Short-term impact of vitamin K2 supplementation on biochemical parameters and lipoprotein fractions.

This study explored the short-term effects of vitamin K2 (VK2) supplementation on biochemical parameters (vitamin D, vitamin E, vitamin A, alkaline phosphatase, calcium, phosphorus (P), magnesium, metallothionein, triglycerides, cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and lipoprotein fractions (albumin, HDL, very low-density lipoprotein (VLDL), LDL, and chylomicrons). A short-term experiment (24 h, six probands) was performed to track changes in VK2 levels after a single-dose intake (360 µg/day). Liquid chromatography-tandem mass spectrometry was used to monitor vitamin K levels (menaquinone-4 (MK-4), menaquinone-7 (MK-7), and vitamin K1 [VK1]) with a limit of detection of 1.9 pg/mL for VK1 and 3.8 pg/mL for the two forms of VK2. Results showed that MK-7 levels significantly increased within 2-6 h post-administration and then gradually declined. MK-4 levels were initially low, showing a slight increase, whereas VK1 levels rose initially and then decreased. Biochemical analyses indicated no significant changes in sodium, chloride, potassium, calcium, magnesium, albumin, or total protein levels. A transient increase in P was observed, peaking at 12 h before returning to baseline. Agarose gel electrophoresis of lipoprotein fractions revealed distinct chylomicron bands and variations in VLDL and HDL mobility, influenced by dietary lipids and VK2 supplementation. These findings suggest effective absorption and metabolism of MK-7 with potential implications for bone metabolism and cardiovascular health.

Spectrophotometric and chromatographic analysis of creatine:creatinine crystals in urine.

Creatinine is the end product of the catabolism of creatine and creatine phosphate. Creatine phosphate serves as a reservoir of high-energy phosphate, especially in skeletal and cardiac muscle. Besides typical known changes in serum and urinary creatinine concentrations, rare cases associated with changes in serum and urinary creatine levels have been described in the literature in humans. These cases are mostly linked to an excessive intake of creatine ethyl ester or creatine monohydrate, often resulting in increased urine creatinine concentrations. In addition, it is known that at such elevated creatinine concentrations, creatinine crystallisation may occur in the urine. Analysis of crystals and urinary concrements, often of heterogenous chemical composition, may provide diagnostic and therapeutic hints to the benefit of the patient. The aim of the present work was to analyze urine crystals of unclear composition with microscopic and spectroscopic techniques. On routine microscopic analysis of urine, a preliminary suspicion of uric acid or creatinine crystals was expressed. The crystals were of a cuboid shape and showed polarization effects in microscopy. The dried urine sample was whitish-orange in colour, odourless and dissolved well in water. Protein concentration in dry weight (DW) urine was about 0.3 mg/mg. The measured zinc content in the studied sample was approximately 660 µg/g DW sample and copper content was approximately 64 µg/g DW sample. A lead signal of around 10 µg/g DW sample was also observed. UV-Vis analysis showed a maximum creatine peak around 220 nm, compatible with the spectrum of creatinine with a maximum peak of 230 nm. Using HPLC technique, an extreme high ratio of creatine to creatinine of about 38 was measured, which led to the conclusion of the occurrence of rare creatine crystals in urine.

Synovial fluid alpha-defensins in Lyme arthritis-a useful marker.

Lyme arthritis, one of the possible late manifestations of Lyme borreliosis, predominantly affects the supporting joints and in adults most often occurs in the form of monoarthritis of the knee. Early diagnosis is based on clinical findings and serology. PCR detection of Borrelia in synovial fluid has become an integral part of the laboratory testing algorithm. The clinical presentation and inflammatory markers in Lyme arthritis can resemble septic arthritis. Determining the levels of alpha-defensins (human neutrophil peptide (HNP 1-3)) in synovial fluid by liquid chromatography is a highly sensitive method revealing the presence of inflammatory process. Between 2020 and 2022, we examined eleven patients with Lyme arthritis of the knee. We measured levels of HNP 1-3 from synovial fluid by HPLC in patients, and we compared it with the corresponding C-reactive protein (CRP) levels in paired serum samples. In patients diagnosed with Lyme arthritis, HNP 1-3 levels in synovial fluid ranged from 2.5 to 261 mg/L, with a median of 46.5 mg/L. Average serum CRP was 43 mg/L. The results show that elevated HNP 1-3 can be consistent with not only septic arthritis or systemic disease, but also with Lyme arthritis, especially in patients with negative culture and 16S PCR from synovial fluid. Final diagnosis must be verified by examination for anti-Borrelia antibodies from serum and synovial fluid. The aim of this work is to introduce an HPLC method for the determination of alpha-defensins as one of the possible diagnostic markers.

Electrochemical Sensors and Biosensors for Identification of Viruses: A Critical Review.

Due to their life cycle, viruses can disrupt the metabolism of their hosts, causing diseases. If we want to disrupt their life cycle, it is necessary to identify their presence. For this purpose, it is possible to use several molecular-biological and bioanalytical methods. The reference selection was performed based on electronic databases (2020-2023). This review focused on electrochemical methods with high sensitivity and selectivity (53% voltammetry/amperometry, 33% impedance, and 12% other methods) which showed their great potential for detecting various viruses. Moreover, the aforementioned electrochemical methods have considerable potential to be applicable for care-point use as they are portable due to their miniaturizability and fast speed analysis (minutes to hours), and are relatively easy to interpret. A total of 2011 articles were found, of which 86 original papers were subsequently evaluated (the majority of which are focused on human pathogens, whereas articles dealing with plant pathogens are in the minority). Thirty-two species of viruses were included in the evaluation. It was found that most of the examined research studies (77%) used nanotechnological modifications. Other ones performed immunological (52%) or genetic analyses (43%) for virus detection. 5% of the reports used peptides to increase the method's sensitivity. When evaluable, 65% of the research studies had LOD values in the order of ng or nM. The vast majority (79%) of the studies represent proof of concept and possibilities with low application potential and a high need of further research experimental work.

Influence of microbiome species in hard-to-heal wounds on disease severity and treatment duration

ABSTRACT BACKGROUND: Infections, mostly those associated with colonization of wound by different pathogenic microorganisms, are one of the most serious health complications during a medical treatment. Therefore, this study is focused on the isolation, characterization, and identification of microorganisms prevalent in superficial wounds of patients (n = 50) presenting with bacterial infection. METHODS: After successful cultivation, bacteria were processed and analyzed. Initially the identification of the strains was performed through matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on comparison of protein profiles (2-30 kDa) with database. Subsequently, bacterial strains from infected wounds were identified by both matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and sequencing of 16S rRNA gene 108. RESULTS: The most prevalent species was Staphylococcus aureus (70%), and out of those 11% turned out to be methicillin-resistant (mecA positive). Identified strains were compared with patients' diagnoses using the method of artificial neuronal network to assess the association between severity of infection and wound microbiome species composition. Artificial neuronal network was subsequently used to predict patients' prognosis (n = 9) with 85% success. CONCLUSIONS: In all of 50 patients tested bacterial infections were identified. Based on the proposed artificial neuronal network we were able to predict the severity of the infection and length of the treatment.