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A new method is presented for quantifying proteomic and metabolomic profile data by liquid chromatography-mass spectrometry (LC-MS) with electrospray ionization. This biotechnology provides differential expression measurements and enables the discovery of biological markers (biomarkers). Work presented here uses human serum but is applicable to any fluid or tissue. The approach relies on linearity of signal versus molecular concentration and reproducibility of sample processing. There is no use of isotopic labeling or chemically similar standard materials. Linear standard curves are reported for a variety of compounds introduced into human serum. As a measure of analytical reproducibility for proteome and metabolome sampling, median coefficients of variation of 25.7 and 23.8%, respectively, were determined for ~3400 molecular ions (not counting their numerous isotopes) from 25 independently processed human serum samples, corresponding to a total of 85 000 individual molecular ion measurements.

Studies have shown that some peptides and small molecules can induce non IgE-mediated anaphylactoid reactions through mast cell activation. Upon activation, mast cells degranulate and release vasoactive and proinflammatory mediators, from cytoplasmic granules into the extracellular environment which can induce a cascade of severe adverse reactions. This study describes a lead optimization strategy to select NaV1.7 inhibitor peptides that minimize acute mast cell degranulation (MCD) toxicities. Various in vitro, in vivo, and PKPD models were used to screen candidates and guide peptide chemical modifications to mitigate this risk. Anesthetized rats dosed with peptides demonstrated treatment-related decreases in blood pressure and increases in plasma histamine concentrations which were reversible with a mast cell stabilizer, supporting the MCD mechanism. In vitro testing in rat mast cells with NaV1.7 peptides demonstrated a concentration-dependent increase in histamine. Pharmacodynamic modeling facilitated establishing an in vitro to in vivo correlation for histamine as a biomarker for blood pressure decline via the MCD mechanism. These models enabled assessment of structure-activity relationship (SAR) to identify substructures that contribute to peptide-mediated MCD. Peptides with hydrophobic and cationic characteristics were determined to have an elevated risk for MCD, which could be reduced or avoided by incorporating anionic residues into the protoxin II scaffold. Our analyses support that in vitro MCD assessment in combination with PKPD modeling can guide SAR to improve peptide lead optimization and ensure an acceptable early in vivo tolerability profile with reduced resources, cycle time, and animal use. [ABSTRACT FROM AUTHOR]

Amyloid fibrils are associated with a variety of neurodegenerative maladies including Alzheimer's disease and the prion diseases. The structures of amyloid fibrils are composed of [beta]-strands oriented orthogonal to the fibril axis ('cross [beta]' structure). We previously reported the design and characterization of a combinatorial library of de novo [beta]-sheet proteins that self-assemble into fibrillar structures resembling amyloid. The libraries were designed by using a 'binary code' strategy, in which the locations of polar and nonpolar residues are specified explicitly, but the identities of these residues are not specified and are varied combinatorially. The initial libraries were designed to encode proteins containing amphiphilic [beta]-strands separated by reverse turns. Each [beta]-strand was designed to be seven residues long, with polar (o) and nonpolar (*) amino acids arranged with an alternating periodicity (o*o*o*o*). The initial design specified the identical polar/nonpolar pattern for all of the [beta]-strands; no strand was explicitly designated to form the edges of the resulting [beta]-sheets. With all [beta]-strands preferring to occupy interior (as opposed to edge) locations, intermolecular oligomerization was favored, and the proteins assembled into amyloid-like fibrils. To assess whether explicit design of edge-favoring strands might tip the balance in favor of monomeric [beta]-sheet proteins, we have now redesigned the first and/or last [beta]-strands of several sequences from the original library. In the redesigned [beta]-strands, the binary pattern is changed from o*o*o*o to o*o*oKo*o (K denotes lysine). The presence of a lysine on the nonpolar face of a [beta]-strand should disfavor fibrillar structures because such structures would bury an uncompensated charge. The nonpolar [right arrow] lysine mutations, therefore, would be expected to favor monomeric structures in which the o*oKo*o sequences form edge strands with the charged lysine side chain accessible to solvent. To test this hypothesis, we constructed several second generation sequences in which the central nonpolar residue of either the N-terminal [beta]-strand or the C-terminal [beta]-strand (or both) is changed to lysine. Characterization of the redesigned proteins shows that they form monomeric [beta]-sheet proteins.

Methods for detecting mycotoxins are very important because of the great health hazards of mycotoxins. However, there is a high background and low signal-to-noise ratio in real-time sensing, and therefore it is difficult to meet the fast, accurate, and convenient requirements for control of food quality. Here we constructed a quantitative fluorescence image analysis based on multicolor upconversion nanocrystal (UCN)-encoded microspheres for detection of ochratoxin A and zearalenone. The background-free encoding image signal of UCN-doped microspheres was captured by fluorescence microscopy under near-infrared excitation, whereas the detection image signal of phycoerythrin-labeled secondary antibodies conjugated to the microspheres was captured under blue light excitation. We custom-wrote an algorithm to analyze the two images for the same sample in 10 s, and only the gray value in the red channel of the secondary probe confirmed the quantity. The results showed that this novel detection platform performed feasible and reliable fluorescence image measurements by this method. Additionally, the limit of detection of was 0.34721 ng/mL for ochratoxin A and 0.41162 ng/mL for zearalenone. We envision that this UCN encoding strategy will be usefully applied for fast, accurate, and convenient testing of multiple food contaminants to ensure the safety of the food. [ABSTRACT FROM AUTHOR]

A variety of naturally occurring biomaterials owe their unusual structural and mechanical properties to layers of [Beta]-sheet proteins laminated between layers of inorganic mineral. To explore the possibility of fabricating novel two-dimensional protein layers, we studied the self-assembly properties of de novo proteins from a designed combinatorial library. Each protein in the library has a distinct 63 amino acid sequence, yet they all share an identical binary pattern of polar and nonpolar residues, which was designed to favor the formation of six-stranded amphiphilic [Beta]-sheets. Characterization of proteins isolated from the library demonstrates that (iii) they self assemble into monolayers at an air/water interface; (ii) the monolayers are dominated by [Beta]-sheet secondary structure, as shown by both circular dichroism and infrared spectroscopies; and (iii) the measured areas (500- 600 [[Angstrom].sup.2]) of individual protein molecules in the monolayers match those expected for proteins folded into amphiphilic [Beta]-sheets. The finding that similar structures are formed by distinctly different protein sequences suggests that assembly into [Beta]-sheet monolayers can be encoded by binary patterning of polar and nonpolar amino acids. Moreover, because the designed binary pattern is compatible with a wide variety of different sequences, it may be possible to fabricate [Beta]-sheet monolayers by using combinations of side chains that are explicitly designed to favor particular applications of novel biomaterials.

Amyloid deposits are associated with several neurodegenerative diseases, including Alzheimer's disease and the prion diseases. The amyioid fibrils isolated from these different diseases share similar structural features. However, the protein sequences that assemble into these fibrils differ substantially from one disease to another. To probe the relationship between amino acid sequence and the propensity to form amyioid, we studied a combinatorial library of sequences designed de novo. All sequences in the library were designed to share an identical pattern of alternating polar and nonpolar residues, but the precise identities of these side chains were not constrained and were varied combinatorially. The resulting proteins self-assemble into large oligomers visible by electron microscopy as amyloid-like fibrils. Like natural amyloid, the de novo fibrils are composed of [Beta]-sheet secondary structure and bind the diagnostic dye, Congo red. Thus, binary patterning of polar and nonpolar residues arranged in alternating periodicity can direct protein sequences to form fibrils resembling amyloid. The model amyloid fibrils assemble and disassemble reversibly, providing a tractable system for both basic studies into the mechanisms of fibril assembly and the development of molecular therapies that interfere with this assembly.

Objective: Antihyperglycemic agents, such as empagliflozin, stimulate proximal tubular natriuresis and improve cardiovascular and renal outcomes in patients with type 2 diabetes. Because dipeptidyl peptidase 4 (DPP-4) inhibitors are used in combination with sodium-glucose cotransporter 2 (SGLT2) inhibitors, we examined whether and how sitagliptin modulates fractional sodium excretion and renal and systemic hemodynamic function.Research Design and Methods: We studied 32 patients with type 2 diabetes in a prospective, double-blind, randomized, placebo-controlled trial. Measurements of renal tubular function and renal and systemic hemodynamics were obtained at baseline, then hourly after one dose of sitagliptin or placebo, and repeated at 1 month. Fractional excretion of sodium and lithium and renal hemodynamic function were measured during clamped euglycemia. Systemic hemodynamics were measured using noninvasive cardiac output monitoring, and plasma levels of intact versus cleaved stromal cell-derived factor (SDF)-1α were quantified using immunoaffinity and tandem mass spectrometry.Results: Sitagliptin did not change fractional lithium excretion but significantly increased total fractional sodium excretion (1.32 ± 0.5 to 1.80 ± 0.01% vs. 2.15 ± 0.6 vs. 2.02 ± 1.0%, P = 0.012) compared with placebo after 1 month of treatment. Moreover, sitagliptin robustly increased intact plasma SDF-1α1-67 and decreased truncated plasma SDF-1α3-67. Renal hemodynamic function, systemic blood pressure, cardiac output, stroke volume, and total peripheral resistance were not adversely affected by sitagliptin.Conclusions: DPP-4 inhibition promotes a distal tubular natriuresis in conjunction with increased levels of intact SDF-1α1-67. Because of the distal location of the natriuretic effect, DPP-4 inhibition does not affect tubuloglomerular feedback or impair renal hemodynamic function, findings relevant to using DPP-4 inhibitors for treating type 2 diabetes. [ABSTRACT FROM AUTHOR]

Abstract: Dynamic voltage scaling (DVS) has been a very effective technique for processor energy reduction. It adjusts processor voltage and frequency level during runtime. In this article, we propose a general and flexible processor voltage scaling algorithm for real-time multitasking systems. Our approach focuses on exploiting dynamic slack that is created when a task finishes earlier than its estimated worst-case execution time (WCET). Our algorithm is efficient enough to execute at runtime and can be configured flexibly to make tradeoffs between running time and energy savings. By rescheduling tasks effectively, we can achieve almost as much energy savings as if there is no arrival time constraints. Furthermore, our approach can effectively incorporate both leakage power consumption as well as variable scaling overhead. Also, it is relatively independent of task characteristics and scheduling policy. Experimental results show that our technique can achieve significant energy savings at runtime over statically generated schedules and up to 12% more savings compared to the state-of-art techniques. [Copyright &y& Elsevier]

The ongoing scaling of semiconductor technology is causing severe increase of on-chip power density and temperature in microprocessors. This urgently requires both power and thermal management during system design. In this paper, we propose a model checking-based technique using extended timed automata to solve the processor frequency assignment problem in a temperature and energy-constrained multitasking system. We also develop a polynomial time-approximation algorithm to address the state-space explosion problem caused by symbolic model checker. Our approximation scheme is guaranteed to not generate any false-positive answer, while it may return false-negative answer in rare cases. Our method is universally applicable since it is independent of any system and task characteristics. Experimental results demonstrate the usefulness of our approach. [ABSTRACT FROM AUTHOR]

In recent years, efficient dynamic reconfiguration techniques have been widely employed for system optimization. Dynamic cache reconfiguration is a promising approach for reducing energy consumption as well as for improving overall system performance. It is a major challenge to introduce cache reconfiguration into real-time multitasking systems, since dynamic analysis may adversely affect tasks with timing constraints. This article presents a novel approach for implementing cache reconfiguration in soft real-time systems by efficiently leveraging static analysis during runtime to minimize energy while maintaining the same service level. To the best of our knowledge, this is the first attempt to integrate dynamic cache reconfiguration in real-time scheduling techniques. Our experimental results using a wide variety of applications have demonstrated that our approach can significantly reduce the cache energy consumption in soft real-time systems (up to 74%). [ABSTRACT FROM AUTHOR]

System optimization techniques are widely used to improve energy efficiency as well as overall performance. Dynamic voltage scaling (DVS) is well studied and known to be successful in reducing processor energy consumption. Due to the increasing significance of the memory subsystem's energy consumption, dynamic cache reconfiguration (DCR) techniques are recently proposed at the aim of improving cache subsystem's energy efficiency. As the manufacturing technology scales into the order of nanometers, leakage current, which leads to static power consumption, becomes a significant contributor in the overall power dissipation. In this paper, we consider various system components and study their impact on system-wide energy consumption under different processor voltage levels as well as cache configurations. Based on the observation, we efficiently integrate DVS and DCR techniques together to make decisions judiciously so that the total energy consumption is minimized. Our studies show that considering only DVS or DCR and ignoring the impact from other system components may lead to incorrect conclusions in overall energy savings. Experimental results demonstrate that our approach outperforms existing leakage-aware DVS techniques by 47.6% and leakage-oblivious DVS + DCR technique by up to 23.5%. [ABSTRACT FROM AUTHOR]

Abstract: System optimization techniques based on dynamic reconfiguration are widely adopted for energy conservation. While dynamic voltage scaling (DVS) techniques have been extensively studied for processor energy conservation, dynamic cache reconfiguration (DCR) for reducing cache energy consumption in multitasking systems is still in its infancy. In this paper, we propose a general and flexible algorithm for energy optimization based on dynamic reconfiguration in multitasking systems. Our algorithm is flexibly parameterized and can be used to provide tradeoffs between running time and solution quality. Furthermore, it can easily incorporate variable reconfiguration overhead. Experimental results show that our technique can generate near-optimal solutions with significantly low running time and memory requirements. [Copyright &y& Elsevier]

Lipids are structurally diverse molecules that play a pivotal role in a plethora of biological processes. However, deciphering the biological roles of the specific lipids is challenging due to the existence of numerous isomers. This high chemical complexity of the lipidome is one of the major challenges in lipidomics research, as the traditional liquid chromatography–mass spectrometry (LC-MS) based approaches are often not powerful enough to resolve these isomeric and isobaric nuances within complex samples. Thus, lipids are uniquely suited to the benefits provided by multidimensional liquid chromatography–ion mobility–mass spectrometry (LC-IM-MS) analysis. However, many forms of lipid isomerism, including double-bond positional isomers and regioisomers, are structurally similar such that their collision cross section (CCS) differences are unresolvable via conventional IM approaches. Here we evaluate the performance of a high resolution ion mobility (HRIM) system based on structures for lossless ion manipulation (SLIM) technology interfaced to a high resolution quadrupole time-of-flight (QTOF) analyzer to address the noted lipidomic isomerism challenge. SLIM implements the traveling wave ion mobility technique along an ∼13 m ion path, providing longer path lengths to enable improved separation of isomeric features. We demonstrate the power of HRIM-MS to dissect isomeric PC standards differing only in double bond (DB) and stereospecific number (SN) positions. The partial separation of protonated DB isomers is significantly enhanced when they are analyzed as metal adducts. For sodium adducts, we achieve close to baseline separation of three different PC 18:1/18:1 isomers with different cis-double bond locations. Similarly, PC 18:1/18:1 (cis-9) can be resolved from the corresponding PC 18:1/18:1 (trans-9) form. The separation capacity is further enhanced when using silver ion doping, enabling the baseline separation of regioisomers that cannot be resolved when measured as sodium adducts. The sensitivity and reproducibility of the approach were assessed, and the performance for more complex mixtures was benchmarked by identifying PC isomers in total brain and liver lipid extracts. [ABSTRACT FROM AUTHOR]

UV resonance Raman bands of Cu-bound and protonated histidine residues have been detected in 2H2O solutions of poplar plastocyanin. For the Cu(II) protein, slow NH–2H exchange of the His37 ligand was monitored via the growth of bands at 1389 and 1344 cm−1 when Pcy was exchanged into 2H2O, or via their diminution when the protein was exchanged back into H2O; the rate constant is 7×10−4/s at pH (p2H) 7.4 at room temperature. The slow exchange is attributed to imidazole H-bonding to a backbone carbonyl. Nearby bands at 1397 and 1354 cm−1, appear and disappear within the mixing time, and are assigned to the solvent-exposed His87 ligand. The ∼10 cm−1 differences between His37 and His87 are attributed to the effect of H-bonding on the imidazole ring modes. The UVRR spectra of the Cu(I) protein in 2H2O reveal a 1408 cm−1 band, characteristic of NH–2H-exchanged histidinium, which grows in as the p2H is lowered. Its intensity follows a titration curve with pKa=4.6. This protonation is assigned to the His87 residue, whose bond to the Cu(I) is known from crystallography to be broken at low pH. As the 1408 cm−1 band grows, a band at 1345 cm−1 diminishes, while another, at 1337 cm−1 stays constant. These are assigned to modes of bound His87 and His37, respectively, shifted down 7–9 cm−1 from their Cu(II) positions. [ABSTRACT FROM AUTHOR]

Abstract Ginger (Zingiber officinale Roscoe), one of the most economically valuable plants in the Zingiberaceae family, is widely used as a spice and flavoring agent for beverages, bakery, confectionary, and pharmaceutics. Bacterial wilt disease, caused by Ralstonia solanacearum , is one of the most detrimental production constraints in ginger cultivation. Field cultivation experiments indicated that soil moisture affects the incidence of bacterial wilt disease. However, the relationship between soil moisture and bacterial wilt incidence as well as the mechanism that underlie this infection remain unclear. This study confirms that high soil moisture elevates the susceptibility to R. solanacearum infection; transcriptome sequencing was performed to elucidate the underlying mechanisms. Differential expression indicates that a small number of genes is involved in both the response to high soil moisture as well as post successful R. solanacearum infection; furthermore, a large number of genes is involved in the defense of the infection. In response to high soil moisture, higher ABA contents, and higher expression levels of ABF4 may be related to higher tiller density in ginger. More importantly, WAK16 and WAK3-2 may be determinative genes that weaken the resistance to R. solanacearum in ginger under high soil moisture. The down-regulated expression levels of PRX , CPY , and XET genes indicate that in response to successful R. solanacearum infection, the normal cell wall metabolism may be disturbed and the hypersensitive response may be inhibited. In summary, our study deepens our understanding of the molecular mechanisms of the soil moisture dependent wilt susceptibility of ginger. Graphical abstract Image 1 Highlights • High soil moisture elevates ginger susceptibility to R. solanacearum. • Comparative transcriptome analysis was performed under low and high soil moistures • High ABA and ABF4 related to high tiller density of ginger under high soil moisture. • WAK16 and WAK3-2 may weaken the resistance of ginger to R. solanacearum. • Low PRX, CPY, and XET showed cell wall metabolism was disturbed after infection. [ABSTRACT FROM AUTHOR]