Hasil untuk "Biochemistry"

A. Pegg

D. Crans, Jason J. Smee, Ernestas Gaidamauskas et al.

J. T. Lumeij

W. Pryor

B. Lippert

K. Cheeseman, T. Slater

J. Kiang, G. Tsokos

P. Mignatti, D. Rifkin

C. H. Raetz

J. Kaplan

E. Mandelkow, E. Mandelkow

B. Lassègue, A. San Martin, K. Griendling

W. Maret

I. Ludwig, M. Clifford, M. Lean et al.

Ting-Rong Hsu, Pei-Hao Chen, Wei-Sheng Lin

Epilepsy is one of the most common neurological disorders in both children and adults, characterized by significant clinical heterogeneity and dynamic natural course. The pathophysiological roles of astrocytes in epilepsy have been increasingly recognized. Fluid biomarkers derived from astrocytes are actively studied in epileptic disorders, although their use remains limited in clinical practice. This review aims to compile and analyze clinical and experimental findings concerning astrocytic biomarkers in epilepsy and related conditions, with a focus on glial fibrillary acidic protein (GFAP) and S100 calcium-binding protein B (S100B). Herein we examine their roles in assessing seizure burden and temporal dynamics, explore their potential in distinguishing epileptic from psychogenic non-epileptic seizures, and discuss their therapeutic, prognostic, and mechanistic implications in the context of epileptic disorders.

Nobumitsu Hirai, Yuhei Miwa, Shunta Hattori et al.

Biofilms cause a variety of problems, such as food spoilage, food poisoning, infection, tooth decay, periodontal disease, and metal corrosion, so knowledge on biofilm prevention and removal is important. A detailed observation of the three-dimensional structure of biofilms on the nanoscale is expected to provide insight into this. In this study, we report on the successful in situ nanoscale observations of a marine bacterial biofilm on glass in phosphate buffer solution (PBS) using both scanning ion conductance microscopy (SICM) and confocal laser scanning microscopy (CLSM) over the same area. By observing the same area by SICM and CLSM, we were able to clarify the three-dimensional morphology of the biofilm, the arrangement of bacteria within the biofilm, and the difference in local ion conductivity within the biofilm simultaneously, which could not be achieved by observation using a microscope alone.

Cassandra Upton, Gerhard Prinsloo, Paul Anton Steenkamp et al.

IntroductionSea cucumbers are ecologically and economically significant marine invertebrates, yet the metabolic diversity and bioactive potential of noncommercialized, endemic species remains poorly understood.MethodsThis study presents the first intra-species metabolomic analysis of Pseudocnella sykion, a species endemic to the Eastern coast of Southern Africa, using untargeted 1HNMR metabolomics and full-scan UPLC-QTOF-HR-MS.ResultsThe analysis revealed a diverse array of metabolites associated with protein synthesis, tissue growth, osmoregulation, and energy utilization, with distinct tissue-specific patterns across the body wall, gonad, and gut/mesentery. The gut/mesentery tissue showed higher levels of amino acids and energy-related compounds. UPLCQTOF-HR-MS tentatively identified several metabolites, including triterpene glycosides and rosmarinic acid, a phenolic compound typically associated with plants. Online resources, including the Dictionary of Marine Natural Products, contained no previously recorded compounds for P. sykion.DiscussionThese findings underscore the untapped potential of P. sykion as a source of novel metabolites and demonstrate the utility of untargeted metabolomics in generating baseline profiles for underexplored marine species. The results offer a foundation for future research into bioactivity, environmental monitoring, and cultivation strategies. While this study provides critical baseline data, challenges in metabolite identification and extraction underscore the need for further targeted analyses. Overall, this research enhances our understanding of the metabolic dynamics of sea cucumbers and advocates for continued exploration of lesser-known species to support conservation, bioprospecting, and sustainable aquaculture. It represents a pioneering effort in metabolomic profiling of Southern African sea cucumber species and lays the groundwork for future investigations into their metabolic pathways and potential bioactivities.

Anasuya Chattopadhyay, Daniel Reti, Hans D. Schotten

The early research report explores the possibility of using Graph Neural Networks (GNNs) for anomaly detection in internet traffic data enriched with information. While recent studies have made significant progress in using GNNs for anomaly detection in finance, multivariate time-series, and biochemistry domains, there is limited research in the context of network flow data. In this report, we explore the idea that leverages information-enriched features extracted from network flow packet data to improve the performance of GNN in anomaly detection. The idea is to utilize feature encoding (binary, numerical, and string) to capture the relationships between the network components, allowing the GNN to learn latent relationships and better identify anomalies.

Mahakaran Sandhu, John Chen, Dana Matthews et al.

Proteins evolve through complex sequence spaces, with fitness landscapes serving as a conceptual framework that links sequence to function. Fitness landscapes can be smooth, where multiple similarly accessible evolutionary paths are available, or rugged, where the presence of multiple local fitness optima complicate evolution and prediction. Indeed, many proteins, especially those with complex functions or under multiple selection pressures, exist on rugged fitness landscapes. Here we discuss the theoretical framework that underpins our understanding of fitness landscapes, alongside recent work that has advanced our understanding - particularly the biophysical basis for smoothness versus ruggedness. Finally, we address the rapid advances that have been made in computational and experimental exploration and exploitation of fitness landscapes, and how these can identify efficient routes to protein optimization.

Thore Hillig, Josephine R. Kristensen, Claus L. Brasen et al.

Abstract To assess if SARS-CoV-2 (COVID-19) systemic disease can be determined by available nucleoprotein assays, we compared the performance of three commercial SARS-CoV-2 nucleoprotein (N) assays in plasma. A total of 272 plasma samples collected in the period November–December 2021 were analyzed by the methods Simoa SARS CoV‐2 N Protein Advantage Kit [Quanterix Simoa], Solsten SARS-CoV-2 Antigen enzyme immunosorbent assay (ELISA) [Solsten ELISA], and Elecsys SARS‐CoV‐2 Antigen electrochemiluminescence immunoassay [Elecsys ECLIA]. Additionally, a dilution series of inactivated virus culture was analyzed by the three assays. The SARS CoV-2 PCR-status was not known for the patients. Linear correlation in the pairwise correlation between assays as well as linearity of dilution series of inactivated virus culture was estimated by Spearman score. Sensitivity and specificity were estimated by pairwise comparison. The three assays showed poor agreement on patient samples with regards to concentration. Performance on virus culture was excellent but with different level of detection (LOD). Positive vs negative results show comparable sensitivity and specificity of Quanterix Simoa and Solsten ELISA, with a higher LOD in Elecsys ECLIA and thus lower sensitivity and high specificity. N by all tested assays can be used as a marker for systemic COVID-19 disease.