sequenced on a v1.5 flowcell. Clustered flowcells were sequenced on the Illumina HiSeq 2000 using Illumina’s TruSeq SBS Kit. Each LI WG library was run in a single lane, and tumor/normal exome pools were sequenced in individual lanes.http://picard.sourceforge.net), which was also used to evaluate GC metrics.Raw sequence data were converted to fastq files using Illumina’s BCLConverter. Fastq files were validated to evaluate the distribution of quality scores and to ensure that quality scores do not drastically drop over each read. Validated fastq files for whole genome and exome data were aligned to the human reference genome build 37) using the Burrows–Wheeler Alignment tool  and sort using thhttps://github.com/davcraig75/tgen_somaticSV). To decrease false negatives, discordant locations to which at least four tumor reads map are also called. Each event was also manually inspected for confirmation. Copy number analysis was completed by determining the log2 difference of the normalized physical coverage  for both germline and tumor samples separately across a sliding 2 kb window of the mean. Our anomalous read pair script also determines the ratio of anomalous read pairs over all read pairs that mark the boundary of a copy number change. The derivative log ratio spread (DLRS) for each sample was calculated by determining the standard deviation of the point-to-point difference across the genome divided by the square root of 2. The average distance between points is 80 kb and the smoothing window is 19 kb.To compare across SI and LI data, SAMtools was used to randomly select 250 million mapped reads from each data set, and these reads were saved as ‘normalized’ bam’s. To detect translocations in SI and LI normalized data, we first defined the range of insert sizes in the normal data, evaluated the tumor data using a window size that is 3× the insert size range of the normal data and identified reads in each window that maps to a different location. A minimum of eight reads mapping to a discordant location was required for a translocation to be called. For this analysis, we generated a script to identify anomalous read pairs , and primers were designed to flank breakpoints using PrimerQuest (Integrated DNA Technologies). Primers were used to PCR amplify regions encompassing breakpoints on the same DNA samples that were sequenced. PCR products were Sanger sequenced to confirm presence of breakpoints.a priori analyses, we determined that physical coverage is directly affected by insert size such that physical coverage increases with longer insert sizes when sequencing a fixed read length . Physical coverage is considered in this analysis because it reflects the size of the insert being sequenced and is associated with our ability to identify copy number variants (CNVs) and translocations. In Supplementary Figure S1, we outline the relationship between physical coverage and the amount of sequencing that is needed to achieve a target physical coverage for SI- and LI-WGS. Overall, our simplified model shows that given a target physical coverage, more sequencing is needed for SI libraries compared with LI libraries. A few caveats of this analysis are that we did not address potential contributions from factors such as GC bias and polymerase fidelity, and we also make the assumption that read depth is evenly distributed across the entire genome although a Poisson distribution is typically observed in sequencing data. To address these caveats and to truly evaluate this relationship between physical coverage and insert size, we additionally performed experimental analyses to compare SI and LI libraries.Using a is the frequency of the somatic event. Three mutation frequencies were evaluated to consider three scenarios in which the tumor cell content of the analyzed sample is 100, 50 or 25% tumor. We assumed that the event is heterogeneous such that the expected frequency of an event a is one-half of the percent tumor cellularity. We required that a minimum of 10 anomalous read pairs be needed to detect an event where an anomalous read pair is defined as one in which the mapping distance between the two ends are substantially greater than the mean inter-read distance, or if the pairs map to different chromosomes. We also performed additional power calculations and assumed a shorter read length for 900-bp insert libraries to evaluate the utility of sequencing less when longer inserts are used  is needed to achieve 0.99 power for detecting 10 anomalous read pairs. However, when sequencing a 900-bp insert under the same conditions and sequencing shorter read lengths, only 30× sequence coverage  is needed. These analyses demonstrate that even with shorter read lengths and less sequencing, LI-WGS using 900-bp inserts, as opposed to 300-bp inserts, increases the power of detecting an event.Based on results from preliminary analyses, we created a LI-WGS library preparation protocol that we modified from Illumina’s TruSeq DNA Sample Prep library protocol for SI-WGS. To generate longer inserts for whole genome libraries, we modified three primary areas in Illumina’s WGS library preparation protocol: (i) fragmentation, (ii) AMPure XP bead purification steps and (iii) enrichment PCR parameters. Details on all changes to the protocol are described in the Methods and are briefly described here. We used 1.1 µg of genomic DNA for a single library preparation and following fragmentation analyzed 100 ng of fragmented product by gel electrophoresis to verify fragmentation.During fragmentation, Illumina’s protocol for generating whole genome libraries using the TruSeq DNA Sample Prep kit fragments genomic DNA to a target size of 300–400 bp. To generate LI libraries, Covaris parameters for sonic fragmentation were modified to generate fragments that are approximately 900–1000 bp. An example of LI fragmentation products, electrophoretically separated on a 1% TAE gel, is shown in With LI-WGS, the increased size of the inserts was expected to cause differences with respect to GC dropout, normalized coverage across GC rich regions, clustering efficiency, cluster size and Q30 scores. We compared an example LI-WGS library prepared according to our modified protocol and an example SI-WGS library prepared according to Illumina’s TruSeq DNA Sample Prep protocol. Sequencing each library in a single flowcell lane, we were able to achieve similar cluster densities but obtained a lower PF density with LI libraries, and thus, a lower number of PF reads. Results from the comparison are shown in Although fewer clusters and less data are acquired when sequencing a LI-WGS library compared with a SI-WGS library in a single flowcell lane, 93× mapped physical coverage is achieved with the LI-WGS library, whereas only 38× is achieved with a SI library in a single flowcell lane A and B. To evaluate the utility and feasibility of LI-WGS in actual patient samples, we next performed both SI- and LI-WGS on DNA from fresh frozen tumor and whole blood samples from three separate cancer patients. Patient 1 had metastatic basal cell carcinoma of the skin, patient 2 had metastatic papillary renal cell carcinoma and patient 3 had metastatic bronchial neuroendocrine cancer. For LI-WGS, we generated tumor and normal libraries for each patient with insert sizes ranging from ∼800–900 bp long for final library lengths of ∼1000 bp. We additionally generated SI-WGS libraries with approximate insert sizes ranging from 300–350 bp for final library lengths of ∼400–450 bp. PE sequencing for ∼2 × 100 read lengths was performed for all libraries. LI libraries were each sequenced in single lanes, whereas SI libraries were sequenced across 4–5 lanes . DetaileRead alignment was performed with Burrows–Wheeler Alignment against the human reference genome (build 37). Using SBS technology  and 2 × t-test P-values of 0.46 and 0.82, respectively). We did observe a difference between LI and SI libraries with respect to AT dropout , but the means for the LI and SI groups remain low  to indicate an overall low level of dropout in AT rich regions.We evaluated several library and sequencing metrics, including the percentage of PCR duplicate reads and GC dropout. No significant differences were observed with respect to percentage of duplicates in the LI and SI libraries. The SI libraries had an average percent duplicate rate of 4.53, whereas the LI libraries had an average of 4.32. No significant differences were also observed when evaluating the extent of GC dropout and median GC normalized coverage in each of the two types of libraries . Events that affect COSMIC    genes arSupplementary Table S2. Overall, the DLRS values are lower for the LI libraries compared with SI libraries for each patient. Additionally, the patient 1’s SI data demonstrated the highest whole genome DLRS of 0.117, which correlates with the higher level of noise that is observed in the CNV plot . This increased noise further correlates with the high number of CNVs identified in the patient 1’s SI data and not in the patient 1’s LI data.To evaluate the level of noise and variability in the CNV data, we determined the DLRS for each data set. This measurement is used as a standard in evaluating consistency in log ratio array comparative genomic hybridization data for CNV detection and is thus applied here to evaluate data quality. Higher values are indicative of increased noise and less accuracy in CNV detection. Results are shown in Supplementary Table S3. We did not identify any genic CNVs in patients 2 and 3, but identified four genic CNVs in patient 1. The absence of genic CNVs in patient 2 in both SI and LI data correlates with the absence of CNVs in the exome data. For patient 1, of the four exome CNVs, one of these events overlap with a CNV identified in patient 1’s LI data and another event overlaps with a CNV identified in patient 1’s SI data. For patient 3, genic CNVs were only identified in LI data but these events were not identified in exome data. We also evaluated the DLRS on the exome data sets (Supplementary Table S2)—exome data for all three patients had DLRS values >0.1, and with the exception of patient 1’s SI data, the exome DLRS values were all higher than SI and LI data. The high DLRS values for all three patients’ exome data indicate that increased noise may have affected CNV detection and that lower CNV detection accuracy is associated with these data. Patient 1’s exome data also had the highest DLSR across both exome and WG sequencing (0.142), and thus suggests decreased accuracy in CNV detection in this patient’s exome data.To validate CNVs, we performed CNV detection on whole exome data generated from the same paired tumor and normal samples that were whole genome sequenced for each patient. We used this approach since the 1000 Genomes Project demonstrated the feasibility of performing CNV detection using exome data . We geneWe identified inter- and intra-chromosomal translocations in each tumor genome that did not have any supporting germline reads. These events were individually evaluated in Integrated Genomics Viewer, and final results from these analyses are listed in et al. .The NCBI  dbGaP study accession number for patient data from this study is phs000646.v1.p1 (Supplementary Data are available at NAR Online.Funding for open access: Institutional funds.Conflict of interest statement. None declared.


The proinflammatory cytokine TNFα fails to provoke cell death in isolated hepatocytes but has been implicated in hepatocyte apoptosis during liver diseases associated with chronic inflammation. Recently, we showed that TNFα is able to sensitize primary murine hepatocytes cultured on collagen to Fas ligand-induced apoptosis and presented a mathematical model of the sensitizing effect. Here, we analyze how TNFα induces apoptosis in combination with the transcriptional inhibitor actinomycin D (ActD). Accumulation of reactive oxygen species (ROS) in response to TNFR activation turns out to be critical for sustained activation of JNK which then triggers mitochondrial pathway-dependent apoptosis. In addition, the amount of JNK is strongly upregulated in a ROS-dependent way. In contrast to TNFα plus cycloheximide no cFLIP degradation is observed suggesting a different apoptosis pathway in which the Itch-mediated cFLIP degradation and predominantly caspase-8 activation is not involved. Time-resolved data of the respective pro- and antiapoptotic factors are obtained and subjected to mathematical modeling. On the basis of these data we developed a mathematical model which reproduces the complex interplay regulating the phosphorylation status of JNK and generation of ROS. This model was fully integrated with our model of TNFα/Fas ligand sensitizing as well as with a published NF-κB-model. The resulting comprehensive model delivers insight in the dynamical interplay between the TNFα and FasL pathways, NF-κB and ROS and gives an example for successful model integration. Hepatocyte apoptosis is associated with many acute and chronic liver diseases. Regulation of the apoptotic process is complex and mainly triggered through the activation of so-called death receptors While the initiation of apoptosis by the receptor complex and the execution via the mitochondrial pathway constitute two parts of the machinery, several other pathways affect the apoptotic process dramatically. Among these, the JNK pathway deserves special interest. JNK is a serine/threonine protein MAPK which is known to be rapidly activated by TNFα complex I via the MAPK kinase MKK7 As mentioned above, TNFα alone does not lead to cell death and this is due to its strong NF-κB activating properties. NF-κB survival signaling interferes with the TNF pathway at various levels to prevent apoptosis. Hereby, the antiapoptotic activity of NF-κB mainly depends on gene induction, namely the transcriptional regulation of survival genes In this study, we introduce a mathematical model for TNFα-induced apoptosis in hepatocytes which is based on presented measurement results and literature data. The developed model is connected with a TNFα/Fas ligand sensitizing model Wild-type mice were purchased from Jackson Laboratories. Bid−/− mice and XIAP−/− were generously provided by Andreas Strasser and John Silke, WEHI, Melbourne, respectively. All mice were bred on the C57BL/6 background for several generations. Hepatocyte isolation from these mice was approved by the animal experimental committees and animals were handled and housed according to specific pathogen free (SPF) conditions.Primary hepatocytes were isolated from 8–12 week old B6 (C57Bl/6NNrl) mice using the collagenase perfusion technique as previously described 6 detached hepatocytes were resuspended in SEM buffer (10 mM Hepes-KOH and 250 mM sucrose) containing protease inhibitors as described above and homogenized in a Dounce homogenizer. The nuclei were removed by centrifugation at 500×g, and crude mitochondria were obtained from the supernatant by an additional centrifugation step at 10'000×g. Mitochondria were washed twice in SEM buffer and then solubilized in H8 buffer  containing 1% SDS. All fractions were used for Western Blot analyses; cytosolic fractions were also used for cytochrome c detection by ELISA.Crude mitochondrial and cytosolic fractions were prepared as described before 6 primary mouse hepatocytes were incubated with TNFα (R&D Systems) or actinomycin D (ActD) (Alexis) at different doses for the indicated times. Then the cell suspension was centrifuged, washed with PBS and homogenized in 50 µl homogenization buffer . The caspase-3/-7 activity assay was performed exactly as described in The activity of the executioner caspases-3/-7 was measured by the fluorogenic DEVDase assay. Briefly, 1×10L/S and cFLIPL both at 1∶1000 (Santa Cruz Biotechnology) and MnSOD at 1∶5000 (R&D Systems) followed by the respective horseradish peroxidase-labeled secondary antibodies , and the ECL plus chemiluminescence detection reagent (Amersham Biosciences). Chemiluminescent images were quantified using the LumiImager and the LumiAnalyst Software (Roche Applied Science).50–70 µg of total protein was separated by SDS-PAGE  and transferred to a 0.45 µm or 0.2 µm pore size PVDF membrane . The respective antigens were detected by antibodies against phospho-JNK at 1∶1000 , JNK at 1∶1000 , β-actin at 1∶10000  cFLIP5′-CGGCTACCACATCCAAGG-3′, rev: 5′-CGGGTCGGGAGTGGGT, probe: 5′-TTGCGCGCCTGCTGCCT), and 300 nM primers and 100 nM probe for the gene of interest. The following target gene primers and probes were used : mouse cFLIP  and mouse MnSOD . The mRNA level for the gene of interest was determined as 2-ΔΔCT and reflects changes relative to untreated cells.Total RNA was isolated using the RNeasy Plus Kit of Qiagen, according to the manufacturer's directions. The quantity and purity of RNA was determined by measuring the optical density at 260 and 280 nm. Subsequently, 1 µg of total RNA was converted to single strand cDNA using Quantiscript Reverse Transcriptase (Qiagen). The analysis of mRNA expression profiles was performed with multiplex quantitative real time PCR. In a 25 µl PCR reaction, 2 µl of cDNA  was amplified in an Light Cycler 480 (Roche) using 2-fold QuantiTect Multiplex PCR Master Mix (Qiagen), 50 nM primers and 100 nM probe for the 18S rRNA reference gene . H2DCFDA diffuses easily across the cell membrane and is then trapped in the cell by deacetylation. In the presence of ROS, H2DCF is rapidly oxidized to the highly fluorescent compound dichlorofluorescin (DCF) 6 primary mouse hepatocytes were incubated with TNFα, ActD or BHA for the indicated times and H2DCFDA 20 µM was added in the last 20 minutes of incubation. After centrifugation at 2150×g, 4°C for 3 min, washing with PBS, another centrifugation cells were lysed in 70 µl lysis buffer  by shaking at 4°C for 20 min followed by a final centrifugation at 20'800×g, 4°C for 10 min. 10 µl of cell lysate was diluted with 90 µl of assay buffer (100 mM HEPES-KOH supplemented with 100 mM DTT) in a 96-well plate and fluorescence was determined using an excitation wavelength of 485 nm and emission of 540 nm. To quantify fluorescence a DCF standard curve was measured and calculated as described before ROS produced by the different treatments with TNFα (R&D Systems), ActD (Alexis) or butylhydroxyanisol (BHA) (Sigma) were assessed by the oxidation-sensitive probe 2, 7-dichloro-dihydrofluorescin diacetate  models is a standard approach in systems biology as it allows describing dynamic behavior over time. A drawback of this approach is however the dependency on kinetic parameters for the simulation of an ODE model. For biological interactions, these parameters usually cannot be directly measured and need to be identified from measurement data. These data are most often not quantitative in absolute units and is afflicted with uncertainty. In addition, many model parameters are in fact not elementary biochemical parameters but subsume several processes which are not modelled in detail. This might be one of the reasons that ODE models for biological systems are rarely merged into larger models although a variety of signalling pathway models is already available. There are supporting approaches to technically merge mathematical models We extended an existing model of TNFα and FasL sensitizing by adding the regulation of pJNK and its impact on the signaling network. Thereby ROS signaling and a published NF-κB model were integrated in the framework. The presented mathematical model is based on biological experiments and on literature. Overall the model comprises 53 different species (thereof 16 in the NF-κB module) and 74 reaction parameters.The presented extended model still reproduces the sensitizing effect which was a presupposed quality requirement. During the integration of the sensitizing model into the far bigger framework we present here, overall seven parameters from the originally published model have been changed. JNK is now activated in a peak-like fashion which is in accordance with our measurement results . Due to Moreover, the presented expanded model for TNFα-induced apoptosis now also reproduces apoptosis after combined TNFα and ActD treatment as well as the effect of BHA. The qualitative interactions in the network are based on literature data and the presented measurement data for murine hepatocytes which clearly document the modeled functional mechanisms.In this work, a special focus lies on the intention to analyze several pathways that have been associated with TNFα-induced apoptosis but measured rather separately. Although knowledge exists on the regulation and implication of JNK In particular, it could be shown that TNFα plus ActD induce apoptosis by ROS-mediated sustained activation of JNK. Furthermore, the inactivation of NF-κB-mediated survival gene transcription was shown to be critically involved as it has been reported before In this work we report the unexpected finding that ROS upregulate the levels of JNK protein and that this upregulation might be the reason for an increase in phosphorylated JNK. Moreover, first experiments in primary murine hepatocytes suggest that this ROS-mediated JNK upregulation might be controlled by JNK itself because inhibition of JNK activity abrogates the reported increase in JNK protein levels (data not shown). However, this regulatory step should be investigated in more detail in order to understand the exact mechanisms involved.Astonishingly, one of the major regulators of caspase-8 activation, cFLIP, which has been shown to be degraded in TNFα-mediated apoptosis In our model we assume TNFα plus ActD to predominantly act by the ROS-mediated strong and sustained activation of JNK which results in the generation of pBim The experimental approach together with the extended model provides a deep and more complete insight in TNF signaling in murine hepatocytes. There are further participating interactions that are currently not included in the model. For example, XIAP and MKPs are known NF-κB target genes, too et al. take the amount of FADD complex as indicator for apoptosis in their NF-κB model but without modeling e.g. caspases It is sometimes not so difficult to model a certain qualitative behavior with a very simple, reduced model while neglecting the connections and crosstalks of the modeled species in the signaling framework of the cell. In the case of NF-κB a lot of effort has been put in mathematical modeling in order to understand the dynamics of this pathway  with or without ActD (0.4 µg/ml) for the indicated times and cFLIP (A) and MnSOD (B) mRNA levels determined by qRT-PCR. Means of at least three independent experiments ± s.d. are shown.(TIF)Click here for additional data file.Figure S2Simulation results of the TNFα-induced apoptosis model after TNFα, ActD and BHA. (A–C) Simulation results for pivotal species of the TNFα-induced apoptosis model over 10 hours after concomitant stimulation with TNFα, ActD and BHA. The species are shown in separate panels for clarity as indicated in the legend.(TIF)Click here for additional data file.Model S1Additional information concerning the model.(PDF)Click here for additional data file.Model S2Mathematica file (see http://www.wolfram.com/) containing the model.(NB)Click here for additional data file.Supplementary Information S1Experimental procedures.(DOC)Click here for additional data file.


Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates . One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis.I introduce the concept of a biased random (advective-diffusive) bridge (BRB) and show that the MKDE method is a practical means to estimate UDs based on simplified  BRBs. The equation governing BRBs is constrained by the maximum delay between successive relocations warranting constant within-bridge advection  but remains otherwise similar to the BB equation. Despite its theoretical inconsistencies, the BB method can therefore be applied to animals that regularly reorientate within their HRs and adapt their movements to the habitats crossed, provided that they were relocated with a high enough frequency.Biased random walks can approximate various movement types at short times from a given relocation. Their simplified form constitutes an effective trade-off between too simple, unrealistic movement models, such as Brownian motion, and more sophisticated and realistic ones, such as biased correlated random walks (BCRWs), which are too complex to yield functional bridges. Relying on simplified BRBs proves to be the most reliable and easily usable way to estimate UDs from serially correlated relocations and raw activity information. Habitat selection is a dynamic process during which a moving animal chooses the habitat patches it visits and the time it spends within each of them. However, even in recent studies involving individuals tracked at a relatively high fix rate using global positioning system (GPS), movement information provided by serial correlation between successive relocations has largely been ignored: habitat use is most often estimated statically as if these relocations were unlinked Contrary to the classical LKDE method, which focuses on the density of presumably unlinked relocations ith track segment, linking successive relocations zi-1 =  and zi =  is characterised by length iL = ||zi–zi-1||, recording time interval RT(i), proportion of activity time iP and thereby activity time iT = iTRP(i). Hereafter, the time t ∈  will refer to the activity time elapsed from the previous relocation  and zT = .Before entering the core of the subject, let us introduce some basic variables. Consider a GPS tracked animal, whose raw activity (vs. resting) was monitored continuously by a sensor detecting head movements. The Wf the probability density function (PDF) of getting an animal at any location z =  at a given time t>0 knowing that it starts at location z0 at time t = 0 and performs a biased random walk (BRW) with speed s. A BRW is a discrete-step walk whose successive movement directions θ are drawn independently from each other in an angular distribution with mean φ, corresponding to the preferred moving direction, and concentration parameter c = E[cos(θ–φ)] . This advection-diffusion model v =  of the mean location, μw(t) = z0+vt, with speed v = ||v|| = sc in direction φ, and an anisotropic diffusion, involving a collinear (Dφ) and an orthogonal (Dφ+π/2) diffusion coefficient. The degree of anisotropy depends on the shape and concentration parameter of the angular distribution and on the movement speed variability X (α = 0) and Y (α = π/2) axes, is t)α = 2Dαt, where Dα = [Dφ+tan2(φ–α)Dφ+π/2]/[1+tan2(φ–α)] is the diffusion coefficient along this axis. The central limit theorem warrants that fW converges (with a speed inversely related to c) towards an elliptical bivariate Gaussian PDF, with drift direction φ corresponding to either the major (Dφ>Dφ+π/2) or minor (Dφ+π/2>Dφ) axis:wZ(t) = z–z0–vt (wZ)Call DφDφ+π/2)0.5 = .where zT at time t = T. Similarly to a BB, a biased random bridge (BRB) is built up by integrating over time (between 0 and T) the PDF Bf of getting the animal at any location z at a given time t<T conditioned by both starting (z0) and ending (zT) locations: Bg = Bfdt/T. The movement performed from z to zT does not depend on the movement previously performed from z0 to z. The PDF of getting the animal at location zT at time T, knowing that location at time t is z, is therefore equal to Wf. Based on conditional probability formula, it is easy to show that Bf can be computed as:Consider now that the animal is relocated at location Bf is shown to correspond to an elliptical bivariate Gaussian PDF, with the same eccentricity and major axis orientation as Wf:BZ(t) = z–z0–(zT–z0)t/T (BZ)By combining Eqs (1) and (2) and re-arranging terms, the asymptotic expression of Bµ(t) = z0+(zT–z0)t/T, slides from z0 to zT with constant speed L/T. The marginal variance on any arbitrary axis with orientation α is t)α = 2Dαt(1–t/T). It is therefore null at times t = 0 and t = T, and takes its maximum value, equal to DαT/2, at time t = T/2, irrespective of the bridge length L. At short times, Wf has a symmetry axis corresponding to the drift direction but not necessarily a symmetry centre zT at time T should force Bf to have a symmetry centre , so that its main asymptotic properties should remain (at least approximately) valid at short times.The mean location, Bg is inversely proportional to the bridge length L, with E(L)>vT). The mathematical expression of BRBs depends however only marginally (through the matrix diffusion) on the drift characteristics, which do not affect the expected value Bµ(t) or the mean diffusion coefficient D) on which a drift v is appended. In this simplified formulation, Bf converges quickly towards a circular bivariate Gaussian PDF, fully independent of the drift v . There is therefore no need to explicitly know the drift characteristics to compute simplified BRBs, which rest on exactly the same PDFs as BBs (v = 0).The advection process affects both the orientation of a BRB, which tends to align in the drift direction, and its shape, as a stronger advection involves a longer and lower bridge on average (the time-integrated PDF T) and simplified BRBs (including BBs), the expected value E[δ2(t)] = t)0+t)π/2 of the squared distance δ2(t) = ||zt–Bµ(t)||2 between any location zt at time t and its expected value Bµ(t) is equal to 2t(1–t/T)(D0+Dπ/2). Three properties are noteworthy: (1) E[δ2(t)] takes its maximum value at time t = T/2; (2) this maximum value is proportional to T; (3) the ratio E[δ2(t)]/E[δ2(T/2)] is equal to 4t/T(1–t/T) for a given T value. Computer simulations showed that, at short times T, the first and second properties still hold true for standard BRBs, but the function E[δ2(t)]/E[δ2(T/2)] vs. t/T tends to be a little bit skewed. This result confirms that, despite differences in diffusion anisotropy and short-time behaviour, simplified BRBs act as valid proxies for standard BRBs.In both standard BRBs (at large times u(z) = ΣiTi gB/Σi Ti. The local contribution of each bridge to the UD is thus nicely assumed to be proportional to the time spent by unit length iT/iL. However, these pioneering studies considered only bridges that are Brownian and characterized by the same diffusion coefficient, and thereby should be relevant only for animals wandering (no HR) in a uniform environment (purely random resource distribution). The use of simplified BRBs in place of BBs, involving an advective-diffusive instead of a purely diffusive movement process, should provide a sound theoretical basis to compute HR space use estimates. Indeed, not only do changes in advection direction φ allow for critical reorientations towards preferred HR areas but changes in advection strength can further allow for changes in space use intensity more efficiently than changes in diffusion because the bridge shape is more sensitive to the drift speed v than to the diffusion coefficient D. As BBs and simplified BRBs rest on the same PDF, methods formerly developed to compute BB-based UDs can nevertheless provide valid estimates when some conditions are fulfilled (see below).It was cleverly proposed maxT to warrant homogeneous movements (i.e. no marked drift or diffusion changes) between successive relocations: track segments that are longer in time are dismissed from UD computation. The introduction of this time threshold results in an overall upper limit for the BRB movement variance t), obtained at time t = T/2 for T = maxT: maxDT/2. In contrast, there is no theoretical reason to include this time constraint in the BB method, as it a priori assumes purely diffusive movements characterised by a diffusion coefficient that remains constant for the whole tracking period.A key point in BRBs is that the advection component (and possibly the diffusion coefficient) is allowed to change freely (both in terms of direction and strength) between bridges, but should nevertheless remain constant during each of them . It is therefore necessary to set an upper time threshold Bf at times t = 0 and t = iT and to take the recording noise into account, it was proposed t)i, written as the sum of the time-weighted recording noise variance ε2 and movement variance t)i, t)i = ε2[t2+(iT–t)2]/Dt(1–t/iT). If this solution was applied to BRBs, the total variance would paradoxically take its lowest rather than highest value at mid-distance (t = iT/2) when the recording noise is large (ε2>iDT) and the animal moves quite straight (involving a strong drift and low diffusion). Furthermore, when the recording noise is practically negligible with respect to patch sizes, as occurs with current GPS tracking, it seems preferable to incorporate a relocation variance that is associated to animal behaviour instead of recording device noise t)i. This leads to the respective expressions of the total variance:i(t) = 4t(1 –t/iT)/maxT. Although Eq. (4b) is more intuitively appealing, it can be applied only for D>maxT, and the result it provides marginally depends on the chosen value of maxT, contrary to Eq. (4a), which warrants full independence. Space use density at any location z, u(z), can then be computed from the time-weighted contributions of the simplified BRBs associated to the SN track segments of the path: Bµ(t)i = zi-1+(zi–zi-1)t/iT and iT reset to 0 for any track segment lasting more than maxT.A last question concerns the space use intensity to attribute to recorded locations. To circumvent the infinite values taken by In the MKDE method ith track segment in i = n round(iT/τ) intervals, where τ is a time constant, by interpolating in–1 equidistant locations along it. In this way, contributions to the UD of the successive relocations distribute preferentially in the local movement direction rather than uniformly in any direction (as occurs in the LKDE method), and the local density of interpolated locations warrants that these contributions are proportional to the times spent per unit length iT/iL. The mth location of the ith segment, ζi(m) = zi-1+(zi–zi-1)m/in , lies at distance i/nimL from the previous relocation zi-1. It therefore represents the expected animal's location at time t = imT/in in BB and BRB theory. As too large delays in relocation may result in dubious movement information due to a too weak serial correlation, an upper recording time limit, maxT, has been introduced to filter out couples of successive relocations that are not sufficiently serially correlated to warrant that the animal was more likely to be in between them than anywhere in its HR at intermediate times. No locations are therefore interpolated along track segments lasting more than maxT. These segments are also ignored in the BRB method for similar reasons, although expressed in a slightly different way.The method consists in dividing the A variable smoothing parameter (which acts as a standard deviation in kernel functions) is then attributed to any (interpolated or recorded) location:minh  applies to any recorded location (m = 0 or m = in). Its upper limit, maxh, applies to the centre of any track segment lasting maxT for which the animal was always active (iT = maxT). Thus, ih(m) takes its minimum value at times t = 0 and t = iT, and reaches a local maximum (which increases with iT) at time t = iT/2. Although various equations can give rise to such properties, the particular form of Eq. (6) was designed to be consistent with BB theory maxT, Eq. (6) turns out to be the discrete time expression of the total standard deviation of simplified BRBs: it can be derived from Eq. (4) by setting σtot(t)i = ih(m), t/iT = m/in, σmin = minh and either βTmax =  takes its maximum value at time t = T/2 in both BRBs and CRBs, but this maximum value tends to increase faster than T in CRBs, and the function E[δ2(t)]/E[δ2(T/2)] vs. t/T, which is parabolic in simplified BRBs, tends to be more bell-shaped in CRBs. These differences are sufficiently weak to imply that simplified BRBs constitute a valid approximation of CRBs or BCRBs when relocations are acquired frequently on a regular time basis (so as to minimize inter-bridge variations in time T). Simplified BRBs are as simple as BBs to apply, as they can be computed without any knowledge about the direction and strength of the advection. They are thus the only advective-diffusive bridges that are sufficiently simple to be usable in practice, while they remain sufficiently sophisticated to suitably represent various types of movements between known relocations acquired within a relatively high rate.Animal movements are best modelled as biased correlated random walks (BCRWs) with adjustable levels of directional bias and directional correlation The introduction of an advection process whose characteristics can change from one bridge to the next allows for the actual abilities of a resident animal to frequently reorientate towards the more attractive areas of its HR (through changes in advection direction) and to locally adapt its space use intensity to the type of habitat it crosses (through changes in advection strength). Simplified BRBs thus provide a functional way to obtain reliable HR space use estimates from GPS fixes that have been obtained at a high rate and raw activity information. Simplified BRB-based UDs can easily be computed using the MKDE method, which can further cope with the presence of obvious boundaries to avoid attributing non-null space use values to inaccessible areas and underestimated values to accessible adjacent areas maxT in the latter, and secondarily by different expressions of the relocation variance. Thus, for an animal tracked with a high fix rate with respect to its usual movement speed and HR size, as in the buffalo example, the BB and BRB methods will provide similar  UD estimates because all recording time intervals RT were shorter than any reasonable maxT value. In such cases, the BRB method will not provide better results than the BB method would do, although confidence in their validity can be higher.Given the crucial function of advection, the validity of HR space use estimates obtained with the BB method is questionable. As BBs and simplified BRBs involve identical PDFs, the computational procedure on which the BB method rests should be globally valid when animals performs advective-diffusive movements with a locally (within bridge) constant drift instead of purely diffusive ones. In practice, the BB and BRB methods differ primarily by the specification of an upper recording time threshold maxT is precisely to filter out track segments that are likely to involve marked changes in the preferred moving direction and/or other movement characteristics. There is obviously no reason to introduce such a time threshold when movements are a priori assumed to be purely and constantly diffusive. It has been acknowledged, however, that too long delays between successive relocations may be problematic for the BB method because they may involve some orientation process (i.e. advection) towards the HR centre RT are small enough to warrant that its characteristics remain approximately constant between successive relocations.In both BB and BRB methods, the expected animal location at intermediate times is assumed to slide along a straight line from one relocation to the next with a constant local speed, involving a homogenous movement process. The key role of the upper recording time threshold maxT prevents the use of the BRB method when animals were tracked with a too low fix rate. If numerous rack segments are longer in time than maxT, the fix data set is then better considered as the output of a point rather than a movement process, and UDs are better estimated using the classical LKDE method. The BB method might still be used in this case, as it incorporates no time threshold, but will provide dubious results. The BRB method is quite flexible when implemented via MKDE as it mechanically generates LKDE-based UD estimates with a constant smoothing parameter equal to minh  whenever all track segments are longer in time than maxT. With animals tracked with a relatively high fix rate, too long track segments may nevertheless still occur because of missing fixes (GPS failures). The BB and BRB methods will provide similar UD estimates when there are no missing fixes, but will increasingly diverge as the fraction of segments longer than maxT increases. The BB method will tend to provide increasingly dubious results because it will estimate erroneous space use frequencies attached to an increasing number of too long segments, whereas the BRB method, which filters them out, will tend to provide increasingly biased results in terms of habitat preferences because GPS failures are often habitat-dependent maxT/2, occasional missing fixes will be replaced by bridge probability estimations with a cost limited to a marginal loss of accuracy.The time threshold maxT value consists in estimating the serial correlation between subsampled relocations. Determining whether the correlation level is low enough to consider relocations as being statistically independent is relatively easy n to obtain a low serial correlation, the maxT value can be set to n–1 times the recording time interval . Setting maxT to any larger value will lead to identical results if the GPS failure rate is negligible. When an animal cannot be tracked with a high fix rate for extended periods because of electric power constraints, the recording time interval could be set to a reasonable maxT value  if the failure rate is negligible, but a doubled rate will have to be used occasionally to estimate the diffusion coefficient D. If GPS failures occur more often, this doubled rate will have to be used routinely.A general guideline to determine a suitable Before the GPS era, getting wild animal locations in the field often required manual triangulation, a highly time-demanding task. Wildlife researchers then usually looked at acquiring only the minimum relocation number necessary to obtain reliable HR size estimates. It was then important to check that relocations were statistically independent Although it has been applied with apparent success to markedly serially correlated relocations, the LKDE method was initially designed to deal with independent locations. It involves a smoothing parameter which can be fixed or variable, and depends on the global (fixed) or local (variable) location density


Gold nanobelts are of interest in several areas; however, there are only few methods available to produce these belts. We report here on a simple evaporation induced self-assembly (EISA) method to produce porous gold nanobelts with dimensions that scale across nanometer (thickness ∼80 nm) and micrometer (width ∼20 µm), to decimeter (length ∼0.15 m). The gold nanobelts are well packed on the beaker wall and can be easily made to float on the surface of the solution for depositing onto other substrates. Microscopy showed that gold nanobelts had a different structure on the two sides of the belt; the density of gold nanowires on one side was greater than on the other side. Electrical measurements showed that these nanobelts were sensitive to compressive or tensile forces, indicating a potential use as a strain sensor. The patterned nanobelts were further used as a template to grow ZnO nanowires for potential use in applications such as piezo-electronics. Gold nanoparticles Recently, sonochemical and other routes have been developed to synthesize high purity gold nanobelts using glucose Although these methods can efficiently produce gold nanobelts by simple procedures, there are some problems, such as the presence of extra reagents and the limitation of the belt length In this paper, we report on a simple method, free from extra reagents, to create porous gold nanobelts with L×W×T of (∼0.15 m)×(∼25 µm)×(∼80 nm), based on the evaporation induced self-assembly (EISA) of gold nanoparticles 4  with citric acid . Briefly, heat 100 ml 0.01 wt % HAuCl4 to boiling point, then add 3 ml citric acid and keep boiling for 5 min. The nanoparticles were with an average size of 10 nm. A TEM image of the synthesized gold nanoparticles is shown in Gold nanoparticles were synthesized by the reduction of HAuClGold nanobelts were deposited on the beaker wall using an EISA method similar to the deposition of gold nanofilms Gold nanoparticles patterns were fabricated by annealing the gold nanobelts on silicon wafer at 1100°C for 10 min in a muffle furnace.The ZnO nanowires were grown as described by Eustis et al Atomic force microscope (AFM) imaging was performed on an EasyScan 2 microscope (Nanosurf) using contact mode. Scanning electron microscopy (SEM) imaging was done using an EVO50 microscope (Zeiss) with SE1 Mode. Transmission electron microscope (TEM) characterization was performed on a JEOL 2000FX (JEOL) microscope. Electric properties were carried out on a micromanipulator 1800 wafer probe station (Micromanipulator), using two stainless wires as source and drain electrodes. For measuring single gold nanobelts, the distance between the two electrodes was 2 mm, while the electrodes were contacted to silver glue with 1 cm distance for strain sensing measurements on a rubber.4 with citric acid. The growth process is similar to the deposition of gold nanofilms on the beaker wall The gold nanobelts in our experiments were self-assembled from gold nanoparticles that were synthesized by the reduction of HAuClSEM results showed that the pattern grown by pre-treating at 40°C only were not obviously different from the ones grown at room temperature, which might due to the small temperature difference between the solution and the surrounding air. When the temperature solution was above 50°C, fully developed gold nanobelts were observed. ×(∼25 µm)×(∼80 nm). SEM and AFM images showed that gold nanobelts were different in structures on two sides, where the density of gold nanowires on one side was higher than the other side. These uniquely gold nanobelt patterned grown by the EISA method is similar to stick-slip motion induced “coffee rings”, but with a difference in that there was a temperature difference between the solution and the surrounding air. The resistances of 2 mm long gold nanobelts were around 1000 Ω, however, the resistances could be higher due to the cracks in the belts. The porous gold nanobelts allowed a simple demonstration of a strain sensor. Moreover, these gold nanobelts can also be used to produce gold nanoparticle patterns by simply annealing the gold nanobelts above the melting point of gold, and furthermore, the gold nanobelt patterns were demonstrated to be used to grown ZnO nanowire pattern that might be potentially used in the study of piezoelectronics.Figure S1(A), (B) and (C) TEM image of as-synthesized gold nanoparticles from different places; (D) shows the electron diffraction pattern of gold nanoparticles. The black dots in the TEM images are artifacts for imaging.(TIFF)Click here for additional data file.Figure S2SEM of gold nanobelt film grown at pre-treatment of 40°C.(TIFF)Click here for additional data file.Figure S3SEM of gold nanobelt film grown at pre-treatment of 70°C.(TIFF)Click here for additional data file.Figure S4SEM of gold nanobelt film grown at room temperature without any pre-treatment.(TIFF)Click here for additional data file.Figure S5Schematic drawing of the process to make gold nanoparticle patterns.(TIFF)Click here for additional data file.Figure S6SEM of gold nanoparticle patterns annealed from gold nanobelts, showing low (A) and high (B) magnification images.(TIFF)Click here for additional data file.


A series of selenophene oligomers incorporating conjugated fluorinated phenylene units have been synthesised as potential semiconductor materials for organic field-effect transistors (OFETs). X-ray crystallography shows that the molecules are held in close proximity by several short intermolecular contacts, making them ideal candidates for OFET applications. Incorporating fluorinated units into such molecular architectures serves to lower both the LUMO and HOMO energies of the materials and also facilitates the planarisation of 1 ,ion of 1 . Lowerin2–4) bearing a central tetrafluorophenylene unit.3 shows p-type conductivity and mobilities that are larger than that of the corresponding pure oligothiophene species.b[[1[benzoselenophene small molecules exhibit excellent stability in FET devices.21We recently reported a series of compounds . In order to assess the properties of macromolecular analogues, we prepared 7 and 8 via palladium catalysed coupling of the dibromo derivative 9 and the stannylated compounds 1011,7 and 8 gave reasonable quality films upon solution deposition (spin coating) and the materials were assessed as p-type semiconductors in organic field effect transistors (vide infra).Compounds 12–17 were prepared. Full experimental details for these materials are given in the Supporting Information section, along with analytical data. The materials were synthesised to compare the effect of the fluorine groups in field effect transistors. However, polymer analogues of 13 and 15 produced very poor films and the device characteristics of OFETs prepared from these materials were not sufficiently promising to study these materials further.Using similar synthetic methodology to 5 was recrystallised from acetone and, as observed in the case of the thiophene analogues,π–π associations can be seen in X-ray crystallographic studies reveal the molecular conformation adopted in the solid state, as well as the identification of possible intermolecular interactions in thin films. Compound 7 and 8 are readily soluble in chlorinated solvents. From the soxhlet extraction procedure, dichloromethane and chloroform fractions of 7 corresponded to 3–4 repeat units  give optical band gaps of 1.89 eV (7λmax = 470 nm) and 2.18 eV (8λmax = 450 nm), respectively. In the solid state, 7 exhibits fine structure in the absorption spectrum, with the longest wavelength absorption maximum at 588 nm. For 8, the spectrum consists of a single, broad band with a maximum at 497 nm.The isolated fractions of 7 and 8 were fabricated by spin coating chlorobenzene solutions onto bottom gate, bottom contact substrates and measured as previously described.8 are shown in −3 cm2 · V−1 · s−1 and a current modulation of greater than 106. The transistor has a relatively high turn-on voltage of +15–20 V, as has been often observed in other electron-rich thiopheneTransistors employing the chloroform fractions of oligomers 7 has a saturated field effect mobility of 2 × 10−5 cm2 · V−1 · s−1 and a current modulation of 102. It is likely that the orientation of the alkyl side chains is different for the two oligomer backbones, if they both adopt the most energetically favourable all-trans configurations of the selenium and sulphur atoms. This would result in different packing modes for the oligomer chains, which may partially explain the different performance. Oligomer 8 is a promising candidate for further optimisation. In particular, the quality of the films spun from both oligomers is poor, most likely due to the low molecular weights. An increase in the length of the solubilising alkyl chains should result in higher molecular weight polymers and higher device performance.7 have given higher values for hole mobility.7.Oligomer 7 has been prepared via chemical coupling and shows clear evidence of high order and planarity in the solid state. The excellent solubility in common solvents enables deposition of active films by solution processing techniques. Preliminary results on hole mobility measurements for spin-coated oligomers 7 and 8 give values of 2 × 10−5 and 3 × 10−3 cm2 · V−1 · s−1, respectively. These results were obtained without any transistor optimisation (which would be expected to improve the charge carrier mobility significantly), and are encouraging for chromophores incorporating the diselenyltetrafluorophenylene core. Further studies are underway to optimise the film forming properties and hole mobilities of these materials.In summary, we have synthesised a series of oligoselenophenes bearing a central tetrafluorophenylene core and shown the effect of rigidification through H…F and Se…F contacts by X-ray crystallographic and absorption studies. The oligomer


ESR1. There have been conflicting reports about the association of this locus with breast cancer in Europeans, and a GWAS in Europeans identified a different SNP, tagged here by rs12662670. We examined the associations of both SNPs in up to 61,689 cases and 58,822 controls from forty-four studies collaborating in the Breast Cancer Association Consortium, of which four studies were of Asian and 39 of European descent. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Case-only analyses were used to compare SNP effects in Estrogen Receptor positive (ER+) versus negative (ER−) tumours. Models including both SNPs were fitted to investigate whether the SNP effects were independent. Both SNPs are significantly associated with breast cancer risk in both ethnic groups. Per-allele ORs are higher in Asian than in European studies . SNP rs2046210 is associated with a significantly greater risk of ER− than ER+ tumours in Europeans . In these Asian studies, by contrast, there is no clear evidence of a differential association by tumour receptor status. Each SNP is associated with risk after adjustment for the other SNP. These results suggest the presence of two variants at 6q25.1 each independently associated with breast cancer risk in Asians and in Europeans. Of these two, the one tagged by rs2046210 is associated with a greater risk of ER− tumours.The 6q25.1 locus was first identified via a genome-wide association study (GWAS) in Chinese women and marked by single nucleotide polymorphism (SNP) rs2046210, approximately 180 Kb upstream of  SNP rs2046210 did not show a clear association in GWAS carried out in women of European ancestry, and replication studies indicated its effect, if any, was weaker in Europeans  for 40–60 cycles.2 = 0.89 in the European samples used in Turnbull et al. 2 = 0.72 and r2 = 0.66 in HapMap2 JPT and CHB samples, respectively).SNP rs12662670 was chosen as the most easily assayable surrogate for the best European GWAS hit, rs3757318, for which no working Taqman™ assay could be designed. These two SNPs are correlated at rThe primer and probe sequences used were:SNP rs2046210For Forward primerTGCCTCAACTGTCTTGTGAATCTTTReverse primerCTACTGTAGAATCATTTTCCTCACACATACAACAGTCACATACGCATCTAG allele probeVIC CAGTCACATACACATCTAA allele probe FAM SNP rs12662670For Forward primerCTAACGAAGGCAGAGCAAAAAGAAAReverse primerCACACATGCATGACACGTAAATCTTATTAAATTCTTGTAAGTTTCCT allele probeVIC AATTCTTGTCAGTTTCCG allele probe FAM Four studies  used the Sequenom iPLEX MassARRAY™ system  with oligonucleotide design performed using MassARRAY Assay Design software (version 3.1).Tables S2a and S2b for information on the respective phases for SNPs rs2046210 and rs12662670). All studies followed standard quality control guidelines (for details see http://www.srl.cam.ac.uk/consortia/bcac/about/about.html). Data were excluded for any sample that failed genotyping for >20% of the SNPs typed in a given phase of genotyping. All study data were excluded for any SNP with overall call rate <95% or duplicate concordance <94% (based on at least 2% of samples in each study being genotyped in duplicate) or departure of genotype distribution from Hardy-Weinberg equilibrium in controls (p<0.005). In addition, all genotyping centres assayed an identical plate of 80 control DNA samples  and had to achieve call rates and duplicate concordance >98% in order for their data to be included. Data for both SNPs from one study (NBCS) were excluded from further analyses after quality control rules were applied. Quality control data for the individual studies are shown in Tables S2a and S2b. Thus, for SNP rs2046210 forty out of forty-one assayed studies , and for SNP rs12662670 thirty-three out of thirty-four assayed studies  were included in the statistical analysis.SNPs were genotyped in three different BCAC genotyping phases along with other SNPs of interest to the consortium  group of interest.2. Tests were two-sided.The primary analysis estimated ORs for the main effect of the SNP, adjusted for the studies that provided data for the respective analysis . ORs adjusted for both study and age were essentially identical and we did not therefore present the age-adjusted analyses. Per allele ORs were estimated under the assumption of a log-additive mode of inheritance, i.e. the SNP was coded according to the number of minor alleles 0, 1 or 2. Additionally, ORs by genotype were calculated, i.e. two indicator variables indicating the presence of the heterozygous genotype and the genotype homozygous for the minor allele, respectively, were entered the model. The primary p-values were derived by means of a Wald-Test assuming a log-additive mode of inheritance (one degree of freedom). Following Laird and Mosteller, heterogeneity of per allele ORs between studies was assessed by the p-value derived from the Q statistic Genetic main effects by ER status were estimated using case-control logistic regression and restricting the case sample to ER+ or ER− cases, respectively. To test for significant differences between main effects of rs2046210 or rs12662670 in ER+ versus ER− cases, logistic regression analyses were conducted in cases only. In these case-only analyses, the binary ER status was the outcome/dependent variable and the respective SNP and the indicator variables representing the studies were the independent variables.Variation in OR by age was evaluated by testing for an interaction between age-group  and SNP, separately for each subgroup defined by ethnicity and ER status. Thus, the multiplicative SNP by age-group interaction term entered the model in addition to the main effect terms for SNP, age-group and study.To investigate whether the association with breast cancer risk could be explained by one SNP or whether both SNPs had independent effects on disease risk, we fitted logistic regression models which included both SNPs, in addition to indicator variables for the studies, as independent variables in the model. Analyses were carried out separately for Europeans and Asians and for ER− versus ER+ cases and controls. Additionally, haplotype analyses were performed using logistic regression models that included the estimated two-marker haplotypes (coded according to a log-additive model) except for the reference haplotype  and the indicator variables for study. Haplotypes were estimated using the expectation-maximization algorithm.All analyses, were performed using R version 2.11.0 Table S1. In addition to the originally discovered SNP rs2046210, SNP s12662670 was genotyped as a surrogate for the best tag from Turnbull et al. (rs3757318) Tables S3a and S3b. The associations of each SNP are presented in −14] than in Europeans  and this difference is statistically significant [pheterogeneity  = 1.4×10−7]. SNP rs12662670 shows a similar pattern, with a higher OR associated with the minor G allele in Asian studies  than in Europeans  and again this difference is statistically significant [pheterogeneity  = 0.002]. In each case there is no evidence for departure from a log-additive model (a co-dominant mode of inheritance).Key characteristics for each participating study are shown in −8 for rs2046210, p = 2.9×10−3 for rs12662670;  = 0.028 for rs2046210, p = 0.012 for rs12662670). In each ethnicity the estimated ORs for each SNP, after adjustment for the other SNP, are of similar magnitudes: For rs2046210 in Europeans OR (A/G) = 1.08 (95% CI 1.05–1.11) and for rs12662670 in Europeans OR (G/T) = 1.07 (95% CI 1.02–1.12). For rs2046210 in Asians OR (A/G) = 1.17 (95% CI 1.02–1.36) and for rs12662670 in Asians OR (G/T) = 1.21 (95% CI 1.04–1.40). Similar effect estimates are also obtained for haplotypes carrying one minor allele though estimates do not reach statistical significance for the very rare haplotype carrying the major (G) allele of rs2046210 along with the minor (G) allele of rs12662670 . For each Asian study, the number of in-situ cases is less than 100 and so effect estimates are inaccurate but do not differ from those for invasive cancer (data not shown).The OR estimates for 4, −17 vs. OR (ER+) = 1.07 (95% CI 1.04–1.1), p = 1.3×10−7, pheterogeneity  = 5.1×10−6. This difference remains significant after adjustment for rs12662670. A similar, although non-significant, difference is observed in European women for SNP rs12662670 (The associations of these two SNPs with tumour sub-types defined by ER status (ER+ and ER−) were also investigated and are presented in 12662670 Table 3.Table S5). In Asian studies the data are too sparse to give meaningful results. In the combined ethnicities and the European studies alone, the magnitudes of the observed associations are greater in younger women.We further investigated whether the magnitudes of these SNP associations on tumour sub-types differed by age at diagnosis/interview (see Table S1), which could have led to an overestimation of the ORs relative to those expected in a population-based case-control study. However, exclusion of these studies does not materially affect the estimated ORs for either SNP (see Table S6).Fourteen of the European studies had been designed to over-sample cases with a family history of breast cancer  = 1.27 (95% CI 1.22–1.34), p = 2.2×10−24; pheterogeneity  = 0.04]. A stronger association of SNP rs2046210 with ER− tumours is also consistent with the report from the Consortium of Modifiers of BRCA1/2 (CIMBA) Table S5). By contrast, the CIMBA consortium reported that SNP rs9397435  shows evidence of modification of risk in both BRCA1 and BRCA2 mutation carriers (who mainly develop ER− and ER+ tumours respectively) We also find evidence that SNP rs2046210 is more strongly associated with ER− than ER+ disease in both European and Asian women. In the present study this differential association with receptor status is statistically significant in European studies (and remains after adjustment for rs12662670) but is not quite significant in Asians which may be due to a lack of power attributable to the comparatively small number of Asian individuals involved in our study Table 3.2 = 0.12 in Europeans and r2 = 0.56 in Asians) and all four possible combinations (haplotypes) of these two SNPs clearly exist.Previous fine-scale mapping publications on this locus 2>0.9) with rs2046210 and those with rs12662670. If there were a single causal variant, directly responsible for the associations seen with both SNPs, it would need to be correlated with both SNPs. Such a variant has not been yet identified (e.g. by the 1000 Genomes Project). It would presumably be relatively rare. An alternative, and we think, more plausible, explanation for the pattern of associations may be the existence of two independent causative variants, one correlated with rs2046210 and another correlated with rs12662670. If this is the case, the former variant may be more strongly associated with ER− breast cancer than the latter. The reason why both SNPs confer higher relative risks in Asians than in Europeans is unclear. Within the BCAC studies, ER− tumours are relatively more prevalent among Asian (36%) compared to European cases (23%), but this is not sufficient to explain the higher ORs in Asians, since the effects persist after stratification by ER status. It remains possible that the higher relative risks are due to differential patterns of linkage disequilibrium if the, as yet, unidentified causal variants are not strongly correlated with the SNPs identified to date. These questions may be resolved by comprehensive re-sequencing of this locus and fine scale mapping to identify the causal variant (or variants) responsible for the observed breast cancer risks. One aim of the iCOGS Project Examination of linkage disequilibrium plots of the regions surrounding these two SNPs in Europeans Figure 7ESR1 gene, whose transcription start site is located approximately 180 Kb downstream of SNP rs2046210. ESR1 encodes ERα and has long been implicated in breast carcinogenesis. However, it is possible that the proximity of this SNP to ESR1 may be providing a false lead – both SNPs (rs2046210 and rs12662670) lie in the flanking region of C6orf97 and there are numerous other genes in close physical proximity .(DOC)Click here for additional data file.Table S2Characteristics of the study populations genotyped for rs2046210 (a) and rs12662670 (b).(DOC)Click here for additional data file.Table S3Genotype frequencies of SNP rs2046210 (a) and rs12662670 (b) in the different studies.(DOC)Click here for additional data file.Table S4Association of rs2046210 and rs12662670 with in-situ/invasive breast cancer.(DOC)Click here for additional data file.Table S5Association of rs2046210 and rs12662670 with risk of ER−*/ER+**breast cancer.(DOC)Click here for additional data file.Table S6Association of rs2046210 and rs12662670 with breast cancer.(DOC)Click here for additional data file.


Gravity flow characteristics of various pharmaceutical granules through static conical hoppers of different cone angles were studied. Mass flow rate depends on properties of granules and cone angles when environmental conditions such as temperature and relative humidity are kept within a fixed range. The granules were made with active pharmaceutical ingredients as per Indian pharmacopoeia with other additives like binders and diluents. Lubricants were added with the granules to observe their effects on mass flow rate. Magnesium stearate and colloidal silicon dioxide of different proportions were used as lubricants after granulation. A new dimensionally analyzed equation was developed to predict flow rate of the granules. The developed equation agreed well with the experimental data with a percentage deviation of ±10%. In an earlier paperT), granule-wall shear stress (Rw) and void fraction (ɛ) were not taken into consideration during dimensional analysis because RT depends on dp, ρp, g, ρ and μ; Rw was negligible as the cylindrical hoppers were made of acrylic and ɛ depends on kdp. Bulk density (ρb) was not taken into consideration because ρb varies with respect to both time and position within the hopper. Flow of granules through conical hopper had been investigated by several workers. Deming and Mehringo, dp, ρp,. μ´ and θ with Q. Peter Yorket alet alet alp/dr’ and ɛ in the final correlation for determining granule velocity at the orifice. The pressure gradient acts in the radial direction and combines with the gravitational force to enhance the discharge rate.Other parameters like drag on granules per unit area , acceleration due to gravity (g), apparent density of granules (ρp), bulk density of the granules (ρb), hopper angle (2θ), angle of repose (α) and Q. They predicted a generalized correlation which is Q=C. ρb. d02.5.√g.(do/D)m. (α/θ)n, where C, m and n are constants. They presented three sets of values for C, m and n on different moisture contents of the feed and concluded that the correlation is useful in predicting the discharge rate at the smallest meal sizes but not suitable for higher meal sizes.A new flow model to predict gravity flow of soya bean meal of different sizes through conical hoppers of different angles of 40°, 50° and 60° and with different orifice sizes of 3.175 cm to 8.89 cm was developed by Wang p’ is not considered during the present investigation because there is no existence of stagnation zones of granules at the bottom and around the orifice of a conical hopper made of glass (negligible Rw), which however may exist during the flow of powder through a cylindrical hopper of any make. The objectives of the present investigation are to (i) study the flow properties of formulation granules in conical hoppers (ii) develop equation correlating the flow variables (iii) compare theoretical mass flow rate with actual values.Earlier investigators on conical hopper flow did not consider the influence of the properties of air, like ρ and μ on the discharge rates of the pharmaceutical granules. Some of them considered the influence of air pressure on the discharge rate during the flow of granules at higher-pressure condition but others neglected the influence of atmospheric air on the flow rate when the flow of granules was carried out through conical hopper at normal pressure. The orifice diameter correction factor ‘kdIndian Pharmacopoeia grade chemicals/drugs like calcium carbonate, famotidine, dicalcium phosphate, acetyl salicylic acid, metronidazole, ofloxacin, norfloxacin, paracetamol, sulphamethoxazole, trimethoprim, diltiazem hydrochloride, amoxicillin, diclofenac sodium, nimesulide, ranitidine, doxycycline, mebendazole, starch, polyvinyl pyrrolidone, talc, magnesium stearate and colloidal silicon dioxide (aerosil) were obtained as gift samples from reputed pharmaceutical concerns in Kolkata, India.Fifteen sets of dried formulation granules were prepared. To prepare each set of granules, drugs and chemicals were wet granulated using necessary amount of starch or polyvinyl pyrrolidone paste as binder in a lab model planetary mixer and with standard ten-mesh sieve. Finally the wet granules thus prepared were dried in a tray drier to moisture content below 5% w/w. Talc (2% w/w) as glidant was mixed with dried granules in another planetary mixer. Each set of dried granules was then divided into 5 equal parts. One part was kept as normal granules  of the dried granules in a part of a set was determined by sieve analysis methodo) were determined by standard physical methods.Mean surface diameter  at the top and the conical portion with the orifice at the bottom. To determine the flow rate of a particular part of granules of a set through a particular hopper the hopper was completely filled with the granules keeping the orifice closed by sliding disc of 0.5 cm thick and made of S.S. The method of filling granules into the hopper was of natural filling. The ratio of do and the highest ds of the granules was above 5:1 (do:ds>5:1); while the ratio of D and the highest ds was more than 20:1 (D:ds>20:1). The ratio of D and do was nearly 4:1. The influence of head on flow rate is negligible when the material head height exceeds 2.5 D1Three conical hoppers made of borosilicate glass are of 25°, 32° and 38° included angles but of same ds, do, ρp, μ', gcosθ, ρ, μ) where ds is mean surface diameter of granules. The variables are analyzed by dimensional analysis method using standard dimensions. The correlation obtained is, Q.(μ')a/(ds.μ)= A.{ds)3.(ρp)2.gcosθ/μ2}b.(ρp/ρ)c.(d0/ds)d…1. The constants A, a, b, c and d are determined by putting experimental values from −0.6/(ds.μ.ρp/ρ)= 0.15.{ds)3.(ρp)2.gcosθ/μ2}0.45. (do/ds)1.1…2.After careful examining of the data and results of earlier investigations as well as considering the assumption and predictions taken in our earlier paperb) is considered since the particle density (ρp) within a hopper varies with respect to both time and position and flowing density  was found to be substantially independent of the initial voidage or the mass flow ratePhysical characteristics of particles, as mentioned in method, have been tabulated in Average experimental flow rate (Q') of each category of granules, calculated theoretical flow rate of the same category (Q) from the equation (2) and the percentage deviation [{Q'-Q)/Q'}×100] are tabulated in The flowability of granular materials is a major consideration in pharmaceutical operations/preparations. High degree of flowability exposes many advantages leading to uniform characterization of the finished products, minimum wear and tear of machine parts and elimination of flows like capping, splitting etc. Therefore this kind of mathematical correlation having small deviation from experimental data within ±10% would be useful in predicting the flow rate of granules. The desired flow rate may be fixed by controlling the variables used in the correlation.


Brain and Behavior 2013; 3(2): 145–158On page 149, the sentence “In these cisterns the sigma-1 receptor is present to buffer calcium entry overload ” should be changed to the following: “At these cisterns, the sigma-1 receptor may play an indirect action modulating intracellular calcium release .”We regret this misinterpretation. It has no consequences for the reported analyses and conclusions.


The non-reducing disaccharide trehalose has been long considered only as a reserve carbohydrate. However, recent studies in yeast suggested that this osmolyte can protect cells and cellular proteins from oxidative damage elicited by exogenously added reactive oxygen species (ROS). Trehalose has been also shown to affect stability, folding, and aggregation of bacterial and firefly proteins heterologously expressed in heat-shocked yeast cells. Our recent investigation of how a lifespan-extending caloric restriction (CR) diet alters the metabolic history of chronologically aging yeast suggested that their longevity is programmed by the level of metabolic capacity – including trehalose biosynthesis and degradation – that yeast cells developed prior to entry into quiescence. To investigate whether trehalose homeostasis in chronologically aging yeast may play a role in longevity extension by CR, in this study we examined how single-gene-deletion mutations affecting trehalose biosynthesis and degradation impact (1) the age-related dynamics of changes in trehalose concentration; (2) yeast chronological lifespan under CR conditions; (3) the chronology of oxidative protein damage, intracellular ROS level and protein aggregation; and (4) the timeline of thermal inactivation of a protein in heat-shocked yeast cells and its subsequent reactivation in yeast returned to low temperature. Our data imply that CR extends yeast chronological lifespan in part by altering a pattern of age-related changes in trehalose concentration. We outline a model for molecular mechanisms underlying the essential role of trehalose in defining yeast longevity by modulating protein folding, misfolding, unfolding, refolding, oxidative damage, solubility, and aggregation throughout lifespan. Cells were cultured at 30°C with rotational shaking at 200 rpm in Erlenmeyer flasks at a “flask volume/medium volume” ratio of 5:1.The wild-type (WT) strain BY4742  per plate was counted. The number of CFU was defined as the number of viable cells in a sample. For each culture, the percentage of viable cells was calculated as follows:  × 100. The percentage of viable cells in mid-logarithmic phase was set at 100%. The lifespan curves were validated using a LIVE/DEAD yeast viability kit (Invitrogen) following the manufacturer’s instructions.9 cells were harvested by centrifugation for 1 min at 21,000 × g at 4°C. The cells were washed three times in ice-cold PBS . The cell pellet was quickly resuspended in 200 μl of ice-cold SHE solution , and 800 μl of ice-cold SHE solution were added to the cell suspension. The resulting alkali extract was incubated at 60°C for 30 min to destroy endogenous enzyme activities and pyridine nucleotides. The extract was neutralized by adding 500 μl of THA solution , divided into 150-μl aliquots, quickly frozen in liquid nitrogen, and stored at – 80°C prior to use. To measure trehalose concentration, 50 μl of alkali extract  were added to 150 μl of trehalose reagent . The mixture was incubated for 60 min at 37°C. Eight hundred microliters of glucose reagent  was added and the mixture incubated for 30 min at 25°C. The NADPH generated from NADP+ was measured fluorimetrically .Preparation of alkali cellular extract and a microanalytic biochemical assay for measuring trehalose concentration were performed as previously described . The cell pellet was quickly resuspended in 800 μl of EB buffer  and incubated for 5 min at 25°C. The resulting lysate was divided into 40-μl aliquots and stored at – 80°C prior to use. To measure hexokinase activity, 4 μl of cellular lysate  were added to 996 μl of hexokinase reagent . The mixture was incubated for 1 h at 25°C. The NADPH generated from NADP+ was measured fluorimetrically . To monitor the extent of thermal inactivation of hexokinase in heat-shocked yeast cells and the efficacy of its reactivation during subsequent incubation of these cells at low temperature, yeast were grown at 29°C, and recovered upon entry into a quiescent state at day 7 or following such an entry at day 13. These cells were treated with cycloheximide for 5 min at 29°C, heat-shocked for 60 min at 43°C, then shifted to 29°C, and incubated for 60 min. Hexokinase enzymatic activity was measured every 15 min of heat shock treatment and every 15 min of the following incubation at 29°C.Preparation of cellular lysate and a microanalytic biochemical assay for measuring hexokinase enzymatic activity were performed as previously described , according to the manufacturer’s instructions. Briefly, total cellular proteins were denatured by adding 12% SDS to an equal volume of the total cell lysate containing 10 μg of protein. Denatured proteins were incubated with 2,4-dinitrophenylhydrazine for 15 min at room temperature. Proteins were separated by 12.5% SDS-PAGE. Immunoblotting using a Trans-Blot SD semi-dry electrophoretic transfer system (Bio-Rad) was performed as described  with glass beads three times for 1 min. Lysates were then centrifuged for 5 min at 21,000 × 6 cells were harvested by centrifugation for 1 min at 21,000 × g at room temperature and then resuspended in 100 μl of PBS. DHR (Sigma) was added to a final concentration of 10 μM. Following incubation in the dark for 60 min at room temperature, the cells were washed in PBS, and then analyzed by fluorescence microscopy. Images were collected with a Zeiss Axioplan fluorescence microscope (Zeiss) mounted with a SPOT Insight 2 megapixel color mosaic digital camera (Spot Diagnostic Instruments). Fluorescence of individual DHR-positive cells in arbitrary units was determined by using the UTHSCSA Image Tool software (Version 3.0). In each of three to six independent experiments, the value of median fluorescence was calculated by analyzing at least 800–1000 cells that were collected at each time-point. The median fluorescence values were plotted as a function of the number of days cells were cultured.Reactive oxygen species were measured in live yeast by fluorescence microscopy of Dihydrorhodamine 123 (DHR) staining according to established procedures dimethylammonio]-1-propanesulfonate  to a final concentration of 10 mM. CHAPS is a zwitterionic, non-denaturing, and electrically neutral detergent; although it protects a native state of soluble proteins and efficiently solubilizes intrinsic membrane proteins (including proteins associated with lipid raft membrane domains), it is unable to solubilize aggregates of denatured proteins  Analysis ToolPack-VBA. All data are presented as mean ± SEM. The To evaluate the effect of trehalose on lifespan extension by CR, we incubated WT strain and several mutant strains, each carrying a single-gene-deletion mutation affecting trehalose biosynthesis or degradation  can be further prolonged by genetic manipulations that simultaneously (1) increase trehalose concentration by 70–160% during PD phase, prior to entry into a quiescent state; and (2) reduce trehalose concentration by 60–80% during ST phase, following entry into quiescence. Thus, lifespan extension by a low calorie diet requires a specific pattern of age-related changes in the intracellular level of trehalose.tsl1Δ and nth1Δ mutations influence the dynamics of age-related changes in protein carbonylation and ROS in yeast grown under CR conditions.Trehalose accumulation in exponentially grown yeast cells exposed to elevated temperature or to a proteasome inhibitor has been shown to increase their ability to survive a subsequent treatment with exogenous ROS and to protect cellular proteins from oxidative carbonylation caused by such a treatment  inhibit the refolding and reactivation of these pre-denatured bacterial and firefly proteins in vitro and in yeast cells by interfering with chaperone-assisted folding of their non-native  species  stabilize bacterial and firefly luciferases in their native (folded) states in heat-shocked yeast cells; (2) prevent aggregation and maintain non-native  states of these two luciferases, as well as of firefly rhodanese, following their guanidinium-induced denaturation tsl1Δ and nth1Δ mutations influence the dynamics of age-related changes in the extent of protein aggregation in yeast limited in calories. We found that both these mutations, which we demonstrated to elevate trehalose concentration  elevates trehalose concentration prior to entry into quiescence to allow this osmolytic disaccharide to prevent aggregation of completely or partially unfolded and/or oxidatively carbonylated cellular proteins; and (2) reduces the concentration of trehalose following entry into quiescence to limit its inhibitory effect on the refolding and reactivation of partially unfolded and/or oxidatively carbonylated proteins.tsl1Δ and nth1Δ mutations influence (1) the extent of thermal inactivation of hexokinase, an endogenous enzyme protein, in heat-shocked yeast cells; and (2) the efficacy of its reactivation during subsequent incubation of these cells at low temperature. In these experiments, yeast grown at 29°C and recovered upon entry into a quiescent state or following such an entry were treated with cycloheximide for 5 min at 29°C, heat-shocked for 60 min at 43°C, then shifted to 29°C, and incubated for 60 min (Figure To use a complementary experimental approach for validating our hypothesis on a longevity-defining role of trehalose concentration in maintaining biological activities of proteins in chronologically aging yeast under CR conditions, we assessed how the tsl1Δ and nth1Δ cells recovered at day 7, upon entry into a quiescent state, the activity of hexokinase synthesized prior to a cycloheximide-induced inhibition of protein synthesis at 29°C was less susceptible to thermal inactivation at 43°C than in identically treated and aged WT cells (Figure tsl1Δ and nth1Δ cells exceeded that in WT cells of the same age (Figure tsl1Δ cells having a lower trehalose concentration than WT cells (Figure nth1Δ cells recovered at day 13 and having a higher trehalose concentration then WT cells of the same age (Figure In tsl1Δ and nth1Δ cells recovered at day 7, upon entry into quiescence, the reactivation of thermally inactivated hexokinase during the subsequent incubation at low temperature occurred less efficient then in WT cells of the same age (Figure tsl1Δ cells having lower trehalose concentration as compared to WT and especially to nth11Δ cells of the same age (Figures nth1Δ cells recovered at day 13 and having a higher trehalose concentration then WT cells of the same age (Figure In e Figure C. Notewoe Figure A,C. If c Figures B,D. In ne Figure B, thermae Figure D. These To investigate whether trehalose homeostasis in yeast cells may play a role in longevity extension by CR, we assessed how single-gene-deletion mutations that in chronologically aging yeast alter trehalose concentrations prior to quiescence and following entry into a quiescent state impact lifespan. We also examined the effects of these mutations on the chronology of oxidative protein carbonylation, intracellular ROS, protein aggregation, thermal inactivation of a protein in heat-shocked yeast cells and a subsequent reactivation of this protein in yeast shifted to low temperature. Our findings provide evidence that CR extends yeast chronological lifespan in part by altering a pattern of age-related changes in trehalose concentration. Based on our data, we propose a model for molecular mechanisms underlying the essential role of trehalose in defining yeast longevity by modulating cellular proteostasis throughout lifespan Figure . This outsl1Δ and nth1Δ mutations, both of which significantly elevate trehalose concentration prior to entry into a quiescent state (Figures tsl1Δ and nth1Δ cells is significantly less susceptible to thermal inactivation at 43°C than in identically treated and chronologically aged WT cells (Figure Pre-quiescent WT cells proliferating under CR conditions cope with a flow of misfolded, partially folded, and unfolded protein species in the non-native folding state Figure . In pre-s Figure  providess Figure , 2010.tsl1Δ and nth1Δ mutations, both of which elevate trehalose concentration prior to entry into quiescence (Figures in vitro and in heat-shocked yeast cells (Singer and Lindquist, In pre-quiescent WT cells, the aberrantly folded protein species that have not been refolded into functional three-dimensional native conformations or degraded within an elaborate network of molecular chaperones and protein degradation factors (Chen et al.,  Figures  supportstsl1Δ and nth1Δ mutations reduce oxidative carbonylation of cellular proteins (Figure The misfolded, partially folded, and unfolded protein species present in pre-quiescent WT cells are known to be more sensitive to ROS-driven oxidative carbonylation than their properly folded counterparts Nyström, . These cs Figure A but do The oxidatively carbonylated protein species present in pre-quiescent WT cells are known to have a tendency to form insoluble aggregates that escape degradation and can compromise the cellular proteostasis network by inhibiting the proteasomal protein degradation machinery Nyström, . By prottsl1Δ mutation reduces trehalose concentration following entry into quiescence (Figure nth1Δ mutation elevates trehalose concentration following entry into quiescence (Figure Following entry into a quiescent state, a network of molecular chaperones in WT cells promotes a refolding of misfolded, partially folded, and unfolded protein species, either soluble or extracted from protein aggregates accumulated in pre-quiescent cells Figure . By shiee Figure  and extee Figure  and shorThe major challenge now is to get a greater insight into the proposed mechanism underlying the essential role of trehalose homeostasis in defining longevity of chronologically aging yeast under lifespan-extending CR conditions. To address this challenge, many important questions need to be answered. What are the identities of oxidatively damaged proteins whose accumulation in pre-quiescent WT cells proliferating under CR conditions is reduced by genetic manipulations that elevate trehalose concentration prior to entry into quiescence Figure A? Are thThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.