From the Microbiome to the Electrome: Implications for the Microbiota-Gut-Brain Axis.

The gut microbiome plays a fundamental role in metabolism, as well as the immune and nervous systems. Microbial imbalance (dysbiosis) can contribute to subsequent physical and mental pathologies. As such, interest has been growing in the microbiota-gut-brain brain axis and the bioelectrical communication that could exist between bacterial and nervous cells. The aim of this study was to investigate the bioelectrical profile (electrome) of two bacterial species characteristic of the gut microbiome: a Proteobacteria Gram-negative bacillus Escherichia coli (E. coli), and a Firmicutes Gram-positive coccus Enterococcus faecalis (E. faecalis). We analyzed both bacterial strains to (i) validate the fluorescent probe bis-(1,3-dibutylbarbituric acid) trimethine oxonol, DiBAC4(3), as a reliable reporter of the changes in membrane potential (Vmem) for both bacteria; (ii) assess the evolution of the bioelectric profile throughout the growth of both strains; (iii) investigate the effects of two neural-type stimuli on Vmem changes: the excitatory neurotransmitter glutamate (Glu) and the inhibitory neurotransmitter γ-aminobutyric acid (GABA); (iv) examine the impact of the bioelectrical changes induced by neurotransmitters on bacterial growth, viability, and cultivability using absorbance, live/dead fluorescent probes, and viable counts, respectively. Our findings reveal distinct bioelectrical profiles characteristic of each bacterial species and growth phase. Importantly, neural-type stimuli induce Vmem changes without affecting bacterial growth, viability, or cultivability, suggesting a specific bioelectrical response in bacterial cells to neurotransmitter cues. These results contribute to understanding the bacterial response to external stimuli, with potential implications for modulating bacterial bioelectricity as a novel therapeutic target.

Context-Aware Statistical Dead Reckoning for Localization in IoT Scenarios.

The current trends in 5G and 6G systems anticipate vast communication capabilities and the deployment of massive heterogeneous connectivity with more than a million internet of things (IoT) and other devices per square kilometer and up to ten million gadgets in 6G scenarios. In addition, the new generation of smart industries and the energy of things (EoT) context demand novel, reliable, energy-efficient network protocols involving massive sensor cooperation. Such scenarios impose new demands and opportunities to cope with the ever-growing cooperative dense ad hoc environments. Position location information (PLI) plays a crucial role as an enabler of several location-aware network protocols and applications. In this paper, we have proposed a novel context-aware statistical dead reckoning localization technique suitable for high dense cooperative sensor networks, where direct angle and distance estimations between peers are not required along the route, as in other dead reckoning-based localization approaches, but they are obtainable from the node's context information. Validation of the proposed technique was assessed in several scenarios through simulations, achieving localization errors as low as 0.072 m for the worst case analyzed.

Bioelectrical State of Bacteria Is Linked to Growth Dynamics and Response to Neurotransmitters: Perspectives for the Investigation of the Microbiota-Brain Axis.

Inter-cellular communication is mediated by a sum of biochemical, biophysical, and bioelectrical signals. This might occur not only between cells belonging to the same tissue and/or animal species but also between cells that are, from an evolutionary point of view, far away. The possibility that bioelectrical communication takes place between bacteria and nerve cells has opened exciting perspectives in the study of the gut microbiota-brain axis. The aim of this paper is (i) to establish a reliable method for the assessment of the bioelectrical state of two bacterial strains: Bacillus subtilis (B. subtilis) and Limosilactobacillus reuteri (L. reuteri); (ii) to monitor the bacterial bioelectrical profile throughout its growth dynamics; and (iii) to evaluate the effects of two neurotransmitters (glutamate and γ-aminobutyric acid-GABA) on the bioelectrical signature of bacteria. Our results show that membrane potential (Vmem) and the proliferative capacity of the population are functionally linked in B. subtilis in each phase of the cell cycle. Remarkably, we demonstrate that bacteria respond to neural signals by changing Vmem properties. Finally, we show that Vmem changes in response to neural stimuli are present also in a microbiota-related strain L. reuteri. Our proof-of-principle data reveal a new methodological approach for the better understanding of the relation between bacteria and the brain, with a special focus on gut microbiota. Likewise, this approach will open exciting perspectives in the study of the inter-cellular mechanisms which regulate the bi-directional communication between bacteria and neurons and, ultimately, for designing gut microbiota-brain axis-targeted treatments for neuropsychiatric diseases.

Localization Algorithm for 3D Sensor Networks: A Recursive Data Fusion Approach.

Location-based applications for security and assisted living, such as human location tracking, pet tracking and others, have increased considerably in the last few years, enabled by the fast growth of sensor networks. Sensor location information is essential for several network protocols and applications such as routing and energy harvesting, among others. Therefore, there is a need for developing new alternative localization algorithms suitable for rough, changing environments. In this paper, we formulate the Recursive Localization (RL) algorithm, based on the recursive coordinate data fusion using at least three anchor nodes (ANs), combined with a multiplane location estimation, suitable for 3D ad hoc environments. The novelty of the proposed algorithm is the recursive fusion technique to obtain a reliable location estimation of a node by combining noisy information from several nodes. The feasibility of the RL algorithm under several network environments was examined through analytic formulation and simulation processes. The proposed algorithm improved the location accuracy for all the scenarios analyzed. Comparing with other 3D range-based positioning algorithms, we observe that the proposed RL algorithm presents several advantages, such as a smaller number of required ANs and a better position accuracy for the worst cases analyzed. On the other hand, compared to other 3D range-free positioning algorithms, we can see an improvement by around 15.6% in terms of positioning accuracy.

Ovarian activity and estrus behavior in early postpartum cows grazing Leucaena leucocephala in the tropics.

The legume Leucaena leucocephala (Leucaena) is widely used to supplement forage in silvopastoral livestock systems in Latin America. Little is known about its possible effects on the cow reproductive dynamic. The aim was to evaluate the effect of Leucaena foliage intake on re-establishment of ovarian activity and estrus behavior in early postpartum (7-90 days) cows. Twenty-four multiparous Bos taurus × Bos indicus cows were divided into two homogenous groups and assigned to one of two treatments: a silvopastoral system (SS, n = 12), consisting of an association of Cynodon nlemfuensis grass and L. leucocephala; and a control system (CS, n = 12), consisting of C. nlemfuensis alone. Intake of Leucaena in the SS ranged from 3.80 to 6.43 kg DM/cow/day. Plasma mimosine concentrations ranged from 1270 to 1530 µg/mL, and those for 2,3-dihydroxypyridine (DHP) from 147 to 729 µg/mL. No 3,4-DHP was detected in plasma. No difference (P > 0.05) between treatments was observed for the number of cows exhibiting small, medium, or dominant follicles, or estrus behavior. The number of cows which re-established ovarian cyclicity (n = 6) was lower (P < 0.05) in the SS than in the CS (n = 9). Corpus luteum lifespan was longer (P < 0.05) in the SS than in the CS. Intake of Leucaena affected the number of cows exhibiting ovarian cyclicity and extended corpus luteum life, but did not affect follicular development and estrus behavior.

Cuticular hydrocarbon profiles reveal geographic chemotypes in stingless bees (Hymenoptera: Meliponini).

Cuticular hydrocarbon (CHCs) variation has been detected in various insect taxa, but the potential contribution of cuticular compounds for analyzing intraspecific diversity at the population level has been little explored. Here we assess for the first time intraspecific variation in the CHC profile of stingless bees, using the species Melipona beecheii and Nannotrigona perilampoides. The objective is determining whether intraspecific variation can be useful for population identification. We found species-specific chemical patterns and extensive variation within each species. Notably, chemotypes were significantly associated to geographic origin in N. perilampoides but less so in M. beecheii and we discuss possible explanations for these patterns. Our results support the use of CHCs in conjunction with other methods in emerging problems such as undetected colony mobilization across regions. As CHCs are involved in several aspects of stingless bee recognition and interactions, it would be essential to unravel how these chemical signatures evolve across populations.

Evaluation of Organofunctionalized Polydimethylsiloxane Films for the Extraction of Furanic Compounds.

Hybrid membranes with three different thicknesses, PMDS_C1, PMDS_C2, and PMDS_C3 (0.21 ± 0.03 mm, 0.31 ± 0.05 mm, and 0.48 ± 0.07 mm), were synthesized by the sol-gel method using polydimethylsiloxane, hydroxy-terminated, and cyanopropyltriethoxysilane. The presence of cyano, methyl, and silicon-methyl groups was confirmed by FTIR analysis. Contact angle analysis revealed the membranes' hydrophilic nature. Solvent resistance tests conducted under vortex and ultrasonic treatments (45 and 60 min) demonstrated a preference order of acetonitrile > methanol > water. Furthermore, the membranes exhibited stability over 48 h when exposed to different pH conditions (1, 3, 6, and 9), with negligible mass losses below 1%. The thermogravimetric analysis showed that the material was stable until 400 °C. Finally, the sorption analysis showed its capacity to detect furfural, 2-furylmethylketone, 5-methylfurfural, and 2-methyl 2-furoate. The thicker membrane was able to adsorb and slightly desorb a higher concentration of furanic compounds due to its high polarity provided by the addition of the cyano groups. The results indicated that the membranes may be suitable for sorbent materials in extracting and enriching organic compounds.

Matrix solid-phase dispersion extraction of organophosphorus pesticides from propolis extracts and recovery evaluation by GC/MS.

Five organophosphorus pesticides (dichlorvos, diazinon, malathion, methyl parathion and coumaphos) were extracted from propolis by matrix solid-phase dispersion (MSPD) extraction using octadecylsilica (C18, 1.0 g) as dispersant material. The kind of solvent elution (acetonitrile or ethyl acetate), volume (8 mL and 15 mL), and adsorbent used to clean-up the extracts (graphitized carbon, florisil™ and silica) were optimized using fortified propolis samples (5.0 µg g(-1)). Recovery was determined by gas chromatography with mass spectrometric detection in selected ion monitoring mode (GC/MS-SIM) and statistical analysis was done to determine better extraction conditions. Relatively high recovery and lower relative standard deviation values (3.1-14.6%) were obtained when analytes were eluted with ethyl acetate from the MSPD column. Diazinon, malathion, methyl parathion, and coumaphos show recoveries of 72.7%, 84.6%, 62.6%, and 78.3%, respectively. In contrast, the recovery for dichlorvos was 53.8%. Additional adsorbents tested for clean-up and increase in solvent elution did not affect recoveries positively and caused a high background in chromatograms. Thus, final conditions were 1 mL of sample, 1 g C18 and 8 mL of ethyl acetate.

Antithrombotic Study and Identification of Metabolites in Leaf Extracts of Chaya [Cnidoscolus aconitifolius (Mill.) I.M. Johnst.].

In Mexico, Cnidoscolus aconitifolius (chaya) has been used to treat cardiovascular diseases (CVD). Because CVD are the number one cause of mortality, chaya use has become a health strategy. The aim of this study was to evaluate the antithrombotic activity and identify the metabolites in the most active extract. Aqueous (Aq), ethanolic (EtOH), acetonic (An), ethyl acetate (AcOEt), diethyl ether (Et2O), and hexanic (Hx) extracts were obtained. Platelet aggregation, phospholipase A2, prothrombin time (PT), activated partial thromboplastin time (aPTT), and clot lysis were evaluated. Metabolites were identified by gas chromatography-mass spectrometry (GC-MS). EtOH showed the greatest inhibition of platelet aggregation and phospholipase A2. Ac had the greatest effect on PT and aPTT. AcOEt had the greatest effect on clot lysis. EtOH, with the highest potential, was analyzed by GC-MS; fatty acids and triterpenes were identified. Thus, EtOH showed greater antiplatelet activity and other extracts showed moderate activity. This is a preliminary antithrombotic study. Future research will allow the development of nutraceuticals or functional ingredients for the prevention and treatment of thrombosis.

A Systematic Review on Recent Advances in mHealth Systems: Deployment Architecture for Emergency Response.

The continuous technological advances in favor of mHealth represent a key factor in the improvement of medical emergency services. This systematic review presents the identification, study, and classification of the most up-to-date approaches surrounding the deployment of architectures for mHealth. Our review includes 25 articles obtained from databases such as IEEE Xplore, Scopus, SpringerLink, ScienceDirect, and SAGE. This review focused on studies addressing mHealth systems for outdoor emergency situations. In 60% of the articles, the deployment architecture relied in the connective infrastructure associated with emergent technologies such as cloud services, distributed services, Internet-of-things, machine-to-machine, vehicular ad hoc network, and service-oriented architecture. In 40% of the literature review, the deployment architecture for mHealth considered traditional connective infrastructure. Only 20% of the studies implemented an energy consumption protocol to extend system lifetime. We concluded that there is a need for more integrated solutions specifically for outdoor scenarios. Energy consumption protocols are needed to be implemented and evaluated. Emergent connective technologies are redefining the information management and overcome traditional technologies.