Protein hydrolysates show great promise as bioactive food and feed ingredient and for valorization of side-streams from e.g. the fish processing industry. This study characterizes bulk emulsifying, foaming, and in vitro antioxidative properties of hydrolysates derived from cod frame by application of Alcalase and Neutrase, individually and sequentially as well as the influence of heat-treatment prior to hydrolysis. We present a novel approach that utilizes proteomics data for calculation of weighted mean peptide properties (length, molecular weight, and charge) and peptide-level abundance estimation. Using subsequent bioinformatic prediction of biofunctional properties to describe observed bulk properties, we are able to provide an in-depth hydrolysate characterization not previously seen. All hydrolysates displayed comparable or higher emulsifying activity and stability than sodium caseinate. Heat-treatment significantly increased stability but showed a negative effect on the activity and degree of hydrolysis. Combining peptide abundance with predicted emulsifying activity, we were able to identify several peptides that are likely linked to the observed differences in bulk emulsifying properties. In general, decreased hydrolysis resulted in significantly higher chelating activity, while the opposite was observed for radical scavenging activity. The study highlights the prospects of applying proteomics and bioinformatics for hydrolysate characterization and in food protein science.

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for Breast Cancer Liver Metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, it aimed to shed light on the diversities of this process. This research investigates Breast cancer liver metastasis relapse by employing a comprehensive approach that integrates data filtering, Gene Ontology and KEGG Pathway Analysis, Overall Survival analysis, identification of the Alteration in the DEGs, Visualization of Protein-Protein Interaction Network, Signor 2.0, identification of positively correlated genes, screening results of the function of hub genes, immune cell infiltration analysis, genetic alternation analysis, Copy number variant analysis, Gene to mRNA interaction, transcription factor analysis , autodocking and identification of Potential Treatment Target. This study’s integrative approach unveils metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Climate change and globalization have raised the risk of vector-borne disease (VBD) introduction and spread in various European nations in recent years. In Italy, viruses carried by tropical vectors have been shown to cause viral encephalitis, one of the symptoms of arbovirosis, a spectrum of viral disorders spread by arthropods such as mosquitoes and ticks. Arbovirosis are currently causing alarm and attention, and the World Health Organization (WHO) has released recommendations to adopt essential measures, particularly during the hot season, to restrict the spreading of the infectious agents among breeding stocks. In this scenario, rapid analysis systems are required, because they can quickly provide information on potential virus-host interactions, the evolution of the infection, and the onset of disabling clinical symptoms, or serious illnesses. Such systems include bioinformatics approaches integrated with molecular evaluation. Viruses have co-evolved different strategies to transcribe their own genetic material, by changing the host's transcriptional machinery, even in short periods of time. The introduction of genetic alterations, particularly in RNA viruses, results in a continuous adaptive fight against the host's immune system. We suggest an in silico pipeline method to unravel viral sequences that may interact with host RNA binding proteins (RBPs), which play important roles in RNA metabolism and its several related biological processes. Indeed, viral RNA sequences, able to bind host RBPs may compete with cellular RNAs, altering important metabolic processes. Our findings suggest that the proposed in silico approach, could be a useful and promising tool to investigate the complex and multiform clinical manifestations of viral encephalitis, and possibly identify altered metabolic pathways as targets of pharmacological treatments and innovative therapeutic protocols.

Serious outbreaks of foodborne disease have been caused by Listeria monocytogenes found in retail delicatessens and the severity of disease is significant, with high hospitalization and mortality rates. Little is understood about the formidable public health threat of L. monocytogenesin all four niches, humans, animals, food and environment in Egypt. This study analyzed the presence of L. monocytogenes collected from the four environmental niches and bioinformatic analysis was implemented to analyze and compare the data. PCR was used to detect virulence genes encoded by pathogenicity island (LIPI-1). prfA amino acid substation that causes constitutive expression of virulence was common in 77.7% of isolates. BLAST analysis did not match other isolates in the NCBI database suggesting this may be a characteristic of the region associated with these isolates. A second group included the NH1 isolate originating in China, and BLAST analysis showed this prfA allele was shared with isolates from other global locations such as Europe and North America. Identification of possible links and transmission pathways between the four niches, helps to decrease the risk of disease in humans, to take more specific control measures in the context of disease prevention, to limit economic losses associated with food recalls and highlightens the need to treatment options.