On converse Lyapunov theorems for fluid network models

We consider the class of closed generic fluid network (GFN) models, which provides an abstract framework containing a wide variety of fluid networks. Within this framework a Lyapunov method for stability of GFN models was proposed by Ye and Chen. They proved that stability of a GFN model is equivalent to the existence of a functional on the set of paths that is decaying along paths. This result falls short of a converse Lyapunov theorem in that no state-dependent Lyapunov function is constructed. In this paper we construct state-dependent Lyapunov functions in contrast to path-wise functionals. We first show by counterexamples that closed GFN models do not provide sufficient information that allow for a converse Lyapunov theorem. To resolve this problem we introduce the class of strict GFN models by forcing closed GFN models to satisfy a concatenation and a semicontinuity condition. For the class of strict GFN models we define a state-dependent Lyapunov function and show that a converse Lyapunov theorem holds. Finally, it is shown that common fluid network models, like general work-conserving and priority fluid network models as well as certain linear Skorokhod problems define strict GFN models.     

IPr3Si3Cl5+: A Highly Reactive Cation with Silanide Character

The reaction of a metastable SiCl₂ solution with the sterically less‐demanding carbene N,N‐diisopropylimidazo‐2‐ylidene (IPr) yields the salt [(IPr₃Si₃Cl₅)⁺]Cl^? ( 1 ‐Cl), containing a silyl cation with a Si₃ backbone. Salt 1 is highly reactive, but it can be used as a reagent in deuterated dichloromethane, whereby dehalogenation with Me₃SiOTf (OTf=O₃SCF₃) gives the dicationic silyl halide [(IPr₃Si₃Cl₄)]²⁺ 2 . Quantum chemical calculations show that the HOMO is localized at the negatively charged central silicon atom of 1 and 2 , and thus although both compounds are cations they are better described as silanides, which was also corroborated by NMR investigations.     

U6 is unsuitable for normalization of serum miRNA levels in patients with sepsis or liver fibrosis

MicroRNA (miRNA) levels in serum have recently emerged as potential novel biomarkers for various diseases. miRNAs are routinely measured by standard quantitative real-time PCR (qPCR); however, the high sensitivity of qPCR demands appropriate normalization to correct for nonbiological variation. Presently, RNU6B (U6) is used for data normalization of circulating miRNAs in many studies. However, it was suggested that serum levels of U6 themselves might differ between individuals. Therefore, no consensus has been reached on the best normalization strategy in ‘circulating miRNA''. We analyzed U6 levels as well as levels of spiked-in SV40-RNA in sera of 44 healthy volunteers, 203 intensive care unit patients and 64 patients with liver fibrosis. Levels of U6 demonstrated a high variability in sera of healthy donors, patients with critical illness and liver fibrosis. This high variability could also be confirmed in sera of mice after the cecal ligation and puncture procedure. Most importantly, levels of circulating U6 were significantly upregulated in sera of patients with critical illness and sepsis compared with controls and correlated with established markers of inflammation. In patients with liver fibrosis, U6 levels were significantly downregulated. In contrast, levels of spiked-in SV40 displayed a significantly higher stability both in human cohorts (healthy, critical illness, liver fibrosis) and in mice. Thus, we conclude that U6 levels in the serum are dysregulated in a disease-specific manner. Therefore, U6 should not be used for data normalization of circulating miRNAs in inflammatory diseases and previous studies using this approach should be interpreted with caution. Further studies are warranted to identify specific regulatory processes of U6 levels in sepsis and liver fibrosis.     

Studies on drug metabolism by fungi colonizing decomposing human cadavers. Part I: DNA sequence-based identification of fungi isolated from postmortem material

Cadavers can be colonized by a wide variety of bacteria and fungi. Some of these microbes could change the concentration or the metabolic pattern of drugs present in postmortem samples. The purpose of this study was to identify fungi from human postmortem material and to further assess their potential role in the metabolism of drugs. Aliquots of 252 postmortem samples (heart blood, liver, kidney, and lung) taken from 105 moderately to severely decomposed bodies were streaked on Sabouraud agar for isolation of fungal species. One part of the samples was worked up immediately after autopsy (group I). The second part had previously been stored at ?20 °C for at least 1 year (group II). Identification of the isolates was achieved morphologically by microscopy and molecularly by polymerase chain reaction amplification and sequencing of markers allowing species identification of the respective genera. Depending on the genus, different gene fragments were used: calmodulin for Aspergillus, β-tubulin for Penicillium, translation elongation factor 1α for Fusarium, and the internal transcribed spacer region of the ribosomal DNA for all remaining genera. A total of 156 fungal strains were isolated from 62 % of the postmortem materials. By using these primers, 98 % of the isolates could be identified to the species level. The most common genera were Candida (60.0 %—six species), Penicillium (10.3 %—two species), Rhodotorula (7.1 %—one species), Mucor (6.4 %—four species), Aspergillus (3.2 %—four species), Trichosporon (3.2 %—one species), and Geotrichum (3.2 %—one species). Group I samples contained 53 % more fungal species than stored samples suggesting some fungi did not survive the freezing process. The isolated fungi might be characteristic for decomposed bodies. The proposed methodology proved to be appropriate for the identification of fungi in this type of material.     

Characterisation and quantification of liposome-type nanoparticles in a beverage matrix using hydrodynamic chromatography and MALDI–TOF mass spectrometry

This paper describes the characterisation of liposome-type nanoparticles (NPs) dispersed in a beverage matrix. Characterisation is based on a two-step procedure: first, liposomes are separated on the basis of size in the nanometre range by use of hydrodynamic chromatography (HDC); second, chemical characterisation is performed by use of MALDI–TOF mass spectrometry (MS). Characterisation of three types of Coatsome liposome, a commercially available type of empty liposome, was investigated. All three liposome types, Coatsome A?=?anionic, N?=?neutral, and C?=?cationic, gave single peaks in HDC, reflecting diameters of 153, 187, and 205 nm, respectively. Subsequent MALDI–TOF MS in positive mode furnished major signals at m/z?=?734.5 ([M?+?H]⁺ adduct) and m/z?=?756.6 ([M?+?Na]⁺ adduct) of l-(α)-dipalmitoylphosphatidylcholine (DPPC) monomer and dimeric adducts at m/z?=?1468.1 and m/z?=?1490.1, respectively. MALDI–TOF MS in negative mode gave a signal at m/z?=?721.3 ([M???H]^? adduct) of l-(α)-dipalmitoylphosphatidylglycerol (DPPG), except for Coatsome C which lacks this phospholipid. After HDC separation of Coatsome A NPs the major DPPC and DPPG signals can be detected in the expected fractions by use of MALDI–TOF MS in positive and negative modes, respectively. Validation of the analytical strategy revealed linearity (R ²?>?0.99), repeatability (relative standard deviation <10 %), and reproducibility (relative standard deviation between days <10 %) were good, recovery was 61?±?5 %, and the limit of quantification was 1 mg?mL^?1 in this matrix. With 4 mg Coatsome A mL^?1 20 out of 20 samples furnished the 734.5 and 756.6 signals typical of DPPC in MALDI–TOF MS characterisation.