Spodoptera littoralis larva during feeding on Phaseolus lunatus (lima bean) leaves was estimated by combining larval foregut volume, biting rate, and quantification of a fluorescent dye injected into the larvae’s foregut prior to feeding. For providing OS amounts by SpitWorm equivalent to larval feeding, dilution and delivery rate were optimized. The effectiveness of SpitWorm was tested by comparing volatile organic compounds (VOC) emissions of P. lunatus leaves treated with either SpitWorm, MecWorm, or S. littoralis larvae. Identification and quantification of emitted VOCs revealed that SpitWorm induced a volatile bouquet that is qualitatively and quantitatively similar to herbivory. Additionally, RT-qPCR of four jasmonic acid responsive genes showed that SpitWorm, in contrast to MecWorm, induces the same regulation pattern as insect feeding. Thus, SpitWorm mimics insect herbivory almost identically to real larvae feeding.Induction of jasmonate-mediated plant defense against insect herbivory is initiated by a combination of both mechanical wounding and chemical factors. In order to study both effects independently on plant defense induction, SpitWorm, a computer-controlled device which mimics the damage pattern of feeding insect larvae on leaves and, in addition, can apply oral secretions (OS) or other solutions to the ‘biting site’ during ‘feeding,’ was developed and evaluated. The amount of OS left by a  Standing at the beginning of the food chain, plants undergo biotic and abiotic challenges from the environment. In nature, herbivorous insects are one of their major threats, especially in vascular plants. Despite their physical immobility, plants have survived and propagated for hundreds of millions of years. During this long time, they have coevolved with herbivorous insects and developed strategies to fend, repel, and defeat their insect enemies . Plant dBut herbivory is more than the simple removal of plant tissue . BesidesPhaseolus lunatus) as a model plant, mechanical wounding alone by cuts or scratches did not induce volatile emission [To study the contributions of the two aspects  the insect’s feeding behavior has to be emulated and separated from the ‘insect’s chemistry’ . Mechaniemission . Only coemission ,22. Thosemission .β-glucosidase [These elicitors include low molecular weight fatty acid—amino acid conjugates (FACs) ,24,25,26cosidase ; and porcosidase ,33 reporcosidase .Methods to study insect OS or OS derived elicitors include mainly applying saliva or related components onto wounds to mimic insect feeding and examine plant defense response. Up to now, no standard procedure for wounding or OS application was established. Thus, besides different ways of wounding itself, varying OS amounts applied (1 to 20 μL), dilution factors up to 1:5, and differing wounding areas, ranging from a few scratches or puncture rows up to 2% of the total leaf, can be found in the various studies ,16,35.Helicoverpa zea) during feeding by cauterizing or surgically removing the larvae’s labial salivary glands. By using this technique, they showed that tobacco plant defense responses to caterpillar feeding were qualitatively different when caterpillars are either able or not able to secrete saliva. In another case, Major and Constabel [Malacosoma disstria applied to poplar leaves with over 100 puncture holes for maximal target gene induction (PtdTI3). The reported quantitative effects of insect saliva introduced to plant wounding area indicate that it is important to quantify the delivery ability of saliva from insect to plant; i.e., how much saliva is delivered per bite by insect.To examine the effect from different amounts and concentrations of insect OS applied to mechanical wounding, Musser, et al.  preventeonstabel  used a dHeliothis virescens feeding on corn and tomato plants, respectively) [However, from all the former studies, one can estimate that the quantities of OS applied to mechanical wounded plants were often several thousand times higher than the actual amount left behind at the wounding site by a larva per feeding bout, which was estimated in the range of 0.5 to 5 nL (ctively) . To precSpodoptera littoralis larvae feeding on induced defense responses in lima beans.Although the development of MecWorm provided deeper insight in our understanding of insect herbivory, it was necessary to take the next step in order to mimic insect feeding as closely as possible. Thus, here an insect feeding-mimicking device was engineered and established that combines both mechanical wounding and the simultaneous application of chemical elicitors to allow the study of their different influence on the plant’s wounding response. This so-called SpitWorm was tested in comparison with both MecWorm and SpitWorm, based on the robotic system MecWorm , was devS. littoralis treated leaves, and for MecWorm and SpitWorm treatments, the un-detached test leaves were enclosed in an acryl glass case together with the punch head, and equipped with a closed-loop volatile collection pump system  by S. littoralis can be found in the b) left by a larva at the wounding edge  to be generated by MecWorm and SpitWorm, leaf wounding sizes of different larval feeding periods were measured. With four replicates for each treatment, the mean wounding sizes upon larval feeding were, after 5 min—0.30 ± 0.13 cm2; 1 µL mean, 29.88 ± 5.02 mm2; control ~ 1 µL, p = 0.999; 5 µL mean, 32.10 ± 5.54 mm2; control ~ 5 µL, p = 0.978) in leaf wounding sizes whereas injected volumes ≥ 10 µL led to a significant decrease in feeding activity .Feeding activities of untreated larvae (control) were compared with the feeding performance of larvae injected with different volumes of fluorescent dye solution into their foregut to determine the optimal injection volume for the subsequent experiments b. Injecti; see t = 300 s) in the model for determining the volume of OS left per bite  resulted in an average foregut length—l = 4.3 ± 0.8 mm; average width—d = 3.8 ± 0.4 mm, resulting in an average foregut volume (Vg) of 49 ± 17.3 µL,  and 1:30  dilutions of labeled OS, respectively, whereas a dilution of 1:10  resulted in a concentration range close to the average concentration of OS  left at the wounding edges by labeled larvae , the amount of fluorescent dye solution injected , the average concentration of OS left at the wounding edges by labeled larvae , the feeding time , and the solvent volume used for extraction of tissues from the wounding edges , the amount of OS left per bite (Vb) was calculated according to the following equation:The observation of larvae that were feeding on lima bean leaves revealed a biting rate (BR) of 3–5 bite·s−1, 92 pL·bite−1; 4 bite·s−1, 69 pL·bite−1; 5 bites·s−1, 55 pL·bite−1; mean ± SD, 72 ± 18.6 pL·bite−1.Taking the three different BR into account the following volumes of OS left at the wounding edges per bite were calculated: 3 bite·sS. littoralis larvae, MecWorm, and SpitWorm, 38 different compounds were identified and quantified relative to an internal standard (IS). p-values) of a pairwise comparison are listed in After optimizing the SpitWorm parameters, the next step was to test its abilities to provoke ‘insect feeding-like defenses.’ In the headspace of lima bean leaves treated with S. littoralis larval treatment, whereas confidence areas (95%) of SpitWorm and S. littoralis treatments overlap almost completely  of all treatments and relative amounts of all 38 compounds revealed significant differences between MecWorm treatment and SpitWorm and mpletely . The twoLOX3), phenylalanine ammonialyase (PAL), β-1,3-glucanase (PR2), and chitinase (PR3)) showed no significant differences in expression levels between S. littoralis and SpitWorm treatment. In cases where larval treatment resulted in a significant difference compared to sole mechanical wounding by MecWorm, SpitWorm and larval treatment showed a stronger induction  is able to induce volatile emissions qualitatively almost identical to the bouquet released upon herbivory by n wheels ,22, or in wheels . These rS. littoralis larvae on lima bean leaves and the respective defense response of the plant was chosen as the ‘gold standard’ model for developing and parameter-adjusting of SpitWorm.In order to be able to study the influence of larval oral secretions or single chemical compounds on the leaf’s wounding response, we aimed for turning the mechanical caterpillar MecWorm into SpitWorm, which combines the mimicking of mechanical leaf wounding by a larva with a continuous and simultaneous delivery of larval OS through a capillary to the tip of the punching needle. The feeding of −1 was evaluated to leave a continuous trail during mechanical ‘biting’. It is worth noting, that due to the mechanical restrictions of an artificial device, the values for flow rate, as well as for biting rate and the leaf area destroyed per bite of SpitWorm, are different to real S. littoralis feeding (see below).The average leaf wounding sizes of larval feeding were measured for different feeding periods a and theIn order to determine the amount of OS left by a larva at the wounding edge and to adjust the amount of OS to be delivered by SpitWorm, a fluorescent dye solution (Lucifer Yellow CH) was injected into the foregut of the larvae before they started feeding on leaves. Lucifer Yellow CH was chosen because (i) of its fluorescence emission maximum at 535 nm, fitting perfectly in the green gap between 490 to 620 nm of chlorophyll a and b (no background at the wavelength of interest), (ii) it is assumed to be non-toxic, (iii) it has a high quantum yield, and (iv) it is highly dissociated at physiological pH levels . A long-−1), and on the other hand, treated with MecWorm and with a razor blade, both without any fluorescent labeling, showed: (i) A pronounced fluorescence signal at the wounding edge after larva and SpitWorm treatment  was calculated by quantifying the fluorescent dye extracted from the wounding edge tissues of leaves treated with labeled larvae in combination with feeding duration, average foregut volume, amount of fluorescent dye solution injected, and observed larval biting rates (3–5 bites·s−1). This resulted in a calculated flow rate of 250–300 pL·s−1 for the OS delivered by a larva, which is 30–40 times lower than the optimized flow rate (10 nL·s−1) determined for SpitWorm (see above). Thus, the ‘effective’ OS delivered by SpitWorm had to be aligned to the amount of OS from the larva during feeding by dilution. The amount of fluorescent dye extracted from larva-damaged tissue (see above) was compared with the amounts extracted from wounding edge tissues after SpitWorm treatment delivering different dilutions of labeled larval OS labeled with Lucifer Yellow solution (The amount of OS left by a larva per bite (approximately 50 to 100 pL·bitesolution . This re−1). Here it needs to be considered that the feeding track of S. littoralis larvae is not linear but usually follows repetitively a curved path. The OS left in the tissue during a feeding bout is re-ingested by the larva in the next round [With an OS dilution of 1:10 SpitWorm delivers an equivalent of 1 nL OS per second, which is still about three to four times the amount of OS left by larva feeding  amounts in the headspace of leaves, as well as expression levels of four JA responsive genes in leaves upon larvae, MecWorm, and SpitWorm treatment, were compared.E)-β-ocimene, one of the most abundant compounds induced after larvae treatment of lima bean leaves, is oxidized to -2,6-dimethyl-3,5,7-octatrien-2-ol and dehydrogenated to -2,6-dimethyl-1,3,5,7-octatetraene to some extent when collected on active charcoal in the presence of humid air [Volatiles in the headspace of lima bean leaves released upon different treatments were collected, identified, and quantified relative to an internal standard by GC-MS . Insteadumid air . Besidesumid air ), only dP. lunatus leaves, time series of expression levels for four JA-responsive genes were chosen, which were also used in earlier studies [LOX3), phenylalanine ammonialyase (PAL), and the pathogenesis-related (PR) proteins ) and (PR3 (chitinase)). All treatments showed no significant difference between SpitWorm treatment and larvae feeding  was influenced by OS from S. littoralis or SpitWorm, respectively. This indicates that mechanical wounding alone is able to induce the JA responsive genes pathway, but chemical factors enhance or modulate this induction for a more rapid defense response. Additionally, the results showed that 1:10 dilution of OS is an appropriate dilution factor to add OS to SpitWorm to mimic S. littoralis feeding.To further investigate responses to SpitWorm treatment in  studies . The fou feeding . Whereas MecWorm , the expAs a further developed MecWorm, a SpitWorm was expected to mimic the action of a feeding insect as close as possible. The results emphasize that both mechanical wounding and chemical factors play prominent roles in gene regulation and defense reactions, which further proves that SpitWorm can be used as an effective tool in mimicking insect feeding. Our findings also support the hypothesis that in wounded leaves, mechanical wounding can trigger most of the defense reactions, while chemical factors in insect OS have a ‘fine-tune’ function by enhancing or attenuating the induction of gene expression by mechanical wounding.With this new tool at hand, it is now possible to study the interplay of mechanical wounding and larval OS at different environmental conditions or with different combinations of compounds. Using fractions of larval OS or single compounds will allow tracking down individual elicitors, and in combination with other comparative genomic, transcriptomic, or proteomic methods, it will be possible to go further and deeper in understanding regulation processes of plant defense against herbivory.Phaseolus lunatus L. (Ferry Morse cv. Jackson Wonder Bush) were grown from seeds at 23 °C and 60% humidity in plastic pots (diameter 5.5 cm) using sterilized potting soil. For daylight radiation, fluorescent tubes (ca. 270 μE m−2 s−1) with a photophase of 16 h were used. Experiments were conducted with 12 to 16 day old seedlings, showing two fully developed primary leaves.Lima beans, Spodoptera littoralis  larvae, hatched from eggs  were reared on artificial diet , and 75 g agar boiled in 1.0 L of H2O) and raised at 22 °C to 24 °C, with a 14 h to 16 h photophase, to the developmental stage of 3rd to 5th instar. For all experiments, larvae with a body length in the range of 2.5 to 3 cm were chosen.S. littoralis, MecWorm, SpitWorm), one un-detached primary leaf of a seedling was inserted in the cubicle of the robotic device. Temperature, humidity (not controlled), and illumination regime were identical to the larvae raising conditions. Three MecWorms/SpitWorms were used simultaneously, each with a punching unit consisting of a hollow needle with 0.5 mm diameter. The punching strokes were adjusted to destroy squared areas of leaf material according to the respective mean wounding sizes and a similar pattern resulting from larval herbivory. A damage of the leaf’s main rib was never observed on larval feeding. Therefore, the wounding pattern of the mechanical devices was set accordingly.For all plant treatments (A gas-tight glass syringe (100 mL) was connected to a capillary  running from the top of the punching head of MecWorm  through −1, 5 nL·s−1, and 10 nL·s−1) SpitWorm was set to mimic larval biting pattern on a filter paper for 5 min.In order to determine the lowest flow rate at which a fluid can be supplied continuously without interruption through the hole in the punching needle, ink was used instead of larval OS. With different delivery rates (2.5 nL·sRegurgitate was collected by slight squeezing the larvae with tweezers and collection of the excreted fluid with a Gilson Pipetman P20 Variable Volume Pipette (2 to 20 µL). If not used immediately, the regurgitate was frozen and stored at −20 °C. Before dilution and use with SpitWorm, larval regurgitate was filtered through a syringe filter .n = 4 for each treatment).After 12 h of starving, single larvae were allowed to feed on a lima bean leaf for 5 min, 1 h, 3 h, 9 h, and 17 h. For subsequent quantification of wounding areas, only treatments where the larva did not feed at the leaf edges were used. Images of the damaged leaves were printed out. Scaled unit areas and wounding areas were cut out of the same sheet of paper and weighed on an analytical scale. Wounding sizes were determined by dividing the paperweight of the wounding area by the paperweight of the scaled unit  was calculated as a cylinder (Vg = l·π·(d/2)2, n = 5).After feeding, larvae were euthanized by immersion in 75% ethanol solution for 30 s, dissected, and the length (l) and width (d) of the foregut were measured. Foregut volume (V−1) of Lucifer Yellow CH dipotassium salt , with 4 replicates for each injection volume. As controls, 4 starved larvae, not-injected, were used. Larvae were then fed on lima bean plants for 5 min, wounding areas were pictured with a LEICA LMD6000 fluorescence microscope, and wounding sizes were measured as described above.After being starved for 12 h, larvae were injected with 1 µL, 5 µL, 10 µL, and 15 µL of an aqueous solution  of Lucifer Yellow and observed under ultraviolet light (365 nm) for 3 h.In order to estimate the residence time of the injected fluorescent dye solution in the larval foregut, −1) of Lucifer Yellow CH dipotassium salt was injected into the larval foregut. After injection, larvae were allowed to feed on leaves for 5 min. Leaf tissue around the wound margins was cut out, ground in liquid nitrogen, suspended in 1 mL H2O by shaking for 1 h in the dark at 4 °C, and centrifuged for 10 min at 12.6 × 1000 rcf. The supernatant was subjected to fluorescence signal quantification with a FP-750 Spectrofluorometer . The supernatant of centrifuged tissue suspensions of leaves treated with unlabeled larvae, processed in the same manner as above, served as blank and as the solvent for the dilutions for the standard curve measurements (n = 3 for each treatment). A standard curve  of Lucifer Yellow solution (1 mg·mL−1).An aqueous solution  using different aqueous dilutions  of fluorescence dye labeled regurgitate  in 44 μL of filtered larval regurgitate).Leaves were treated for 5 min with SpitWorm , tissues of the wound edges were processed in the same manner as described for the treatment with labeled larvae (see above).For fluorescence signal quantification , SpitWorm (delivering a diluted (1:10) Lucifer Yellow solution  in 44 μL of filtered larval regurgitate at a flow rate of 10 nL·s−1), and by MecWorm and a razor blade, both without fluorescent labeling. Pictures of the wounding areas were taken with a LEICA LMD6000 fluorescence microscope.Lima bean leaves were treated by S. littoralis treated (one larva per leaf), as well as for MecWorm and SpitWorm  treated leaves  and wounding areas (7.25 cm2) for all treatments), the test leaves were enclosed in an acryl glass case  together with the punch head in the MecWorm device , or treated with larvae (n = 6), MecWorm (n = 5), and SpitWorm (n = 6), were continuously collected for 24 h on Porapak Q traps  using the closed-loop-stripping (CLS) method [−1) as internal standards, and stored at −20 °C prior to analysis. Samples were analyzed by gas chromatography mass spectrometry (GC-MS) with an ISQ GC-quadrupole MS system  equipped with a fused silica capillary column ZB–5 . Helium at 1 mL·min−1 served as carrier gas with an injector temperature of 220 °C running in split mode (1:10); 1 µL of sample was injected. Separation of the compounds was achieved under programmed temperature conditions . The MS was run in EI mode (70 eV) with a scan range of 35 to 450 amu, a transfer line temperature of 280 °C, and an ion source temperature of 250 °C. Data acquisition was performed using Xcalibur 3.1 (Thermo Fisher Scientific).For headspace volatiles collection of m device . The cap) method . Traps w8–C20 in n-hexane (Aldrich) was measured before and after a sample sequence under the same conditions except for the injector split ratio (1:50). Retention times of the n-alkanes were used to calculate the retention index (RI) for each peak in the GC-MS chromatogram according to the method of van Den Dool and Kratz [A mixture of n-alkanes Cnd Kratz .Compounds were identified based on their mass spectra (MS) in combination with their individual RIs in comparison to NIST , Adams  and Mass−1; OS dilution, 1:10) for 1, 3, and 9 h with comparable leaf wounding sizes for each period. Leaves of untreated plants served as control. Three technical and three biological replicates were used for each sample.For gene expression analysis, lima bean leaves were treated by larvae, MecWorm, and SpitWorm , X53129, [PR3 (chitinase), M13968 [P. lunatus actin  gene was used as the normalizer [Primers for RT-qPCR were designed with Primer3plus  accordin X63521, ) in the  M11939, ) in the  X53129, ) and PR3, M13968 ,51,52. PPrimers used for RT-qPCR were as follows were follows:LOX3 (X63521),forward5′-TGGATGACCGATGAAGAA-3′reverse5′-TGTTGCTATGACGAATGG-3′PAL (M11939),forward5′-GAAACCTTAGAATCCATCACCA-3′reverse5′-TAGAAGCCAAGCCAGAACC-3′PR2 (X53129),forward5′-AAACTCCTACCCTCCATCACAA-3′reverse5′-CCATCCCTCACCACAACA-3′PR3 (M13968),forward5′-GGCGAGGACAGGATAGCAG-3′reverse5′-TCACAAAGGGAAACACAGATT-3′PACT1 (DQ159907),forward5′-AGGCTCCTCTTAACCCCAAG-3′reverse5′-GTGGGAGAGCATAACCCTCA-3′TM DNase (Ambion) and RNeasy MinElute Cleanup kit. RNA was then directly subjected to 1-step comparative quantitative real-time RT-qPCR using the VersoTM SYBR Green 1-Step QRT-PCR Low ROX Kit (ABgene), with an Mx3000P Real-Time PCR system (Stratagene). The process was conducted according to the manufacturer’s protocol with a 25 µL reaction system, consisting of 0.25 μL Verso Enzyme Mix, 12.5 μL 1-Step qPCR SYBR Mix, 1.25 μL RT Enhancer, 1.75 μL forward and reverse primers (1 μM) each, 2 μL RNA template (25 ng·μL−1), and 5.5 μL water (PCR grade). The reaction procedure was as follows: cDNA synthesis for 15 min at 50 °C, Thermo-Start activation for 15 min at 95 °C followed by 40 cycles of denaturation (15 s at 95 °C), annealing , and extension (30 s at 72 °C). Fluorescence signals were recorded after each annealing step. After this an additional temperature cycle  was followed by an incremental heating to 95 °C (stepwise 0.5 °C for 10 s) to verify the products by a dissociation curve. Fluorescence signals were recorded during the whole melting process. PCR conditions were determined by comparing threshold values, followed by non-template control for each primer pair. Relative RNA levels were normalized with the level of P. lunatus actin mRNA (PACT1) and calibrated with relative expression levels of the target genes in untreated control plants.Leaf tissues (80–100 mg) were collected around the leaf’s wounding edges or from intact leaves as a control and ground in liquid nitrogen. Total RNA was isolated using Trizol reagent (Invitrogen) following the manufacturer’s protocol and purified using TURBOStatistical analysis was performed using the free software package R version 3.4.3  in combiFor comparing the relative amounts of volatile compounds released upon different treatments, a dimension reduction by principal component analysis (PCA) with scaled experimental values was performed.


A pheochromocytoma of the rat adrenal medulla derived (a.k.a. PC12) cell-based assay for dopamine measurement by luminescence detection was customized for the qualitative evaluation of agonists and antagonists of nicotinic acetylcholine receptors (nAChRs). The assay mechanism begins with ligand binding to transmembrane nAChRs, altering ion flow into the cell and inducing dopamine release from the cell. Following release, dopamine is oxidized by monoamine oxidase generating hydrogen peroxide that catalyzes a chemiluminescence reaction involving luminol and horseradish peroxidase, thus producing a detectable response. Results are presented for the action of nAChR agonists , and antagonists (α-conotoxins (α-CTxs) MII, ImI, LvIA, and PeIA) that demonstrate a luminescence response correlating to the increase or decrease of dopamine release. A survey of cell growth and treatment conditions, including nerve growth factor, nicotine, ethanol, and temperature, led to optimal assay requirements to achieve maximal signal intensity and consistent response to ligand treatment. It was determined that PC12 cells treated with a combination of nerve growth factor and nicotine, and incubated at 37 °C, provided favorable results for a reduction in luminescence signal upon treatment of cells with α-CTxs. The PC12 assay is intended for use as a fast, efficient, and economic qualitative method to assess the bioactivity of molecules that act on nAChRs, in which testing of ligand–nAChR binding hypotheses and computational predictions can be validated. As a screening method for nAChR bioactivity, lead compounds can be assessed for their likelihood of exhibiting desired bioactivity prior to being subjected to more complex quantitative methods, such as electrophysiology or live animal studies. Xenopus oocytes that express the desired nAChR isoform [Nicotinic acetylcholine receptors (nAChRs) are pentameric transmembrane proteins present throughout the nervous system, brain, and muscle. Neuronal nAChRs are involved in critical brain functions, and have been implicated in a variety of neurological diseases and disorders ,2,3,4,5. isoform ; patch c isoform ; model s isoform ,27,28,29 isoform ,31,32; a isoform  or human isoform . Cell-ba isoform . Each of isoform . Computa isoform ,37,38. M isoform . HoweverThe PC12 protocol reported in this study is an adaptation of a luminescence bioactivity assay that permitted measurement of dopamine release from rat PC12 cells, following activation by acetylcholine (ACh), bradykinin, muscarine, and ATP ,41. Acet50 and Emax values for agonist-stimulated 86Rb+ efflux in NGF-treated PC12 cells, as reported by Avila et al., are shown in In the present investigation, the PC12 assay protocol of Shinohara et al. was adapted for measurement of increased response following stimulation with ACh, nicotine, and cytisine ,41. Acet50 of 0.5 to 2.2 nM [50 = 220 nM) [50 = 8.7 nM) [50 = 19.2 nM) [50 values for ImI, LvIA, and PeIA with rα3β2 nAChR are >5 µM [50 values for ImI, LvIA, and PeIA with rα3β4 nAChR are >5µM [α-Conotoxins (α-CTxs) are known to be highly potent and selective for nAChR isoforms, and have been used extensively by scientists seeking to understand ligand binding paradigms for nAChR subtypes . The reao 2.2 nM . α-CTx Mo 2.2 nM . When us 220 nM) , rα3β2 ( 8.7 nM) , and rα319.2 nM)  nAChR sure >5 µM , 8.7 nM re >5 µM , respectare >5µM , 148 nM are >5µM , respect86Rb+ efflux studies that NGF treatment predominantly increases expression of an α3β4 receptor subtype in PC12 cells, while nicotine treatment predominantly increases expression of an α3β2 receptor subtype, and that these two treatments combined have a supplemental effect on increasing nAChR expression [86Rb+ efflux studies do not provide real-time observation of dopamine release through nAChR stimulation or suppression by ligands, such as the study by Shinohara et al., which the current study aimed to achieve.PC12 cell growth and ligand treatment parameters were evaluated for enhanced response to the rα3β2 nAChR isoform selective antagonist, α-CTx MII. PC12 assay results were assessed for influence by nerve growth factor, nicotine, ethanol, and temperature. Rogers et al. revealed that PC12 cells express the rα3β2 nAChR isoform among other receptor subtypes, and that NGF treatment provides growth conditions that favor expression of the β2 subunit . In a copression . HoweverGiven the wealth of data associated with nAChR expression in PC12 cells reported in the literature, the PC12 cell assay conditions optimized in the present study were performed to achieve two objectives. The first objective was to obtain an optimal response for nAChR agonist and antagonist activity by alteration of the PC12 assay experimental parameters, including NGF, nicotine, ethanol, and temperature. The second objective was to establish optimal α-CTx suppression of dopamine release by inhibition of nAChRs in the context of the PC12 cell line expression system, as recorded by luminescence response.Non-NGF-treated cells A give a Effective NGF treatment was confirmed by cell morphology, in which NGF-treated cells contained neurite extensions indicative of neuron-like differentiation . AccordiCells incubated at a lower temperature before luminescence recording showed a significantly increased response in a temperature-dependent manner but sensitivity to α-CTx MII treatment was appreciably diminished. The luminescence response for cells incubated at 37 °C was appreciably higher as compared to those incubated at lower temperatures.Finally, Decreased luminescence response upon treatment with α-CTx MII indicates that α-CTx MII inhibition of nAChR-mediated release of dopamine in the PC12 cell assay can be observed and measured . Sensiti125I-labelled epibatidine, which binds more potently to α3β2, α3β4, and α4β2 nAChR subtypes than acetylcholine. Additionally, epibatidine binding requires incubation at room temperature for 1 h, which our results have shown drastically increases response  and antagonists  . The PC1This study presents an accessible, time and cost efficient, and reliable luminescence-based method for the detection of nAChR bioactivity, and demonstrates decreased response upon addition of α-CTx antagonist. As a result of the alterations made to the PC12 protocol see , this asShinohara et al. permitted real-time detection of dopamine release upon stimulation of nAChR and bradykinin receptor agonists in PC12 cells without NGF treatment, as well as upon stimulation of mAChR, ATP receptor, and bradykinin receptor agonists in PC12 cells treated with NGF. The present investigation improves upon Shinohara’s original assay by exploring and identifying optimal growth conditions for nAChR expression, and the use of selective α-CTxs to assess nAChR isoforms responsible for assay response upon stimulation with ACh, demonstrating that nAChR expression can be manipulated by chemical treatment and growth conditions in order to qualitatively characterize the real-time ligand effect on nAChR-induced dopamine release. While we demonstrated that this assay provides accurate bioactivity validation, it is apparent that the assay’s sensitivity is limited by a response resulting from the presence of non-rα3β2-nAChR subtypes. Additionally, inconsistent expression from cell to cell, and high background noise can complicate results. Possible reasons for such background noise in the response include inherent base-level activity of predominantly expressed nAChRs, such as rα7, rα3β4, and rα3β2, as well as G-protein coupled activation of nAChRs as opposed to ion translocation . While tA simple method for the measurement of ligand-induced bioactivity on nAChRs that can be quickly and easily performed was presented. Because PC12 cells grow quickly, the time from cryopreservation recovery to assay can be achieved within one week with 3 to 4 days of treatment. Assay response curves can be obtained within minutes, enabling evaluation of an entire 96-well plate within an hour. Optimal growth conditions for expression of rα3β2 nAChRs were measured by the degree of sensitivity to α-CTx MII suppression. According to the results of this study, combined treatment with NGF and nicotine, and incubation at 37 °C provides the greatest level of sensitivity to α-CTx MII. This adapted PC12 assay can be applied to qualitative characterization of the bioactivity of lead compounds with nAChRs, as demonstrated by the compound screen performed here under optimized growth conditions with non-specific agonists and antagonists of nAChR. The materials and methods for this PC12 assay represent an adaptation and modification of the foundational work originally reported by Shinohara et al. ,41. Key Assays were performed using a Biotek Synergy H1 microplate reader . All chemicals were purchased at the highest purity available (>95%) from Fisher Scientific, except for synthetic α-CTxs, which were purchased from CS Bio Inc. . ATCC® CRL1721™ PC12 cells were provided by the Biomolecular Research Center at Boise State University.Cell Culture: PC12 cells were recovered from cryopreservation, seeded, and cultured into laminin-coated flasks according to Shinohara et al. with the exception that cells were not trypsinized to detach them from laminin [ laminin . Instead laminin . Well plCell Assay: Cells were washed with Locke’s solution (pH 7.4) before introducing assay solution. An assessment of modified Hank’s balanced salt solution was performed but results were unfavorable (avorable . Assay s


Based on their presence and severity, the morbidities were clustered to generate distinct clusters in COPD and controls. Telomere length in circulating leukocytes was compared across the clusters. Results: (co)morbidities were more prevalent in COPD patients compared to controls . A “Psychologic” and “Cachectic” cluster were only present in the COPD population. “Less (co)morbidity”, “Cardiovascular”, and “Metabolic” clusters were also observed in controls, although with less complexity. Telomere length was reduced in COPD patients, but did not differ between the (co)morbidity clusters in both populations. Conclusions: Two COPD-specific comorbidity clusters, a “Cachectic” and “Psychologic” cluster, were identified and warrant further studies regarding their development. Accelerated aging was present across various multimorbidity clusters in COPD.Background: Patients with chronic obstructive pulmonary disease (COPD) often suffer from multiple morbidities, which occur in clusters and are sometimes related to accelerated aging. This study aimed to assess the disease specificity of comorbidity clusters in COPD and their association with a biomarker of accelerated aging as a potential mechanistic factor. Methods: Body composition, metabolic, cardiovascular, musculoskeletal, and psychological morbidities were objectively evaluated in 208 COPD patients (age 62 ± 7 years, 58% males, FEV Chronic obstructive pulmonary disease (COPD) is considered a complex, heterogeneous, and multicomponent condition . Comorbiwww.isrctn.com.The current cross-sectional analysis is part of the “Individualized COPD Evaluation in relation to Ageing” (ICE Age) study  conducteDetails of patient characterization, (co)morbidity assessment, and references of the (co)morbidity definitions are provided in 2; hyperglycemia as plasma glucose concentration ≥ 5.6 mmol/L; insulin resistance as HOMA index ≥ 4.29/4.43 for women/men; dyslipidemia as plasma triglyceride concentration > 1.7 mmol/L or HDL < 1.29/1.03 mmol/L for women/men; hypertension as systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg; arterial stiffness as PWV > 10 m/s; atherosclerosis as c-IMT > 0.9 mm; underweight as BMI < 21 kg/m2; low muscle mass as FFMI < 14.62/17.05 kg/m2 for women/men; osteoporosis as a T score < −2.5/−2.8 in women/men; renal impairment as estimated GFR < 60 mL/min/1.73 m2); and anxiety or depression as a HADS score ≥ 10 points. Thirteen (co)morbidities were identified based on predefined cut-offs, mostly corresponding to our previous cluster analysis . In summwww.viscovery.net; Vienna, Austria). Self-organizing maps (SOMs) were used to create an ordered representation for the presence of COPD and (co)morbidities. The SOM method can be viewed as a non-parametric regression technique that converts multidimensional data spaces into lower dimensional abstractions. It generates a non-linear representation of the data distribution and allows the user to identify homogenous data groups visually. Patients were primarily ordered by the presence/absence of COPD and secondarily by their overall similarity concerning their present (co)morbidities and also by the degree of its presence given by parameters from which the (co)morbidities were calculated. Based on the created SOM model, clusters were generated using the SOM–Ward Cluster algorithm that applies the classical hierarchical method of Ward on top of the SOM topology. Summary variables are presented as mean ± standard deviation for quantitative variables (except pack-years: median (interquartile range)), and percentage for discrete variables. Comorbidities, clinical characteristics, and telomere length were compared between: (1) The COPD and control group; (2) each (co)morbidity cluster and its corresponding group (COPD or control group); (3) each parallel (co)morbidity cluster in COPD and controls, using the integrated two-sided t-test with a confidence of 95%. Post-hoc in SPSS 19.0, additional binary logistic regression models were run within each group , using the cluster as a dependent variable and telomere length as an independent variable.Statistical analyses were performed using Viscovery SOMine 7.1 by Viscovery Software GmbH  and 200 non-COPD controls (61 ± 7 years) were included . PatientFive comorbidity clusters were identified in the COPD patients, and three (co)morbidity clusters in the non-COPD group .n = 46 (22%)) had significantly fewer morbidities compared to the whole COPD group (n = 27 (13%)) had the highest prevalence of hypertension, arterial stiffness, and osteoporosis, but a lower prevalence of metabolic features. Cluster C3 ) had a higher prevalence of obesity, hyperglycemia, insulin resistance, and dyslipidemia, but also cardiovascular features. Cluster C4 ) had the highest number of subjects with anxiety and depression. Cluster C5 ) had the highest portion of subjects with underweight and low muscle mass. Cluster C1 ) and was characterized by a clearly fewer number of (co)morbidities (n = 34 (17%)), hypertension and arterial stiffness was present in all subjects. Cluster X3 ) had the highest portion of subjects with obesity, hyperglycemia, insulin resistance, and dyslipidemia. Cluster X1 (“Less (co)morbidity” cluster in controls) was a large cluster (bidities . In clusCluster X1 (“Less (co)morbidity”) was a younger, predominantly female cluster with less pack-years, and a lower cardiovascular risk . Cluster2 of the table). In summary, COPD subjects in the “Less (Co)morbidity” cluster (C1) had more (co)morbidities than those in the parallel control cluster (X1), including hyperglycemia, dyslipidemia, obesity, arterial stiffness, and renal impairment. The presence of (co)morbidities in the “Cardiovascular” clusters  was mainly comparable, except for a higher frequency of osteoporosis and less dyslipidemia in the COPD cluster C2. Both cluster C3 and X3 had a high prevalence of metabolic diseases. The “Metabolic” COPD cluster (C3) was older, more overweight, and had more (co)morbidities than cluster X3, in particular insulin resistance, hypertension, and arterial stiffness. Details of the comparison of the parallel (co)morbidity clusters “Less (Co)morbidity”, “Cardiovascular”, and “Metabolic” are shown in p = 0.05) (Telomere length was reduced in the patients with COPD compared to controls . The mea = 0.05) . This study showed that a “Psychologic” and “Cachectic” comorbidity cluster were specifically related to COPD, and that “Cardiovascular”, “Metabolic”, and “Less-(co)morbidity” clusters were also present in aging controls, while it validates the previously identified comorbidity clusters . AccelerUsing a similar statistical approach, but a slightly different assessment of comorbidities, the current study identified a predominantly similar comorbidity clustering, compared to that in the CIROCO cohort , except A systematic review of studies that derived COPD phenotypes using unsupervised methods identified two recognizable phenotypes with poor longitudinal health outcomes across multiple studies . A phenoThe formation of emphysematous lesions might be promoted by cellular senescence which infers with tissue regeneration . In turnAnxiety and depression often co-occur ,22 and aUniquely, this cluster study included elderly controls, allowing for a meaningful comparison of their—rigorously and objectively assessed—comorbidity profiles with those of patients with COPD, although the control population was, on average, one year younger. Most of them suffered from several morbidities, which underlines the importance of including a control population when studying multimorbidity from the perspective of an index disease . WhereasConsiderations: Most COPD patients were recruited in a tertiary care pulmonary rehabilitation setting, which limits the external validity of the current findings. Reflecting clinical reality, patients with COPD had a more substantial smoking history than their controls. While influenced by smoking, reduced telomere length in COPD compared to smoking and non-smoking controls was consistently reported ,20,26,27This study confirms previously identified clusters of objectively identified multiple comorbidities in a well-characterized cohort of patients with COPD and adds to this the comparison to a non-COPD elderly population, and the evaluation of telomere length between clusters, as a measure of biological aging. The current findings underline the complexity and heterogeneity of patients with COPD. Interestingly, exacerbation frequency, dyspnea, and functional exercise performance were similar amongst COPD comorbidity clusters, emphasizing again that detailed phenotyping is needed beyond the aforementioned clinical outcomes. In addition, a subgroup with low nutritional status and more severe lung function impairment, and a well-represented subgroup with psychological conditions are more specifically related to the presence of COPD and are important subgroups for targeted mechanistic and intervention studies. Reduced telomere length, is present across various comorbidity clusters in COPD, but did not seem a major determinant of (co)morbidity clustering itself.


The purpose of the meta-analysis was to evaluate the relationship between serum asymmetric dimethylarginine (ADMA) level and microvascular complications in diabetes mellitus (DM) including diabetic retinopathy (DR), diabetic neuropathy (DN), and diabetic nephropathy.2 statistics were applied to evaluate statistical heterogeneity. Subgroup analyses were conducted and publication bias was assessed by Egger's test. Studies were comprehensively identified by searching Web of Science, Embase, and PubMed databases up to August 30, 2018. The meta-analysis was carried out to compare the difference of serum ADMA concentrations of DR, DN, and diabetic nephropathy patients with healthy controls. The Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality were applied to assess the methodological quality. Chi-squared Q test and II2 = 77.0%, p < 0.001). Compared with DM without microvascular complications, circulating level of ADMA was significantly higher in DM with microvascular complications . Sensitivity analysis suggested that the results of this meta-analysis were shown to be stable. There was no significant publication bias (P=0.823). Ten studies were finally entered in the meta-analysis. Statistically significant heterogeneity was observed across these studies ( Elevated ADMA levels correlate with diabetic microangiopathies such as DR and diabetic nephropathy. ADMA may play an important role in the pathobiology of microvascular complications of diabetes. Diabetes mellitus (DM) is caused by a defect in insulin secretion and/or insulin resistance leading to persistent hyperglycemia, affecting millions of people worldwide . Most loStudies demonstrate that endothelial dysfunction plays a vital role in the development of diabetes-associated microvascular complications , 4. AsymTherefore, meta-analysis of all relevant studies was conducted to assess the association between ADMA level and diabetic microvascular complications.The meta-analysis was performed based on the Meta-Analysis of Observational Studies in Epidemiology: A Proposal for Reporting (MOOSE). We comprehensively searched Web of Science, PubMed, and Embase to identify related articles published before August 30, 2018. No language restriction was imposed. Literature search was performed using keywords as follows: “N,N-dimethylarginine”; “N(G1), N(G1)-dimethylarginine”; “N(G)-dimethylarginine”; “asymmetric dimethylarginine”; “guanidine-N,N-dimethylarginine”; “N(G), N(G)-dimethylarginine” or “dimethyl-L-arginine” and “diabetic retinopathy” or “retinopathies, diabetic” or “diabetic retinopathies”; “retinopathy, diabetic” and “diabetic neuropathies” or “diabetic neuropathy” or “diabetic autonomic neuropathy” or “diabetic autonomic neuropathies” or “diabetic neuralgia”; “diabetic neuralgias” or “painful diabetic neuropathies” or “painful diabetic neuropathy” or “asymmetric diabetic proximal motor neuropathy” or “diabetic asymmetric polyneuropathy” or “diabetic asymmetric polyneuropathies” or “diabetic mononeuropathy” or “diabetic mononeuropathies” or “diabetic mononeuropathy”; “diabetic mononeuropathy simplices” or “diabetic amyotrophy” or “diabetic amyotrophies” or “diabetic polyneuropathy” or “diabetic polyneuropathies” and “diabetic nephropathy” or “nephropathy, diabetic”, “DN”. The reference lists were also scanned to acquire the additional relevant articles. We considered all potentially eligible publications regardless of language or the primary outcome to avoid biases. Additionally, a manual search from the reference list of key articles published in English was used to identify additional papers. No language or date limitations were set.Study design had to meet the following criteria: the study should report the correlation of serum ADMA level in DM to retinopathy, neuropathy, or nephropathy; they were observational studies ; study data should be represented by mean ± SD or can be converted based on the information in the literature; studies are with control group of DM without retinopathy, neuropathy, or nephropathy; patients are of any gender, age, region, or race with DM.We excluded studies if the same studies came from different database; if they were case reports, animal studies, and summaries of personal experience; if there were no controls or absence of DM with retinopathy, neuropathy, or nephropathy.The literature search, document selection, and data extraction were performed independently by two investigators (Jing-liu and Kuanrong He). The Newcastle-Ottawa Scale (NOS), a representative tool, was used to measure the quality of case-control or cohort studies , includiThe following data were collected: (1) first author's name; (2) publication date; (3) country of the study; (4) disease duration; (5) number of cases and controls considered; (6) mean age; (7) mean serum ADMA levels of cases and controls (presented as mean + SD). Disputes were resolved via consultation or discussion with a third reviewer (Wen Chen).2 statistics were applied to evaluate statistical heterogeneity of changes in ADMA levels in DM with retinopathy, neuropathy, nephropathy, and controls. If there was a statistical homogeneity between studies (p < 0.05 or I2 > 50%), we used a random-effect model; otherwise we used a fixed-effect model [We used the statistical software program Stata12.0. The data was presented as mean ± SD. Chi-squared Q test and Ict model . SubgrouEgger's test  was usedA flow chart of the article selection process is presented in I2 = 77.0%, p < 0.001). A random-effects model was applied. Compared to controls, DM with microvascular complications had significantly higher ADMA serum levels  (There was significant heterogeneity (< 0.001) . Subgrou< 0.001) . In addi< 0.001) .In the sensitivity analysis, no study individually altered the corresponding pooled WMDs –0.062 , P<0.05), suggesting that the results of this meta-analysis were stable. Moreover, no significant publication bias was found by the Egger's test (P=0.823).Our evidence suggests that DM with microvascular complications had increased serum levels of ADMA.DR, a major microvascular complication of DM, is a leading cause of preventable blindness in working-age adults. ADMA, a strong and independent predictor of endothelial dysfunction, is increasingly a focus of interest in DR. Evidence indicates that plasma ADMA levels are markedly elevated in diabetic patients with advanced retinopathy , 21. ThiDiabetic nephropathy, characterized by a decline in glomerular filtration rate and proteinuria, has become the leading cause of end-stage renal disease and the strongest predictor of mortality in diabetes . ADMA isDN is one of the major diabetic microvascular complications and mainly affects both autonomic and peripheral nerves. There is emerging evidence that ADMA is associated with DN . OxidatiTo our knowledge, this meta-analysis is the first that assessed the relationship between ADMA level and DM microvascular complications. However, this meta-analysis has several limitations. First, high heterogeneity was observed. A random-effects model and sensitivity analysis were used to adjust for heterogeneity. Egger's tests illustrate that no publication bias was found in any analysis. Second, subgroup analysis was not successful in detecting the source of heterogeneity. In some studies, there was a significant difference in baseline information  between the case group and the control group. The rigor of the experimental design and the pertinence of the inclusion criteria for case groups or control groups between the various included studies may have a certain impact on the results. In addition, to a certain extent, other factors such as the type of study object and laboratory assay for serum ADMA level affected the evaluation. Moreover, the included studies are not randomized controlled trials and are thus vulnerable to potential bias.In conclusion, elevated ADMA are associated with diabetic microangiopathies such as retinopathy and nephropathy. ADMA plays an important role in the pathobiology of microvascular complications of diabetes. We suspect that ADMA may be a target for diagnosis and treatment of microvascular manifestations in diabetes.


Glycine max) has been grown in rotation with ruzigrass (Urochloa ruziziensis) or fallow for 10 years, with the application of 0, 13, and 26 kg ha−1 of P, was evaluated for two consecutive years. Soil P desorption kinetics was assessed using diffusive equilibrium (DET) and gradient in thin films (DGT) techniques, as well as the DGT-induced fluxes in soils model (DIFS). Microbial biomass P (MBP) was assessed to verify if soil solution P (PDET) was reduced due to immobilization by microorganisms. Ruzigrass reduced MBP and PDET especially when P fertilizer was applied. The concentration of labile P (PDGT) was also lower after ruzigrass than in fallow. The soil ability to resupply P to soil solution was lower after ruzigrass regardless of P rates due to a slower desorption in response to the perturbation imposed by DGT. Growing ruzigrass as cover crop in the soybean off-season decreases soil P availability regardless of P fertilizer application rates by fundamentally reducing P mobility and P resupply from soil solid phase into soil solution.The use of grasses as cover crops in the off-season of cash crops under no-till has been largely adopted. However, soil phosphorus (P) uptake was previously shown to be reduced when ruzigrass is introduced in the rotation, affecting the viability and sustainability of this cropping system. The objective of this study was to assess the effect of ruzigrass on soil P availability and desorption kinetics under different P fertilizer application rates. A long-term field experiment where soybean ( •The use of ruzigrass as cover crop affect soil P availability in the long-term.•Soil P desorption kinetics was assessed using diffusive gradient in thin films (DGT).•The use of DGT provided new insights into P availability, by considering the P diffusion and resupply process.•Ruzigrass decreases P availability by reducing P mobility and resupply from soil solid phase into soil solution. Germ. and C.M. Evrard) Morrone and Zuloaga] has been preferentially used as cover crop in the off-season of cash crops and as forage in integrated crop-livestock systems than other Urochloa grasses, due to its ease of management in desiccation, high yield, palatability, nutritional quality for animal feed, high adaptability to poor phosphorus (P) soils, long residue persistence protecting the soil, and adaptability to climatic conditions during off-season (Glycine max (L.) Merrill] grain yield and leaf P concentration after ruzigrass than fallow in four consecutive years. A lower P uptake by maize (Zea mays L.) was also observed after ruzigrass than in fallowed soil  and aluminum (Al) oxides with SOM . The lowHordeum vulgare L.) (Triticum aestivum L.)  , and wheivum L.) . AccordiThe objective of this study was to test the long term effect of ruzigrass on soil P availability and desorption kinetics at different P fertilizer application rates at field conditions. Specifically, we aimed to test the hypothesis that growing ruzigrass (cover-crop) in the off-season reduces P availability to the soybean (cash-crop) due to reduced soil P desorption rates.22.1−1 of sand and 210 g kg−1 of clay. The area selected for the experiment has been under no-till since 1998. From 1998 to 2005, all plots received a total of 96 kg ha−1 of P as triple superphosphate (TSP), and soybean was cropped in the summer in rotation with black oat  and triticale  in the fall-winter, and with pearl millet  in the spring. From 2006 when the present experiment started, soybean has been grown in rotation with ruzigrass or fallowed, with the application of 0, 13, and 26 kg ha−1 of P as triple superphosphate in the soybean seed furrow each year. The experimental design was a 2 × 3 factorial in randomized complete block design, with four replications. Plots were 8.0 m long × 5.0 m wide. In the fallow treatment, weed growth was random and sparse, with insignificant dry matter production by the end of the off-season period.A long-term field experiment located in Botucatu, State of São Paulo, Brazil , was carried out for two years (2014 and 2015). The soil is a Rhodic Hapludox  with 670Six soil subsamples were randomly collected per plot to compose one sample per depth per field replication, using a 50 mm diameter core sampler, at depths of 0–5, 5–10, 10–20 and 20–40 cm, in November 2014 and 2015 after ruzigrass desiccation. The samples were air-dried and passed through a 2-mm sieve for subsequent chemical analysis.2.2−1 calcium chloride (CaCl2) suspension (1:2.5 soil/solution), potential acidity (H + Al) at pH 7.0 was estimated by the Shoemaker-McLean-Pratt (SMP) pH buffer method (resin) and exchangeable Ca, Mg, and K were extracted with a mixture of anionic resin (IRA-400) and cationic resin (IR-120), following method described by 3-form using a solution of 0.1 mol L−1 sodium bicarbonate (NAHCO3), pH 8.5. Briefly, 2.5 cm3 of air-dried soil and a glass marble about 1.8 cm of diameter were added to 25 mL of deionized water. The glass marble was used to complete disaggregate the soil, shaking on an orbital shaker for 15 min at 220 rpm. The glass marble was then removed, and 2.5 cm3 of the resin mixture was added, and the samples were shaken overnight for 16 h at 220 rpm. The separation of the resin from the soil was performed by sieving, using a 0.4-mm sieve. The resin was eluted and shaken in 50 mL of a solution of 0.2 mol L−1 hydrochloric acid (HCl) and 0.8 mol L−1 ammonium chloride (NH4Cl) to extract P, Ca, Mg, and K from the resin. The P concentration was determined according to Selected chemical characteristics of the soil of the experimental area are presented in r method , and cat2.32)  with ultra-pure Milli-Q (MQ) water (Millipore).Soil labile P was measured using diffusive gradient in thin films (DGT) and soil solution P was measured using diffusive equilibrium in thin films (DET) as in 2) . Between2SO4 solution, 0.25 mol L−1. The DGT and DET devices were deployed in duplicates for each experimental replicate. The P concentration in the eluent was measured using the malachite green method (4)6Mo7O24)-4H2O] and then with the color obtained after addition of malachite green oxalate (C52H54N4O12). The molybdate reactive P (Pi) was read on a Multiskan spectrophotometer .Samples of 80 g of dried soil were placed in a container and wetted with MQ water to approximately 50% of maximum water holding capacity to re-establish microbial activity, and incubated for 72 h at 24–25 °C. After incubation, the soil slurry was prepared by adding MQ water and mixing the soil until maximum retention was reached . The DETn method . The malDET) is expressed as the equilibrium concentration to soil solution P. The concentration of labile P (PDGT) at the surface of the DGT devices was calculated using Eq. 2), t is the deployment time, Δg is the total thickness of the diffusive gel layer and the filter membrane, and D is the diffusion coefficient of P in the diffusive gel. The concentration of P in the diffusive layer of DET devices  between PDGT and soil solution P (PDET) was calculated using a dynamic numerical model of the DGT-soil system  artificially to 1 × 1010 s (extremely slow response) and Kd as 10−10 cm3 g−1 . The relative resupply from solid phase (R-Rdiff) was calculated subtracting the Rdiff from the R ratio.The diffusive only ratio (RDGT could be converted to an effective concentration (PE) using eq. The Presin provides an estimate of the labile solid phase pool, the partition coefficient between P in the solid and solution phases (Kd) was calculated as Presin/PDGT. Using the DIFS model, the Tc was obtained, thereby the desorption rate constants (k−1) can be estimated as in Eq. Assuming that P2.4−1 HCl and the concentration of P was measured by the malachite green method. The MBP was estimated as the difference between samples extracted with and without hexanol. A correction factor to account for sorption of P to soil solid phase during extraction was determined from soil samples spiked with 20 mg g−1 of P immediately before adding the resin strips.The DGT analysis was performed in non-sterile soil in order to better represent the field conditions. Therefore, some of the desorbed P from the soil solid phase can be intercepted and locked (immobilized) in the microbial biomass before it accumulates on the DGT. The microbial biomass P (MBP) was simultaneously assessed in order to understand if the observed changes on P mobility and availability were affected by P immobilization by the soil microbial community. The MBP was measured according to 2.5p < 0.05), treatment means were compared by Student's t-test (p < 0.05).Data from each soil layer were subjected to analysis of variance using a general linear model (Proc GLM) in SAS software , considering a 2 × 3 factorial in randomized complete block design, with four replications. When the F test was significant   and seemed to be more appropriated since it gave R values at reasonable ranges; while other methods seemed to contain suspended particles and overestimated solution P concentration, often gave unreasonably low R values. The use of DET to minimize solution P estimation artifacts was also discussed by The P μg L−1) . Due to  μg L−1) . The useE is an effective concentration which convert all P supply to DGT device as diffusion only  was markedly higher than from the solution phase (PDET), and ruzigrass resulted in a lower P resupply from a solid phase below 5 cm depth, in both years, mainly when P was applied (The Pion only . It repr in 2015 . The pro applied .d represents the labile P in the soil solid phase (adsorbed and precipitated P) and soil solution P, accounting for the easily desorbed and readily soluble forms of inorganic P. Interestingly, the Kd was higher after ruzigrass than fallow at 0–5 and 10–20 cm in 2014 when P was not applied, and at 5–10 cm in both years, when 26 kg ha−1 of P was applied  was very low, averaging only 0.02, and had little variation across the treatments due to the similarity of porosity and particle concentration, similar to what was observed by diff) was very similar to the total R value  (Avena sativa L.)   and oat tiva L.) , the useuzigrass . Therefo4The long term use of ruzigrass as cover crop in the soybean off-season decreased P mobility regardless of P rates by reducing P diffusion and resupply from the soil solid phase, in contrast to fallow, accepting the hypothesis that growing ruzigrass reduces P availability to soybean. Under ruzigrass treatment, soil solution P cannot be sustained at the same levels of fallowed soils during the continuous P depletion generated by DGTs (and roots), even at higher solid-to-solution P concentration gradients. This indicates that ruzigrass may have caused more P to be retained in the soil solid phase compared to the fallow treatment. Depletion induced P resupply from the soil solid phase to solution is the main mechanism affecting P availability in the studied soil. Therefore, long-term soybean ruzigrass crop rotation resulted in a lower soil P availability, which may have a significant impact on crop production.DET), effective soil phosphorus concentration (PE), and desorption rate constant (k−1) in four soil depths with ruzigrass and different P application rates, in 2014 and 2015.Phosphorus concentration in soil solution phase (PTable S1The following is the supplementary data related to this article.


Patient A is hemizygous for a second MRXSB mutation originally identified by Bain et al in three females within the nuclear localization sequence of HNRNPH2 ,HNRNPH2 , suggesting that other mutations within this gene are capable of producing a range of similar phenotypes  was performed on the patient and biological parents revealing a de novo, missense mutation, HNRNPH2(R206W), that has been previously associated with MRXSB.Patient B is an 8‐year‐old male with global developmental delay, microcephaly, failure to thrive, intractable epilepsy, hypotonia, and cortical visual impairment. A vagal nerve stimulator was placed at age 2. At certain times in his life he would have over 10 generalized tonic‐clonic and dozens of myoclonic seizures daily. He was non‐verbal and did not follow commands. There were frequent athetoid movements of the upper extremities. Dyskinetic movements of the face and tongue were observed. Feeding problems required placement of a G‐tube.HNRNPH2  that was confirmed by Sanger sequencing. The variant has a CADD PHRED of 22.4 and is considered likely pathogenic by the American College of Medical Genetics (ACMG) classification  with a score of 0.00 , and MutationTaster (http://mutationtaster.org) predicts it is disease causing . WES revealed five reference reads (7%) and 64 variant reads (93%) at the position, implying low level mosaicism for the reference allele. Phenotypic overlaps with MRXSB include developmental delay, seizures, tone abnormalities, and growth problems.WES identified a private, de novo, missense mutation in GRIA3 , encoding a glutamate receptor associated with mental retardation, X‐linked 94. One male is hemizygous for the mutation, and one female is a carrier in gnomADHNRNPH2 has been associated with microcephaly.GRIA3, only five are missense mutations (<4.0%), implying loss‐of‐function of GRIA3 is required for pathogenicity.A second variant with an ACMG classification of “uncertain significance” (rules: none meet criteriahttp://genetics.bwh.harvard.edu/pph2) prediction algorithm predicts GRIA3(Q140R) as “probably damaging” with a score of 0.999 , while the private HNRNPH2(R114W) mutation is predicted “benign” with a score of 0.105 . However, the known clinical pathogenic variant carried by patient A, HNRNPH2(R206W) is also predicted by PolyPhen‐2 to be “benign” with a score of 0.028 . Therefore, PolyPhen‐2, alone, is not a good predictor for HNRNPH2 pathogenicity, and comparison to the GRIA3(Q140R) score may not be appropriate. Rather, classification via ACMG guidelines, which also accounts for many prediction algorithms, should be considered the final predictor of pathogenicity. Therefore, we do not believe that the causal variant in patient B is in the GRIA3 gene, but is the private, de novo mutation, HNRNPH2(R114W), although functional studies will be required to conclusively eliminate either variant as contributive to the phenotype.Interestingly, the PolyPhen‐2  research protocol at the Translational Genomics Research Institute (TGen). Written consent for the both children was obtained from the parents. Verbal assent was obtained for participants 7‐17 years of age when appropriate. The study protocol and consent documents were approved by the Western Institutional Review Board (WIRB # 20120789).2


Feature screening has become a real prerequisite for the analysis of high-dimensional genomic data, as it is effective in reducing dimensionality and removing redundant features. However, existing methods for feature screening have been mostly relying on the assumptions of linear effects and independence (or weak dependence) between features, which might be inappropriate in real practice. In this paper, we consider the problem of selecting continuous features for a categorical outcome from high-dimensional data. We propose a powerful statistical procedure that consists of two steps, a nonparametric significance test based on edge count and a multiple testing procedure with dependence adjustment for false discovery rate control. The new method presents two novelties. First, the edge-count test directly targets distributional difference between groups, therefore it is sensitive to nonlinear effects. Second, we relax the independence assumption and adapt Efron’s procedure to adjust for the dependence between features. The performance of the proposed procedure, in terms of statistical power and false discovery rate, is illustrated by simulated data. We apply the new method to three genomic datasets to identify genes associated with colon, cervical and prostate cancers. Feature screening, as a key and inevitable step in many bioinformatics applications, is effective in reducing dimensionality and removing redundant features. Because the quality of selected features may greatly affect the subsequent analysis and conclusions, a reliable screening procedure is essential in practice. In general, the ideal feature screening should have high sensitivity and specificity simultaneously, as too many false positives could result in poor model interpretability while too many false negatives may cause lack of fit and inaccurate prediction. In statistics and bioinformatics literature, there has been a wealth of feature screening techniques that can be roughly classified into two categories, namely model-based screening and model-free screening. The model-based methods often rely on a class of specific models such as generalized linear model and nonparametric regression model –4. HowevDifferent types of data require different feature screening techniques. For instance, the dependence between a continuous response and continuous features could be quantified by correlation-based measures such as Pearson’s correlation, rank-based correlation, and distance correlation –10. TherThe remainder of the paper is structured as follows: In Section Methods, we formulate the problem and introduce the two-step procedure including edge-count test and Efron’s multiple testing procedure. In Section Results, we conduct a simulation study to evaluate the performance of the proposed procedure in terms of statistical power and false discovery rate control under various settings. The new method is applied to three real genomic datasets to search genes that differentiate cancer and normal subjects. We discuss the new method with some future work perspectives in Section Discussion and conclude the paper in Section Conclusions.J categories (J < ∞) and the features are continuous. For example in genomics, the outcome response can be normal/diseased, cancer subtypes or tumor stages and each feature can be the expression level of a gene. Existing model-free screening based on correlation measures [X1, …, Xp} be p features (p can be large), and {1, …, J} be the sampling space of response variable Y. With N independent observations of {Y, Xi,1≤i≤p}, we test the independence between Y and Xi, which is equivalent to testing equality of J conditional distributions, i.e.,Xi in group Y = j. To test if Hi0 is true, we employed a modified edge-count test which is proved more powerful in detecting difference between multiple multivariate distributions [J groups and indexed them by k was denoted by yk. A d-MST is then constructed on the pooled samples using the standard Kruskal’s algorithm [G simultaneously represents the similarity graph and the set of all edges, while |G| denotes the total number of edges throughout the paper. For the edge connecting samples k and k′, i.e., , we define Rj as the number of edges connecting samples from same group j, i.e.,R = T, V−1(R) represents the inverse covariance matrix of R. The test statistic defined here simply quantifies the deviation of  from their expected values under permutation null, i.e., S for J = 2, J groups asymptotically follows a Chi-square distribution with J degrees of freedom under mild regularity conditions. To illustrate the results, for an edge e in graph G, we letWe consider a general setting where the outcome variable is discrete with measures , 6 were measures . In thisibutions , 16, 17.ibutions  applied lgorithm . Unless Theorem 1. If |G| = O(N), e∈G|Ae||Be| = o(N3/2), thenwhere j = 1, …, J is the group index.R1, …, RJ) can be derived as follows:The expected values and covariance matrix of (n−1/2 and there are three conditions on the similarity graph (stated in the main Theorem above). |G| ∼ O(N) requires that the density of the graph is of the same order as the pooled sample size. e∈G|Ae||Be| ∼ o(N3/2) requires there is no cluster of small hubs [Y. Increasing sample size generally results in better accuracy of approximation, and the use of slightly denser graph  may result in better accuracy. These findings are consistent with the simulation results for two groups (J = 2) [nj ≤ 10, j = 1, …, J), however, the asymptotic distribution might not work well, and in such cases, it is safer to use a permutation p-value based on our test statistic S.The convergence rate of the asymptotic result is the usual all hubs . These call hubs , we ther (J = 2) . For smaXi can be a random vector), i.e., our method can be used to select feature sets. One interesting application is to search biological pathways or gene sets that are associated with certain phenotypes [It is noteworthy to mention that the main theorem also applies to multi-dimensional features  [S1, …, Sp} into z-values by quantile normalization−1(⋅) represents the inverse cumulative distribution function of N. Following the notations in Efron (2007), let P0 = 2Φ(1) − 1, ϕ(⋅) represents the probability density function of N. Here, A(z) is used to control the influence of correlation between test statistics  is close to 1, thus the procedure is same as BH procedure). The critical value can be obtained as follows:α , one can solve for the cutoff z0 and reject zi > z0. This testing procedure asymptotically controls the FDR at the desired level under some mild regularity conditions (though it might be slightly conservative for some cases) and it works well under all settings in our simulation study. The detailed proof and regularity conditions for Gaussian case can be found in Liu (2017)  . Unlike n (2007) , 26. To Y ∈ {0, 1}  and p continuous features {X1, …, Xp} with sample size N (p ≥ N). Four high-dimensional settings (each setting refers to a combination of model and feature dependency structure) were used to generate the data. To be precise, let k ∈ {1, 2, …, N} be the index of sample, and i ∈ {1, 2, …, p} be the index of feature, where we set p = 500 and N = 50, 100, 200, 500 respectively. In addition, we assumed that only the first 10 features, {X1, …, X10}, were associated with Y and the other 490 features were redundant. The transformation functions {hi(Xik), 1 ≤ i ≤ 10} were set as hi(Xik) = Xik for 1 ≤ i ≤ 3 (linear transformation), i ≤ 6 (nonlinear monotonic transformation), i ≤ 8 (nonlinear non-monotonic transformation) and hi(Xik) = sin(2πXik/3) for 9 ≤ i ≤ 10 (nonlinear non-monotonic transformation), representing a combination of linear effects and nonlinear effects. The four transformation curves were shown in The simulation studies in this part examined the performance of the proposed procedure under several different settings. Without loss of generality, we considered a binary outcome variable Y and {X1, …, X10}, we considered two different models:To establish the relation between Yk ∼ Bernoulli(πk), β1 = β2 = β4 = β6 = β7 = β9 = 0.5, and β3 = β5 = β8 = β10 = −0.5Logistic regression model: ϵk ∼ N, β1 = β2 = β4 = β6 = β7 = β9 = 0.5, and β3 = β5 = β8 = β10 = −0.5Latent variable model: Furthermore, to evaluate the effect of feature dependencies on statistical power and FDR control, we generated the data by two methods:Xik ∼ Unif for 1 ≤ i ≤ 500.Independent features: Zik}i≤5001≤ ∼ N500 and Σ is a random correlation matrix containing both positive and negative elements (generated by R package clusterGeneration). In addition, we conducted an interval truncation (between -1.5 and 1.5) for the samples to avoid extreme values.Dependent features: The following six testing procedures were applied to each combination of model and feature dependency structure above, namely logistics model with independent features, logistic model with dependent features, latent variable model with independent features and latent variable model with dependent features:Edge-count test with Efron’s multiple testing procedureEdge-count test with Benjamini-Hochberg procedureWelch’s t test with Efron’s multiple testing procedureWelch’s t test with Benjamini-Hochberg procedureMutual information z-test with Efron’s multiple testing procedureMutual information z-test with Benjamini-Hochberg procedurevi was approximated by Welch-Satterthwaite equation and the test statistics ti was calculated by the standard formula for t test with unequal variances:n1, n0} stand for the sample sizes for Y = 1 and Y = 0, Xi in two groups, respectively.In the edge-count test, a 3-MST was constructed as the similarity graph for better approximation of p-values . To implY and Xi, and it can be computed as Y and Xi, and Y and Xi. By the classical decision theory, infotheo (https://cran.r-project.org/web/packages/infotheo), where the continuous Xi was discretized into N1/3 bins.To test whether the mutual information is zero, we used the following Fisher-z transformation:pothesis , 28. Theα = 0.10. Figs The targeted FDR was chosen to be X7 was missed by Welch’s t test and mutual information test but captured by the edge-count test in our simulation. The reason is that feature X7 has a quadratic effect  becomes subtle and undetectable. However, feature X7 showed very different patterns in two groups  which was detected by the edge-count test. α = 0.10. As can be seen from our simulation results , the mutual information z-test exhibited extremely low power, therefore we did not consider this method for real data analysis.We first applied the new procedure to a colon cancer dataset  to searclts Figs  and 3, wHsa.3180, Hsa.1804, Hsa.40177, Hsa.4937, Hsa.2157, Hsa.44676, Hsa.2847, Hsa.3026, Hsa.108, Hsa.11632, Hsa.27716. Figs Hsa.108 and Hsa.2157, where the sample distributions in normal and tumor groups were significantly different from each other but both skewed. Our edge-count test successfully detected this difference, while the Welch’s t test failed to detect it due to close sample means . Similar results were observed for the other nine genes  promotes lung adenocarcinoma progression at an early stage [Hsa.4937 (CREBBP) acts as a potent tumor suppressor in small cell lung cancer, and inactivation of CREBBP enhances responses to a targeted therapy [Hsa.44676 (VAV1) promotes cancer growth by instigating tumor-microenvironment cross-talk via growth factor secretion [Hsa.108 (POSTN), a matricellular protein-coding gene, has been shown to regulate key aspects of tumor biology, including proliferation, invasion, matrix remodeling, and dissemination to pre-metastatic niches in distant organs [Hsa.11632 (RYR1), together with RYR2 stimulates apoptosis of prostate cancer cells [As previously reported in the literature, several of these 11 genes are associated with human cancers. To name a few, gene ly stage . Gene Hs therapy . Gene Hsecretion . Gene Hst organs . Gene Hser cells .glm), followed by a Benjamini-Hochberg procedure with α = 0.10. We detected a total of 28 significant genes, and 26 of them were consistent with the selection by Welch’s t test. However, this model fails to detect any of the 11 genes with nonlinear effects. The logistic regression model was further modified by adding a quadratic term in order to capture the nonlinear relations, however, this modification did not lead to any improvement.The results from colon cancer data well confirmed our findings from simulation study, i.e., the edge-count test can not only detect the mean difference, but also detect distributional differences, thus it is more sensitive to nonlinear change compared to normal-based tests such as t test, F test and Hotelling’s t test. Additionally, we conducted feature selection using p-values from a simple logistic regression .m-MST based on Euclidean distance as the similarity graph, and the main result There are several possible extensions of the proposed selector. For instance, in addition to feature screening, our method can also be used to select feature sets. One appealing property of the edge-count test is that it only requires a similarity graph constructed on the samples. In practice, one could simply build a MST or S1, …, Sp} in our framework, a subsampling without replacement might be needed in order to get independent samples of {S1, …, Sp}, however, the estimation may require relatively large sample size, e.g., N > 1, 000.Efron’s multiple testing procedure was used in our method to control FDR under feature dependencies, but it might be replaced by other recently developed procedures. For instance, when the test statistics are positively dependent, one may also use Benjamini-Hochberg-Yekutieli (BHY) procedure to control FDR . Fan et Identification of disease-related biomarkers from large-scale data is essential in many genomic studies. However, existence of nonlinear effects and strong feature dependencies make existing methods inappropriate and unreliable. In this work, we presented a model-free feature screening method which is sensitive to both linear and nonlinear effects. In addition, the dependence-adjusted multiple testing procedure can well control the false discovery rate under feature dependencies. On a whole, we put forward a simple yet effective testing procedure that reliably captures different types of effects. Although we used gene expression data for illustration in the paper, the proposed test can be readily applied to other data types and problems, such as DNA methylation data and protein expression data and pathway selection.S1 FileThis file contains additional simulation studies and real data applications, as well as the technical report by Zhang, Mahdi and Chen.(PDF)Click here for additional data file.


Carcinoma of the esophagogastric junction (EGJ) is a type of upper digestive cancer that occurs within 2 cm above or below the EGJ regardless of the histological type. Most cases of carcinoma of the EGJ are detected at an advanced stage and thus show a poor prognosis , 2. The Alpha-fetoprotein (AFP) is a useful tumor marker for primary hepatocellular carcinoma and yolk sac tumor . AlthougA 75-year-old man with hypertension, diabetes, and dyslipidemia underwent esophagogastroduodenoscopy to investigate the cause of a high CEA value and dysphagia in December 2010. An ulcerative circular tumor was detected at the EGJ  .–20.13–20n = 3) , 17, 19, [n = 3) , 15, 18, [n = 1) , 18–20.


Bombyx mori cocoons, was blended with gelatin (G) to produce materials composed of varying ratios of the two components . Cell compatibility to these materials was first confirmed in two-dimensional culture and found to be equivalent to standard tissue culture plastic, and better than SF or G alone. The mechanical properties of the blends were investigated and the blended materials were found to have increased Young's moduli over SF alone. Microcarriers of SF/G blends with defined diameters were generated in a reproducible manner through the use of an axisymmetric flow focussing device, constructed from off-the-shelf parts and fittings. These SF/G microcarriers supported adhesion of rat mesenchymal stem cells with high degrees of efficiency under dynamic culture conditions and, after culturing in osteogenic differentiation medium, cells were shown to have characteristics typical of osteoblasts. This work illustrates that microcarriers composed of SF/G blends are promising building blocks for osteogenic tissue engineering.Microcarrier cell scaffolds have potential as injectable cell delivery vehicles or as building blocks for tissue engineering. The use of small cell carriers allows for a ‘bottom up’ approach to tissue assembly when moulding microparticles into larger structures, which can facilitate the introduction of hierarchy by layering different matrices and cell types, while evenly distributing cells through the structure. In this work, silk fibroin (SF), purified from  •Silk fibroin/gelatin blends were examined as substrates for mesenchymal stem cell growth.•The presence of gelatin significantly improved cell response.•Homogeneous silk fibroin/gelatin microcarriers were generated by flow focussing.•Microcarriers supported mesenchymal stem cell culture.•Osteogenic differentiation was comparable to that on commercial microcarriers. This has distinct disadvantages; it is often difficult to ensure even cell distribution, and central or core scaffold regions can remain underpopulated. Encapsulating cells within hydrogels is a possible means of overcoming cell distribution issues, but hydrogels have their own shortcomings, such as poor mechanical properties . More reBone tissue is a promising target for the application of microcarriers, either assembled into a construct to treat a sizeable defect, or as injectable cell delivery vehicles to stimulate repair . MicrocaWhile a wide range of silk-based scaffolds, such as freeze dried sponges , nanofib22.1http://www.homecrafts.co.uk/). Foetal bovine serum (FBS) was purchased from Thermo-Fisher. Antibodies for fluorescence-activated cell sorting were obtained from Miltenyi Biotec Ltd., R&D Systems and BD Biosciences as described in Silk cocoons were purchased from Homecrafts Direct  and dialysed against deionized water using SnakeSkin™ dialysis tubing  until the conductivity of the dialysate did not increase (2–3 days). The SF solution was then either freeze dried (Thermo Savant MicroModulyo) or known volumes were oven-dried overnight to determine the concentration, and the solution stored at 4 °C until required.SF was extracted from escribed . Briefly2.35 and 106 cells per sample. Cells were then pelleted by centrifugation  and washed in cold FACS buffer consisting of PBS with 1% v/v FBS before 30 min incubation on ice. Cells were again pelleted and re-suspended in 50 μL of FACS buffer. The antibodies and isotype controls were added to each sample as appropriate, in the dilutions listed in rMSCs were extracted from the bone marrow of juvenile Wistar rats as described by Zhang and Chan . Cells wl-glutamine, 100 U/mL penicillin and 100 μg/mL streptomycin. Cells were maintained at 37 °C, in a humidified atmosphere containing 5% CO2 and used up to passage 8, after which they lose their capacity to proliferate and differentiate [The population of cells positively expressing CD90.1 and CD54, and negative for CD45, was cultured in basal medium consisting of αMEM supplemented with 10% foetal calf serum, 2 mM rentiate .2.4w/v and added to separate wells of multiwell plates at a volume sufficient to coat the base of the well (105 μL/cm2). The solvent was evaporated to leave thin protein films, which were crosslinked by treatment with 50 mM 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) in methanol for 24 h at 4 °C, which also ensured the transition of SF to the insoluble β–sheet conformation [2O, dried in a culture hood overnight, and sterilized by 30 min exposure to UV light . Plates were either seeded with cells immediately or stored at 4 °C until use.Silk fibroin (SF), gelatin (G) and SF/G blends  were dissolved in hexafluoroisopropanol (HFIP) at a total protein concentration of 2% ormation . Wells w2.54 per well and, at specific time points, subsequently incubated with 0.15 mg/mL resazurin solution at 20% v/v of the total culture volume. After 2 h incubation at 37 °C, the fluorescence of the medium was measured at 560/590 nm (excitation/emission) using a BMG Labtech FLUOstar Omega, and cell culture continued in fresh medium.Relative cell metabolism was used as a measure of cell proliferation and was determined by quantifying the reduction of resazurin. To measure cell metabolism by reduction of resazurin to resorufin, rMSCs were seeded in 24 well plates at 2.5 × 104 per well and grown to confluence in basal medium before switching to osteogenic differentiation medium (ODM), which consisted of basal medium supplemented with 0.1 μM dexamethasone, 0.2 mM ascorbic acid 2-phosphate and 10 mM β-glycerophosphate. Levels of osteopontin (OPN) in cell culture supernatants were subsequently quantified using mouse/rat Osteopontin Quantikine ELISA Kit (R&D Systems) according to the manufacturer's instructions. Prior to this, cell culture medium was completely replaced on day 10 after switching to ODM and supernatants collected on day 14 for OPN analysis. Data were normalized to the number of cells per well, quantified by fluorescent detection of Hoechst-stained cell lysate [2O was then added to each well before sonicating for 15 min (VWR Ultrasonic Cleaner USC300TH) and then re-freezing. Samples were again thawed at 37 °C, and the resulting supernatants added to an equal volume of 20 μg/mL Hoechst 33342 in TNE buffer . A standard curve was constructed using samples with known cell numbers. Fluorescence was read at 350/460 nm (BMG Labtech FLUOstar Omega).To promote osteogenic differentiation, rMSCs were seeded in 24 well plates at 3 × 10l lysate . Briefly2.6via tubing-to-cone and cone-to-Luer fittings . The two input feeds were controlled by syringe pumps (Harvard Apparatus Pump 11 Plus and Cole Parmer single syringe infusion pump), and consisted of two immiscible fluids, an outer continuous oil phase and an inner aqueous phase.The flow focussing device was based on a design by Terray & Hart  and asse2.72O at 60 °C, and SF solution was diluted to the same concentration. Prior to the formation of microcarriers, these solutions were mixed to give blends with SF/G ratios of 100:0, 75:25, 50:50 and 25:75, and then maintained at 60 °C until use. To generate microcarriers, SF or SF/G solution was used as the inner phase in the flow-focussing device, with the inner flow rate (Qinner) set at 0.36 mL/h. The outer phase consisted of oleic acid, methanol and Span 80, mixed in a volume ratio of 73:25:2 [outer) set at 7.2 mL/h. The output of the device was collected into a mixture of the outer phase solution diluted 1:1 with methanol and kept on ice. Following filtration, SF microcarriers were washed with PBS, autoclaved in PBS at 121 °C for 15 min and then stored at 4 °C until use. Gelatin-containing microcarriers were cross-linked for 24 h with 50 mM EDC in methanol at 4 °C and then treated in the same way as SF microcarriers.Type A porcine gelatin was dissolved to a concentration of 50 mg/mL in dH 73:25:2 , with th2.8http://imagej.nih.gov/ij) [Images of the microcarriers were acquired using a Leica DMI4000B microscope and their diameters then determined using the Particle Analysis function of ImageJ  . At leas2.9w/v solutions of SF, the three SF/G blends and gelatin were added to wells of a 12 well plate. Plates were cooled to 4 °C to gel the gelatin-containing discs, before being frozen at −20 °C. Methanol (1 mL) was added to each well and the discs incubated overnight at 4 °C. After removal of the methanol, SF discs were then thoroughly washed three times with PBS, while SF/G and gelatin discs were further crosslinked by EDC treatment as described in To produce discs for compression testing, 1.5 mL aliquots of 5% 2.105 cells/mL with microcarriers suspended at 2 × 103 particles/mL in basal medium. The plate was incubated on a plate rocker under standard cell culture conditions and, after 24 h, the suspension was filtered through a 70 μm nylon mesh filter to remove unattached cells, which were counted to establish the proportion of cells remaining adhered to the microcarriers. After initial seeding, cell-laden microcarriers were cultured statically in basal medium or transferred into ODM, and cultured for 14 or 28 days.Cells were seeded onto microcarriers in 24 well plates coated with a non-adhesive layer of 1% agarose in DMEM. In a total volume of 500 μL, cells were seeded at a concentration of 3.75 × 102.11w/v paraformaldehyde (maximum of 60 s) and then washed in PBS with 0.05% v/v Tween 20. BCIP/NBT solution , was then added to the cells for 10 min and the cells washed once more with PBS/0.05% v/v Tween 20. Generation of a dark purple precipitate, indicating the presence of ALP, was assessed using a stereomicroscope (Olympus SZ61TR).To assess rMSC viability on SF/G microcarriers, cells were seeded as described above and, after 96 h in culture, stained simultaneously with calcein-AM and ethidium homodimer-1 (both 2 μM in PBS) to identify living and dead cells. Cells were washed with PBS, incubated in the staining solution in the dark for 20 min at 37 °C and then examined using a Zeiss LSM510 confocal microscope. To determine osteogenic differentiation of the cells, secretion of OPN was measured as described in 2.12p < 0.05 was considered statistically significant.Statistical analysis was performed using one-way analysis of variance (ANOVA) with Tukey's honest significant difference post-hoc test using R software . A value3In order to determine the suitability of SF/G blends for use as a substrate for MSC proliferation and osteogenic differentiation, cell-material interactions were initially assessed in 2D by seeding rMSCs on biomaterial films, which were cast within multiwell plates. Suitable blends were then taken forwards to evaluate their ability to form microcarriers which supported MSC adhesion and osteogenesis.3.1Bombyx mori SF [The ability of films of SF, SF/G and gelatin to support rMSC proliferation was assessed over 7 days using the resazurin reduction assay which, unlike a number of other metabolic assays, enables the same population of cells to be examined across multiple time points . rMSCs p mori SF . Many st mori SF ,46,47. I mori SF . An exce mori SF . Thus, i3.2Deposition of calcified ECM is a commonly used measure to determine osteogenic differentiation of MSCs. However, it was found that mineralization stains, such as Alizarin Red  and von Cells grown on all three SF/G blends and the TCP control secreted very low quantities of OPN, between 2.08 and 3.08 fg/cell, when cultured in basal medium, with no significant differences observed between the different substrates. However, when cultured in ODM, there was a significant increase in OPN secretion on all surfaces, ranging from 17.68 to 22.92 fg/cell, indicating osteogenic differentiation of the rMSCs on these blended materials. While there was an apparent trend for increasing OPN secretion with increasing SF content in the films, differences in OPN levels between substrates were not statistically significant. It is extremely difficult to compare these relative quantities to similar studies in the literature as data is often reported at the mRNA level and/or as a fold-increase or percentage relative to a control rather than absolute quantity of protein secreted per cell. Nonetheless, it is clear that SF/G blends are capable of supporting the proliferation and osteogenic commitment of rMSCs.3.3Following the positive 2D results, we investigated microcarriers for the 3D culture and osteogenic differentiation of MSCs. Previous studies have demonstrated the formation of SF microcarriers from simple homogenized emulsions, but this requires volatile organic solvents and results in microcarriers with a wide size distribution . At the outer/Qinner; inner of 0.36 mL/h was the optimum for the consistent generation and collection of microcarriers, with Qouter/Qinner of 20 consistently yielding microcarriers with diameters in the desired range of 300–400 μm.Using an outer phase of oleic acid/methanol/Span 80 (73:25:2) and an inner phase of SF/G solution, microcarriers were produced successfully from SF/G 75:25, SF/G 50:50, and SF/G 25:75. Methanol was employed in the outer phase to induce a conformational change in silk fibroin, resulting in the formation of insoluble crystalline β-sheets which act as physical crosslinks in the protein structure . This ef3.4The morphology of the microcarriers was assessed by visible light and scanning electron microscopy. Microcarriers of all three SF/G blends shared a very similar porous surface structure, with representative images of SF/G 75:25 microcarriers shown in Microcarrier diameters were measured using ImageJ analysis of visible light microscopy images, and these results are summarized in vice versa.To examine the mechanical properties of these blends, the Young's modulus of SF/G discs was measured by compression testing and compared to SF and gelatin alone . Althoug3.5Cell adhesion to the microcarriers, shown in 3.6For applications in bone tissue engineering, it is important that these microcarriers are able to support not only cell adhesion, but growth, viability and osteogenesis. Viability of rMSCs was confirmed by live/dead fluorescent staining and confocal microscopy of cell-seeded microcarriers. The image in 4The results obtained in this study support the use of SF/G microcarriers as scaffolds for cell culture and their development towards bone repair applications. rMSC compatibility and proliferation on silk fibroin and gelatin materials was first confirmed in a two-dimensional format before moving to microcarrier culture. Although silk fibroin alone was shown to have poor cell adhesion, blending silk with gelatin improved the cell adhesion, proliferation and elastic modulus. The SF/G microcarriers were also shown to support cell adhesion and viability as well as osteogenic differentiation of rMSCs. The poor compatibility of the unblended SF and gelatin films highlights the importance of scaffold design for cell response. These microcarriers have the potential to be used as an injectable delivery system for therapeutic cells or a filler material which could stimulate the proliferation and differentiation of resident MSCs for the repair of small bone defects, where load-bearing ability is not a prerequisite. An additional advantage of carrier-based systems is the capacity to scale up the production of therapeutic cells prior to delivery using a stirred, fluidized or rotating bioreactor. Alternatively, the use of the microcarriers as building blocks could allow the development of a macroscopic tissue construct, by moulding a number of cell-laden microcarriers into a fixed architecture for the generation of a number of engineered tissues.