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Graph embedding techniques are using deep learning algorithms in data analysis to solve problems of such as node classification, link prediction, community detection, and visualization. Although typically used in the context of guessing friendships in social media, several applications for graph embedding techniques in biomedical data analysis have emerged. While these approaches remain computationally demanding, several developments over the last years facilitate their application to study biomedical data and thus may help advance biological discoveries. Therefore, in this review, we discuss the principles of graph embedding techniques and explore the usefulness for understanding biological network data derived from mass spectrometry and sequencing experiments, the current workhorses of systems biology studies. In particular, we focus on recent examples for characterizing protein-protein interaction networks and predicting novel drug functions.

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In the present study, we explored the effects of displacement directionality in mating behavior (i.e., lateralized and non-lateralized movements) on mating success (i.e., copulation occurs) and efficiency (i.e., time length at which copulation is achieved), and its association with sex and sexual experience in A. diaperinus. To do so, we carried out mating experiments and recorded the behavior of the mating pair during the whole mating sequence (i.e., precopulatory and copulatory phases). During the precopulatory phase, independently of sex and sexual experience, all beetles performed non-lateralized (i.e., backside or frontside) approaches; however, only sexually experienced beetles showed lateralized approaches (i.e., right-side and left-side). Notably, experienced males exhibited greater mating success than virgin males. After the approach, both virgin and experienced males displayed lateralized and non-lateralized mounts on the females with distinct mating success. Regardless of their sexual experience, 100% of successful mating attempts were achieved when males mounted from the females' right side. Furthermore, the development of lateralized approaches and mounts reduces the time of mating sequence span compared with non-lateralized behaviors. We highlight the importance of lateralization in mating behavior and sexual experience to achieve higher mating success, addressing a potential learning ability of beetles based on experience.

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Alphitobius diaperinus is one of the most significant pests in the poultry industry. Identifying the role of self-produced chemical signals can help control it. Here, we exposed adults to the olfactory signals of other adults of similar and different genders (either males or females) and sexual experiences (i.e., virgin and experienced) to assess their long-range attractiveness and, at short-range, their mating behavior responses (i.e., touching, mounting, and copulation). In olfactometric experiments, our results indicate that adults are attracted to the olfactory signals of other male adults, independently of gender, or sexual condition, indicating the presence of generalized long-range attractive signals, in contrast to female signals, can be both factor-dependent. However, in mating experiments, virgin males developed more robust mating responses (i.e., they mount and copulate longer with females) compared to sexually experienced males, even though they both have similar precopulatory behavioral responses (i.e., time of antennal and leg touching). These results address the importance of short-range chemical signals in eliciting copulation. Furthermore, when virgins of both genders were tested, their mating responses were significantly longer than any other pair combination, indicating that sexual experience also affects mating behavior. Chemical analyses of adult extracts showed that sexual experience, but not gender, is linked to differences in chemical profiles of adults, primarily involved in short-range signaling. These findings provide new insights into the attractiveness and mating responses of A. diaperinus and the role of sexual experience in shaping the behavior and chemical profile of insects that mate multiple times during their lifetime.

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The Rimac river is the main source of water for Lima, Peru's capital megacity. The river is constantly affected by different types of contamination including mine tailings in the Andes and urban sewage in the metropolitan area. In this work, we aim to produce the first characterization of aquatic bacterial communities in the Rimac river using a 16S rRNA metabarcoding approach which would be useful to identify bacterial diversity and potential understudied pathogens. We report a lower diversity in bacterial communities from the Lower Rimac (Metropolitan zone) in comparison to other sub-basins. Samples were generally grouped according to their geographical location. Bacterial classes Alphaproteobacteria, Bacteroidia, Campylobacteria, Fusobacteriia, and Gammaproteobacteria were the most frequent along the river. Arcobacter cryaerophilus (Campylobacteria) was the most frequent species in the Lower Rimac while Flavobacterium succinicans (Bacteroidia) and Hypnocyclicus (Fusobacteriia) were the most predominant in the Upper Rimac. Predicted metabolic functions in the microbiota include bacterial motility and quorum sensing. Additional metabolomic analyses showed the presence of some insecticides and herbicides in the Parac-Upper Rimac and Santa Eulalia-Parac sub-basins. The dominance in the Metropolitan area of Arcobacter cryaerophilus, an emergent pathogen associated with fecal contamination and antibiotic multiresistance, that is not usually reported in traditional microbiological quality assessments, highlights the necessity to apply next-generation sequencing tools to improve pathogen surveillance. We believe that our study will encourage the integration of omics sciences in Peru and its application on current environmental and public health issues.

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Flavor is one of the most prominent characteristics of chocolate and is crucial in determining the price the consumer is willing to pay. At present, two types of cocoa beans have been characterized according to their flavor and aroma profile, i.e., (1) the bulk (or ordinary) and (2) the fine flavor cocoa (FFC). The FFC has been distinguished from bulk cocoa for having a great variety of flavors. Aiming to differentiate the FFC bean origin of Peruvian chocolate, an analytical methodology using gas chromatography coupled to mass spectrometry (GC-MS) was developed. This methodology allows us to characterize eleven volatile organic compounds correlated to the aromatic profile of FFC chocolate from this geographical region (based on buttery, fruity, floral, ethereal sweet, and roasted flavors). Monitoring these 11 flavor compounds during the chain of industrial processes in a retrospective way, starting from the final chocolate bar towards pre-roasted cocoa beans, allows us to better understand the cocoa flavor development involved during each stage. Hence, this methodology was useful to distinguish chocolates from different regions, north and south of Peru, and production lines. This research can benefit the chocolate industry as a quality control protocol, from the raw material to the final product.

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Fungi are a highly diverse group of heterotrophic organisms that play an important role in diverse ecological interactions, many of which are chemically mediated. Fungi have a very versatile metabolism, which allows them to synthesize a large number of still little-known chemical compounds, such as soluble compounds that are secreted into the medium and volatile compounds that are chemical mediators over short and long distances. Mass spectrometry (MS) is currently playing a dominant role in mycological studies, mainly due to its inherent sensitivity and rapid identification capabilities of different metabolites. Furthermore, MS has also been used as a reliable and accurate tool for fungi identification (i.e., biotyping). Here, we introduce the readers about fungal specialized metabolites, their role in ecological interactions and provide an overview on the MS-based techniques used in fungal studies. We particularly present the importance of sampling techniques, strategies to reduce false-positive identification and new MS-based analytical strategies that can be used in mycological studies, further expanding the use of MS in broader applications. Therefore, we foresee a bright future for mass spectrometry-based research in the field of mycology.

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Volatile organic compounds (VOCs) are small molecular mass substances, which exhibit low boiling points and high-vapour pressures. They are ubiquitous in nature and produced by almost any organism of all kingdoms of life. VOCs are involved in many inter- and intraspecies interactions ranging from antimicrobial or fungal effects to plant growth promotion and human taste perception of fermentation products. VOC profiles further reflect the metabolic or phenotypic state of the living organism that produces them. Hence, they can be exploited for non-invasive medicinal diagnoses or industrial fermentation control. Here, we introduce the reader to these diverse applications associated with the monitoring and analysis of VOC emissions. We also present our vision of real-time VOC analysis enabled by newly developed analytical techniques, which will further broaden the use of VOCs in even wider applications. Hence, we foresee a bright future for VOC research and its associated fields of applications.

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