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Across the world and within Europe, a growing number of consumers are choosing to buy gluten-free products. Motivations for a gluten-free diet and the consequences of consuming gluten are varied, from a medical necessity for those diagnosed with celiac disease to a range of health complications and discomfort for those who are gluten-intolerant. In this research, 7296 gluten-free consumers across 13 European countries responded to an online survey on the 33 types of gluten-free products purchased, how frequently they purchased them, their satisfaction with gluten-free quality and availability, the problems they have experienced, and the strategies they have employed to cope with these problems. The investigation examines whether and how these consumer attitudes and behaviors differ between those diagnosed with celiac disease, those who are gluten-intolerant, and those who are caregivers for others with a gluten-free diet. The results show that significant differences existed for all these habits and issues across the three gluten-free consumer groups. Specifically, caregivers purchased most of the gluten-free product types more frequently than the other two groups, experienced more availability problems, and were more likely to shop at multiple stores or make their own gluten-free products. Celiac-diagnosed consumers tended to buy gluten-free products more frequently than those who are gluten-intolerant, and they tended to be the most satisfied with the quality and range of gluten-free offerings. Despite purchasing frequency differences between the groups, the results suggest a similar hierarchy of gluten-free products that could provide the foundation for a European gluten-free food basket.

The increasing burden of lifestyle-related diseases highlights the need to address unhealthy dietary habits. This study aims to explore the latest dietary patterns in Japan following the COVID-19 pandemic, focusing on trends in health-promoting food choices. A web-based survey was conducted among 27,154 Japanese adults, selected via quota sampling to mirror national demographics. The study evaluated dietary diversity, measured through the Dietary Variety Score (Outcome 1), and the prioritization of nutritional and health considerations in food selection, assessed via a Likert scale (Outcome 2). Uniform Manifold Approximation and Projection (UMAP) and Ordering Points To Identify the Clustering Structure (OPTICS) algorithms were used to delineate patterns in health-centric food selections. OPTICS clustering revealed four distinct clusters for each outcome. Cluster 3, with a diverse diet, comprised older, predominantly female individuals with higher well-being and lower social isolation compared to Cluster 4, which lacked distinct dietary patterns. Cluster 3 also engaged more in snacking, treat foods, home cooking, and frozen meals. Similarly, a divide emerged between those prioritizing dietary considerations (Cluster C) and those indifferent to such aspects (Cluster D). The findings underscore the need for holistic post-COVID-19 public health initiatives addressing socioeconomic and cultural barriers to healthier dietary practices.

Scanning electron microscopy (SEM) techniques have been extensively performed to image and study bacterial cells with high-resolution images. Bacterial image segmentation in SEM images is an essential task to distinguish an object of interest and its specific region. These segmentation results can then be used to retrieve quantitative measures (e.g., cell length, area, cell density) for the accurate decision-making process of obtaining cellular objects. However, the complexity of the bacterial segmentation task is a barrier, as the intensity and texture of foreground and background are similar, and also, most clustered bacterial cells in images are partially overlapping with each other. The traditional approaches for identifying cell regions in microscopy images are labor intensive and heavily dependent on the professional knowledge of researchers. To mitigate the aforementioned challenges, in this study, we tested a U-Net-based semantic segmentation architecture followed by a post-processing step of morphological over-segmentation resolution to achieve accurate cell segmentation of SEM-acquired images of bacterial cells grown in a rotary culture system. The approach showed an 89.52% Dice similarity score on bacterial cell segmentation with lower segmentation error rates, validated over several cell overlapping object segmentation approaches with significant performance improvement.

We propose and investigate a bidirectional device-to-device (D2D) transmission scheme that exploits cooperative downlink non-orthogonal multiple access (NOMA) (termed as BCD-NOMA). In BCD-NOMA, two source nodes communicate with their corresponding destination nodes via a relaying node while exchanging bidirectional D2D messages simultaneously. BCD-NOMA is designed for improved outage probability (OP) performance, high ergodic capacity (EC) and high energy efficiency by allowing two sources to share the same relaying node for data transmission to their corresponding destination nodes while also facilitating bidirectional D2D communications exploiting downlink NOMA. Simulation and analytical expressions of the OP, EC and ergodic sum capacity (ESC) under both perfect and imperfect successive interference cancellation (SIC) are used to demonstrate the effectiveness of BCD-NOMA compared to conventional schemes.

Sulfate-reducing bacteria (SRB) are anaerobic bacteria that form biofilm and induce corrosion on various material surfaces. The quorum sensing (QS) system that employs acyl homoserine lactone (AHL)-type QS molecules primarily govern biofilm formation. Studies on SRB have reported the presence of AHL, but no AHL synthase have been annotated in SRB so far. In this computational study, we used a combination of data mining, multiple sequence alignment (MSA), homology modeling and docking to decode a putative AHL synthase in the model SRB, Desulfovibrio vulgaris Hildenborough (DvH). Through data mining, we shortlisted 111 AHL synthase genes. Conserved domain analysis of 111 AHL synthase genes generated a consensus sequence. Subsequent MSA of the consensus sequence with DvH genome indicated that DVU_2486 (previously uncharacterized protein from acetyltransferase family) is the gene encoding for AHL synthase. Homology modeling revealed the existence of seven α-helices and six β sheets in the DvH AHL synthase. The amalgamated study of hydrophobicity, binding energy, and tunnels and cavities revealed that Leu99, Trp104, Arg139, Trp97, and Tyr36 are the crucial amino acids that govern the catalytic center of this putative synthase. Identifying AHL synthase in DvH would provide more comprehensive knowledge on QS mechanism and help design strategies to control biofilm formation.

A significant amount of literature is available on biocorrosion, which makes manual extraction of crucial information such as genes and proteins a laborious task. Despite the fast growth of biology related corrosion studies, there is a limited number of gene collections relating to the corrosion process (biocorrosion). Text mining offers a potential solution by automatically extracting the essential information from unstructured text. We present a text mining workflow that extracts biocorrosion associated genes/proteins in sulfate-reducing bacteria (SRB) from literature databases (e.g., PubMed and PMC). This semi-automatic workflow is built with the Named Entity Recognition (NER) method and Convolutional Neural Network (CNN) model. With PubMed and PMCID as inputs, the workflow identified 227 genes belonging to several Desulfovibrio species. To validate their functions, Gene Ontology (GO) enrichment and biological network analysis was performed using UniprotKB and STRING-DB, respectively. The GO analysis showed that metal ion binding, sulfur binding, and electron transport were among the principal molecular functions. Furthermore, the biological network analysis generated three interlinked clusters containing genes involved in metal ion binding, cellular respiration, and electron transfer, which suggests the involvement of the extracted gene set in biocorrosion. Finally, the dataset was validated through manual curation, yielding a similar set of genes as our workflow; among these, hysB and hydA, and sat and dsrB were identified as the metal ion binding and sulfur metabolism genes, respectively. The identified genes were mapped with the pangenome of 63 SRB genomes that yielded the distribution of these genes across 63 SRB based on the amino acid sequence similarity and were further categorized as core and accessory gene families. SRB’s role in biocorrosion involves the transfer of electrons from the metal surface via a hydrogen medium to the sulfate reduction pathway. Therefore, genes encoding hydrogenases and cytochromes might be participating in removing hydrogen from the metals through electron transfer. Moreover, the production of corrosive sulfide from the sulfur metabolism indirectly contributes to the localized pitting of the metals. After the corroboration of text mining results with SRB biocorrosion mechanisms, we suggest that the text mining framework could be utilized for genes/proteins extraction and significantly reduce the manual curation time.

Copper (Cu) is an essential micronutrient required as a co-factor in the catalytic center of many enzymes. However, excess Cu can generate pleiotropic effects in the microbial cell. In addition, leaching of Cu from pipelines results in elevated Cu concentration in the environment, which is of public health concern. Sulfate-reducing bacteria (SRB) have been demonstrated to grow in toxic levels of Cu. However, reports on Cu toxicity towards SRB have primarily focused on the degree of toxicity and subsequent elimination. Here, Cu(II) stress-related effects on a model SRB, Desulfovibrio alaskensis G20, is reported. Cu(II) stress effects were assessed as alterations in the transcriptome through RNA-Seq at varying Cu(II) concentrations (5 µM and 15 µM). In the pairwise comparison of control vs. 5 µM Cu(II), 61.43% of genes were downregulated, and 38.57% were upregulated. In control vs. 15 µM Cu(II), 49.51% of genes were downregulated, and 50.5% were upregulated. The results indicated that the expression of inorganic ion transporters and translation machinery was massively modulated. Moreover, changes in the expression of critical biological processes such as DNA transcription and signal transduction were observed at high Cu(II) concentrations. These results will help us better understand the Cu(II) stress-response mechanism and provide avenues for future research.

The parallel reaction monitoring (PRM) assay has emerged as an alternative method of targeted quantification. The PRM assay is performed in a high resolution and high mass accuracy mode on a mass spectrometer. This review presents the features that make PRM a highly specific and selective method for targeted quantification using quadrupole-Orbitrap hybrid instruments. In addition, this review discusses the label-based and label-free methods of quantification that can be performed with the targeted approach.

The postsynaptic density (PSD) is a structural, electron-dense region of excitatory glutamatergic synapses, which is involved in a variety of cellular and signaling processes in neurons. The PSD is comprised of a large network of proteins, many of which have been implicated in a wide variety of neuropsychiatric disorders. Biochemical fractionation combined with mass spectrometry analyses have enabled an in-depth understanding of the protein composition of the PSD. However, the PSD composition may change rapidly in response to stimuli, and robust and reproducible methods to thoroughly quantify changes in protein abundance are warranted. Here, we report on the development of two types of targeted mass spectrometry-based assays for quantitation of PSD-enriched proteins. In total, we quantified 50 PSD proteins in a targeted, parallel reaction monitoring (PRM) assay using heavy-labeled, synthetic internal peptide standards and identified and quantified over 2100 proteins through a pre-determined spectral library using a data-independent acquisition (DIA) approach in PSD fractions isolated from mouse cortical brain tissue.

The recent identification of catalytically active peptidylglycine α-amidating monooxygenase (PAM) in Chlamydomonas reinhardtii, a unicellular green alga, suggested the presence of a PAM-like gene and peptidergic signaling in the last eukaryotic common ancestor (LECA). We identified prototypical neuropeptide precursors and essential peptide processing enzymes (subtilisin-like prohormone convertases and carboxypeptidase B-like enzymes) in the C. reinhardtii genome. Reasoning that sexual reproduction by C. reinhardtii requires extensive communication between cells, we used mass spectrometry to identify proteins recovered from the soluble secretome of mating gametes, and searched for evidence that the putative peptidergic processing enzymes were functional. After fractionation by SDS-PAGE, signal peptide-containing proteins that remained intact, and those that had been subjected to cleavage, were identified. The C. reinhardtii mating secretome contained multiple matrix metalloproteinases, cysteine endopeptidases, and serine carboxypeptidases, along with one subtilisin-like proteinase. Published transcriptomic studies support a role for these proteases in sexual reproduction. Multiple extracellular matrix proteins (ECM) were identified in the secretome. Several pherophorins, ECM glycoproteins homologous to the Volvox sex-inducing pheromone, were present; most contained typical peptide processing sites, and many had been cleaved, generating stable N- or C-terminal fragments. Our data suggest that subtilisin endoproteases and matrix metalloproteinases similar to those important in vertebrate peptidergic and growth factor signaling play an important role in stage transitions during the life cycle of C. reinhardtii.

Amidst the rapid development of the fifth generation (5G) networks, Internet of Things (IoT) is considered as one of the most important part of 5G next generation networks as it can support massive object communications. These massive object communications in the context of IoT is expected to consume a huge power. Furthermore, IoT sensors or devices are rather power constrained and are mostly battery operated. Therefore, energy efficiency of such network of IoT devices is a major concern. On the other hand, energy harvesting (EH) is an emerging paradigm that allows the wireless nodes to recharge themselves through radio frequency (RF) signals directed to them from the source node and then relaying or transmitting the information. Although a myriad of works have been carried out in the literature for EH, the vast majority of those works only consider RF EH at the relay node and successfully transmitting the source node data. Those approaches do not consider the data transmission of the relay node that may be an energy deprived IoT node which needs to transmit its own data along with the source node data to their respective destination nodes. Therefore, in this paper, we envisioned a RF EH and information transmission system based on time switching (TS) relaying, power splitting (PS) relaying and non-orthogonal multiple access (NOMA) which is suitable for wireless powered IoT relay systems. A source node information data is relayed through power constrained IoT relay node I o T R that first harvests the energy from source node RF signal using either TS and PS relaying protocol and then transmits the source node information along with its information using NOMA protocol to the respective destination nodes. Considering NOMA as a transmission protocol, we have mathematically derived analytical expressions for TS and PS relaying protocol for our proposed system. We have also formulated an algorithm to find out optimal TS and PS factor that maximizes the sum-throughput for our proposed system. Our proposed system analytical results for TS and PS protocol are validated by the simulation results.

Cocaine addiction is characterized by aberrant plasticity of the mesolimbic dopamine circuit, leading to dysregulation of motivation to seek and take drug. Despite the significant toll that cocaine use disorder exacts on society, there are currently no available pharmacotherapies. We have recently identified granulocyte-colony stimulating factor (G-CSF) as a soluble cytokine that alters the behavioral response to cocaine and which increases dopamine release from the ventral tegmental area (VTA). Despite these known effects on behavior and neurophysiology, the molecular mechanisms by which G-CSF affects brain function are unclear. In this study mice were treated with repeated injections of G-CSF, cocaine or a combination and changes in protein expression in the VTA were examined using an unbiased proteomics approach. Repeated G-CSF treatment resulted in alterations in multiple signaling pathways related to synaptic plasticity and neuronal morphology. While the treatment groups had marked overlap in their effect, injections of cocaine and the combination of cocaine and G-CSF lead to distinct patterns of significantly regulated proteins. These experiments provide valuable information as to the molecular pathways that G-CSF activates in an important limbic brain region and will help to guide further characterization of G-CSF function and evaluation as a possible translational target.

Across the world and within Europe, a growing number of consumers are choosing to buy gluten-free products. Motivations for a gluten-free diet and the consequences of consuming gluten are varied, from a medical necessity for those diagnosed with celiac disease to a range of health complications and discomfort for those who are gluten-intolerant. In this research, 7296 gluten-free consumers across 13 European countries responded to an online survey on the 33 types of gluten-free products purchased, how frequently they purchased them, their satisfaction with gluten-free quality and availability, the problems they have experienced, and the strategies they have employed to cope with these problems. The investigation examines whether and how these consumer attitudes and behaviors differ between those diagnosed with celiac disease, those who are gluten-intolerant, and those who are caregivers for others with a gluten-free diet. The results show that significant differences existed for all these habits and issues across the three gluten-free consumer groups. Specifically, caregivers purchased most of the gluten-free product types more frequently than the other two groups, experienced more availability problems, and were more likely to shop at multiple stores or make their own gluten-free products. Celiac-diagnosed consumers tended to buy gluten-free products more frequently than those who are gluten-intolerant, and they tended to be the most satisfied with the quality and range of gluten-free offerings. Despite purchasing frequency differences between the groups, the results suggest a similar hierarchy of gluten-free products that could provide the foundation for a European gluten-free food basket.