A Survey on Error Exponents in Distributed Hypothesis Testing: Connections with Information Theory, Interpretations, and Applications.

A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors' exponential rate of convergence, known as error exponents, provides crucial insights into system performance. Error exponents offer a lens through which we can understand how operational restrictions, such as resource constraints and impairments in communications, affect the accuracy of distributed inference in networked systems. This survey presents a comprehensive review of key results in HT, from the foundational Stein's Lemma to recent advancements in distributed HT, all unified through the framework of error exponents. We explore asymptotic and non-asymptotic results, highlighting their implications for designing robust and efficient networked systems, such as event detection through lossy wireless sensor monitoring networks, collective perception-based object detection in vehicular environments, and clock synchronization in distributed environments, among others. We show that understanding the role of error exponents provides a valuable tool for optimizing decision-making and improving the reliability of networked systems.

Scattering approaches to unravel protein solution behaviors in ionic liquids and deep eutectic solvents: From basic principles to recent developments.

Proteins in ionic liquids (ILs) and deep eutectic solvents (DESs) have gained significant attention due to their potential applications in various fields, including biocatalysis, bioseparation, biomolecular delivery, and structural biology. Scattering approaches including dynamic light scattering (DLS) and small-angle X-ray and neutron scattering (SAXS and SANS) have been used to understand the solution behavior of proteins at the nanoscale and microscale. This review provides a thorough exploration of the application of these scattering techniques to elucidate protein properties in ILs and DESs. Specifically, the review begins with the theoretical foundations of the relevant scattering approaches and describes the essential solvent properties of ILs and DESs linked to scattering such as refractive index, scattering length density, ion-pairs, liquid nanostructure, solvent aggregation, and specific ion effects. Next, a detailed introduction is provided on protein properties such as type, concentration, size, flexibility and structure as observed through scattering methodologies. This is followed by a review of the literature on the use of scattering for proteins in ILs and DESs. It is highlighted that enhanced data analysis and modeling tools are necessary for assessing protein flexibility and structure, and for understanding protein hydration, aggregation and specific ion effects. It is also noted that complementary approaches are recommended for comprehensively understanding the behavior of proteins in solution due to the complex interplay of factors, including ion-binding, dynamic hydration, intermolecular interactions, and specific ion effects. Finally, the challenges and potential research directions for this field are proposed, including experimental design, data analysis approaches, and supporting methods to obtain fundamental understandings of complex protein behavior and protein systems in solution. We envisage that this review will support further studies of protein interface science, and in particular studies on solvent and ion effects on proteins.

Ecotourism and mangrove conservation in Southeast Asia: Current trends and perspectives.

Mangroves in Southeast Asia provide numerous supporting, provisioning, regulating, and cultural services that are crucial to the environment and local livelihoods since they support biodiversity conservation and climate change resilience. However, Southeast Asia mangroves face deforestation threats from the expansion of commercial aquaculture, agriculture, and urban development, along with climate change-related natural processes. Ecotourism has gained prominence as a financial incentive tool to support mangrove conservation and restoration. Through a systematic literature review approach, we examined the relationships between ecotourism and mangrove conservation in Southeast Asia based on scientific papers published from 2010 to 2022. Most of the studies were reported in Indonesia, Malaysia, Philippines, Thailand, and Vietnam, respectively, which were associated with the highest number of vibrant mangrove ecotourism sites and largest mangrove areas compared to the other countries of Southeast Asia. Mangrove-related ecotourism activities in the above countries mainly include boat tours, bird and wildlife watching, mangrove planting, kayaking, eating seafood, and snorkeling. The economic benefits, such as an increase in income associated with mangrove ecotourism, have stimulated infrastructural development in ecotourism destinations. Local communities benefited from increased access to social amenities such as clean water, electricity, transportation networks, schools, and health services that are intended to make destinations more attractive to tourists. Economic benefits from mangrove ecotourism motivated the implementation of several community-based mangrove conservation and restoration initiatives, which attracted international financial incentives and public-private partnerships. Since mangroves are mostly located on the land occupied by indigenous people and local communities, ensuring respect for their land rights and equity in economic benefit sharing may increase their intrinsic motivation and participation in mangrove restoration and conservation initiatives. Remote sensing tools for mangrove monitoring, evaluation, and reporting, and integrated education and awareness campaigns can ensure the long-term conservation of mangroves while sustaining ecotourism's economic infrastructure and social amenities benefits.

Optogenetic modulation of cardiac autonomic nervous system.

The following is a narrative review of the fundamentals of optogenetics. It focuses on the advantages and constraints of manipulating the autonomic nervous system by modifying the pathophysiological characteristics that arise in different diseases. Although the use of this technique is currently experimental, we will discuss improvements that have been implemented and identify the necessary measures for potential preclinical translation in the control of the cardiac autonomic nervous system.

Exploring the cobia (Rachycentron canadum) genome: unveiling putative male heterogametic regions and identification of sex-specific markers.

BACKGROUND: Cobia (Rachycentron canadum) is the only member of the Rachycentridae family and exhibits considerable sexual dimorphism in growth rate. Sex determination in teleosts has been a long-standing basic biological question, and the molecular mechanisms of sex determination/differentiation in cobia are completely unknown. RESULTS: Here, we reported 2 high-quality, chromosome-level annotated male and female cobia genomes with assembly sizes of 586.51 Mb (contig/scaffold N50: 86.0 kb/24.3 Mb) and 583.88 Mb (79.9 kb/22.5 Mb), respectively. Synteny inference among perciform genomes revealed that cobia and the remora Echeneis naucrates were sister groups. Further, whole-genome resequencing of 31 males and 60 females, genome-wide association study, and sequencing depth analysis identified 3 short male-specific regions within a 10.7-kb continuous genomic region on male chromosome 18, which hinted at an undifferentiated sex chromosome system with a putative XX/XY mode of sex determination in cobia. Importantly, the only 2 genes within/between the male-specific regions, epoxide hydrolase 1 (ephx1, renamed cephx1y) and transcription factor 24 (tcf24, renamed ctcf24y), showed testis-specific/biased gene expression, whereas their counterparts cephx1x and ctf24x, located in female chromosome 18, were similarly expressed in both sexes. In addition, male-specific PCR targeting the cephx1y gene revealed that this genomic feature is conserved in cobia populations from Panama, Brazil, Australia, and Japan. CONCLUSION: The first comprehensive genomic survey presented here is a valuable resource for future studies on cobia population structure and dynamics, conservation, and evolutionary history. Furthermore, it establishes evidence of putative male heterogametic regions with 2 genes playing a potential role in the sex determination of the species, and it provides further support for the rapid evolution of sex-determining mechanisms in teleost fish.

Rheology of Suspensions of TEMPO-Oxidised and Cationic Cellulose Nanofibrils-The Effect of Chemical Pre-Treatment.

Cellulose nanofibrils (CNFs) are particles with a high aspect ratio. Typically, chemically pre-treated CNFs (containing anionic or cationic charged groups) consist of long fibrils (up to 2 µm) with very low thickness (less than 10 nm). Derived from their high aspect ratio, CNFs form strong hydrogels with high elasticity at low concentrations. Thus, CNF suspensions appear as an interesting rheology modifier to be applied in cosmetics, paints, foods, and as a mineral suspending agent, among other applications. The high viscosity results from the strong 3D fibril network, which is related to the good fibrillation of the material, allowing the nanofibrils to overlap. The overlap concentration (c*) was found to vary from ca. 0.13 to ca. 0.60 wt.% depending on the type and intensity of the pre-treatment applied during the preparation of the CNFs. The results confirm the higher tendency for the fibres treated with (3-chloro-2-hydroxypropyl) trimethylammonium chloride (CHPTAC) and 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO) to form a 3D network, resulting in the lowest c*. For the TEMPO-oxidised CNF suspensions, it was also found that aggregation is improved at acidic pH conditions due to lower charge repulsion among fibrils, leading to an increase in the suspension viscosity as well as higher apparent yield stresses. TEMPO CNF suspensions with a low content of carboxylic groups tend to precipitate at moderately acidic pH values.

Revealing Retroviral Life Cycles Using Visible Viruses and Live Cell Imaging.

Viruses exploit key host cell factors to accomplish each individual stage of the viral replication cycle. To understand viral pathogenesis and speed the development of new antiviral strategies, high-resolution visualization of virus-host interactions is needed to define where and when these events occur within cells. Here, we review state-of-the-art live cell imaging techniques for tracking individual stages of viral life cycles, focusing predominantly on retroviruses and especially human immunodeficiency virus type 1, which is most extensively studied. We describe how visible viruses can be engineered for live cell imaging and how nonmodified viruses can, in some instances, be tracked and studied indirectly using cell biosensor systems. We summarize the ways in which live cell imaging has been used to dissect the retroviral life cycle. Finally, we discuss select challenges for the future including the need for better labeling strategies, increased resolution, and multivariate systems that will allow for the study of full viral replication cycles.

Comparative transcriptome analyses reveal regulatory network and hub genes of aluminum response in roots of elephant grass (Cenchrus purpureus).

Aluminum (Al) toxicity severely restricts the growth and productivity of elephant grass in acidic soils around the world. However, the molecular mechanisms of Al response have not been investigated in elephant grass. In this study, we conducted phenotype, physiology, and transcriptome analysis of elephant grass roots in response to Al stress. Phenotypic analysis revealed that a low concentration of Al stress improved root growth while higher Al concentrations inhibit root growth. Al stress significantly increased the citrate (CA) content in roots, while the expression levels of genes related to citrate synthesis were substantially changed. The multidrug and toxic compound extrusion (MATE) family were identified as hub genes in the co-expression network of Al response in elephant grass roots. Phylogenetic analysis showed that hub genes CpMATE93 and CpMATE158 belonged to the same clade as other MATE genes reported to be involved in citrate transport. Additionally, overexpression of CpMATE93 conferred Al resistance in yeast cells. These results provide a theoretical basis for further studies of molecular mechanisms in the elephant grass response to Al stress and could help breeders develop elite cultivars with Al tolerance.

EEG functional connectivity as a Riemannian mediator: An application to malnutrition and cognition.

Mediation analysis assesses whether an exposure directly produces changes in cognitive behavior or is influenced by intermediate "mediators". Electroencephalographic (EEG) spectral measurements have been previously used as effective mediators representing diverse aspects of brain function. However, it has been necessary to collapse EEG measures onto a single scalar using standard mediation methods. In this article, we overcome this limitation and examine EEG frequency-resolved functional connectivity measures as a mediator using the full EEG cross-spectral tensor (CST). Since CST samples do not exist in Euclidean space but in the Riemannian manifold of positive-definite tensors, we transform the problem, allowing for the use of classic multivariate statistics. Toward this end, we map the data from the original manifold space to the Euclidean tangent space, eliminating redundant information to conform to a "compressed CST." The resulting object is a matrix with rows corresponding to frequencies and columns to cross spectra between channels. We have developed a novel matrix mediation approach that leverages a nuclear norm regularization to determine the matrix-valued regression parameters. Furthermore, we introduced a global test for the overall CST mediation and a test to determine specific channels and frequencies driving the mediation. We validated the method through simulations and applied it to our well-studied 50+-year Barbados Nutrition Study dataset by comparing EEGs collected in school-age children (5-11 years) who were malnourished in the first year of life with those of healthy classmate controls. We hypothesized that the CST mediates the effect of malnutrition on cognitive performance. We can now explicitly pinpoint the frequencies (delta, theta, alpha, and beta bands) and regions (frontal, central, and occipital) in which functional connectivity was altered in previously malnourished children, an improvement to prior studies. Understanding the specific networks impacted by a history of postnatal malnutrition could pave the way for developing more targeted and personalized therapeutic interventions. Our methods offer a versatile framework applicable to mediation studies encompassing matrix and Hermitian 3D tensor mediators alongside scalar exposures and outcomes, facilitating comprehensive analyses across diverse research domains.

Complete mitochondrial genome of the introduced Indian walking stick Carausius morosus (Lonchodidae, Insecta) from California.

We present the complete mitochondrial genome of Carausius morosus from Salinas, CA. The mitochondrial genome of C. morosus is circular, AT rich (78.1%), and 16,671 bp in length. It consists of 13 protein-coding, 22 transfer RNA, and 2 ribosomal RNA genes and is identical in gene content to Carausius sp.

Dissemination of antimicrobial resistance in agricultural ecosystems following irrigation with treated municipal wastewater.

The spread of antimicrobial resistance (AMR) in agricultural systems via irrigation water is a serious public health issue as it can be transmitted to humans through the food chain. Therefore, understanding the dissemination routes of antibiotic resistance genes (ARGs) in agricultural systems is crucial for the assessment of health risks associated with eating fresh vegetables such as spinach and radish irrigated with treated municipal wastewater (TMW). In this study, we investigated the bacterial community structure and resistome in the soil-plant-earthworm continuum after irrigation of spinach and radish with TMW containing the antibiotics trimethoprim (TMP), sulfamethoxazole (SMZ), and sulfapyridine (SPD) using 16S rRNA gene sequencing and high throughput quantitative PCR (HT-qPCR). The study was conducted in two phases: Phase I involved eight weeks of spinach and radish production using TMW for irrigation, whereas Phase II entailed three weeks of earthworm exposure to contaminated plant material obtained in Phase I. The 16S data indicated that the rhizosphere bacterial community composition and structure were more resilient to antibiotic residuals in the irrigated water, with radish showing less susceptibility than spinach than those of bulk soils. The HT-qPCR analysis revealed that a total of 271 ARGs (out of 285) and 9 mobile genetic elements (MGEs) (out of 10) were detected in all samples. Higher diversity and abundance of ARGs were observed for samples irrigated with higher concentrations of antibiotics in both spinach and radish treatments. However, compared to spinach, radish ARG dynamics in the soil biome were more stable due to the change of antibiotic introduction to the soil. At the class level, multi-drug resistance (MDR) class was altered significantly by the presence of antibiotics in irrigation water. Compared to earthworm fecal samples, their corresponding soil environments showed a higher number of detected ARGs, suggesting that earthworms could play a role in reducing ARG dissemination in the soil environments. These findings will not only provide insight into the dissemination of ARGs in agricultural environments due to antibiotic residuals in irrigated water but could help understand the potential human health risks associated with ARGs.

MultiToxPred 1.0: a novel comprehensive tool for predicting 27 classes of protein toxins using an ensemble machine learning approach.

Protein toxins are defense mechanisms and adaptations found in various organisms and microorganisms, and their use in scientific research as therapeutic candidates is gaining relevance due to their effectiveness and specificity against cellular targets. However, discovering these toxins is time-consuming and expensive. In silico tools, particularly those based on machine learning and deep learning, have emerged as valuable resources to address this challenge. Existing tools primarily focus on binary classification, determining whether a protein is a toxin or not, and occasionally identifying specific types of toxins. For the first time, we propose a novel approach capable of classifying protein toxins into 27 distinct categories based on their mode of action within cells. To accomplish this, we assessed multiple machine learning techniques and found that an ensemble model incorporating the Light Gradient Boosting Machine and Quadratic Discriminant Analysis algorithms exhibited the best performance. During the tenfold cross-validation on the training dataset, our model exhibited notable metrics: 0.840 accuracy, 0.827 F1 score, 0.836 precision, 0.840 sensitivity, and 0.989 AUC. In the testing stage, using an independent dataset, the model achieved 0.846 accuracy, 0.838 F1 score, 0.847 precision, 0.849 sensitivity, and 0.991 AUC. These results present a powerful next-generation tool called MultiToxPred 1.0, accessible through a web application. We believe that MultiToxPred 1.0 has the potential to become an indispensable resource for researchers, facilitating the efficient identification of protein toxins. By leveraging this tool, scientists can accelerate their search for these toxins and advance their understanding of their therapeutic potential.

Polytomous Rasch Analyses of Surgeons' Decision-Making on Choice of Procedure in Endoscopic Lumbar Spinal Stenosis Decompression Surgeries.

BACKGROUND: With the growing prevalence of lumbar spinal stenosis, endoscopic surgery, which incorporates techniques such as transforaminal, interlaminar, and unilateral biportal (UBE) endoscopy, is increasingly considered. However, the patient selection criteria are debated among spine surgeons. OBJECTIVE: This study used a polytomous Rasch analysis to evaluate the factors influencing surgeon decision-making in selecting patients for endoscopic surgical treatment of lumbar spinal stenosis. METHODS: A comprehensive survey was distributed to a representative sample of 296 spine surgeons. Questions encompassed various patient-related and clinical factors, and responses were captured on a logit scale graphically displaying person-item maps and category probability curves for each test item. Using a Rasch analysis, the data were subsequently analyzed to determine the latent traits influencing decision-making. RESULTS: The Rasch analysis revealed that surgeons' preferences for transforaminal, interlaminar, and UBE techniques were easily influenced by comfort level and experience with the endoscopic procedure and patient-related factors. Harder-to-agree items included technological aspects, favorable clinical outcomes, and postoperative functional recovery and rehabilitation. Descriptive statistics suggested interlaminar as the best endoscopic spinal stenosis decompression technique. However, logit person-item analysis integral to the Rasch methodology showed highest intensity for transforaminal followed by interlaminar endoscopic lumbar stenosis decompression. The UBE technique was the hardest to agree on with a disordered person-item analysis and thresholds in category probability curve plots. CONCLUSION: Surgeon decision-making in selecting patients for endoscopic surgery for lumbar spinal stenosis is multifaceted. While the framework of clinical guidelines remains paramount, on-the-ground experience-based factors significantly influence surgeons' selection of patients for endoscopic lumbar spinal stenosis surgeries. The Rasch methodology allows for a more granular psychometric evaluation of surgeon decision-making and accounts better for years-long experience that may be lost in standardized clinical guideline development. This new approach to assessing spine surgeons' thought processes may improve the implementation of evidence-based protocol change dictated by technological advances was endorsed by the Interamerican Society for Minimally Invasive Spine Surgery (SICCMI), the International Society for Minimal Intervention in Spinal Surgery (ISMISS), the Mexican Spine Society (AMCICO), the Brazilian Spine Society (SBC), the Society for Minimally Invasive Spine Surgery (SMISS), the Korean Minimally Invasive Spine Society (KOMISS), and the International Society for the Advancement of Spine Surgery (ISASS).

CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics.

We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.

Predictive coding with spiking neurons and feedforward gist signaling.

Predictive coding (PC) is an influential theory in neuroscience, which suggests the existence of a cortical architecture that is constantly generating and updating predictive representations of sensory inputs. Owing to its hierarchical and generative nature, PC has inspired many computational models of perception in the literature. However, the biological plausibility of existing models has not been sufficiently explored due to their use of artificial neurons that approximate neural activity with firing rates in the continuous time domain and propagate signals synchronously. Therefore, we developed a spiking neural network for predictive coding (SNN-PC), in which neurons communicate using event-driven and asynchronous spikes. Adopting the hierarchical structure and Hebbian learning algorithms from previous PC neural network models, SNN-PC introduces two novel features: (1) a fast feedforward sweep from the input to higher areas, which generates a spatially reduced and abstract representation of input (i.e., a neural code for the gist of a scene) and provides a neurobiological alternative to an arbitrary choice of priors; and (2) a separation of positive and negative error-computing neurons, which counters the biological implausibility of a bi-directional error neuron with a very high baseline firing rate. After training with the MNIST handwritten digit dataset, SNN-PC developed hierarchical internal representations and was able to reconstruct samples it had not seen during training. SNN-PC suggests biologically plausible mechanisms by which the brain may perform perceptual inference and learning in an unsupervised manner. In addition, it may be used in neuromorphic applications that can utilize its energy-efficient, event-driven, local learning, and parallel information processing nature.

Recycling Polyethylene/Polyamide Multilayer Films with Poly(isoprene-g-Maleic Anhydride) Compatibilizer.

Polymers generally form incompatible mixtures that make the process of recycling difficult, especially the mechanical recycling of mixed plastic waste. One of the most commonly used films in the packaging industry is multilayer films, mainly composed of polyethylene (PE) and polyamide (PA). Recycling these materials with such different molecular structures requires the use of compatibilizers to minimize phase separation and obtain more useful recycled materials. In this work, commercial polyisoprene-graft-maleic anhydride (PI-g-MA) was tested as a compatibilizer for a blend of PE and PA derived from the mechanical recycling of PE/PA multilayer films. Different amounts of PI-g-MA were tested, and the films made with 1.5% PI-g-MA showed the best results in terms of mechanical properties and dart impact. The films were also characterized thermally via thermogravimetric analysis (TG) and differential scanning calorimetry (DSC), using Fourier-transform infrared spectroscopy (FTIR), and morphologically using a scanning electron microscope (SEM). Other parameters, such as tearing and perforation, were analyzed.

Development of a dry powder insufflation device with application in in vitro cell-based assays in the context of respiratory delivery.

Research on pharmaceutical dry powders has been increasing worldwide, along with increased therapeutic strategies for an application through the pulmonary or the nasal routes. In vitro methodologies and tests that mimic the respiratory environment and the process of inhalation itself are, thus, essential. The literature frequently reports cell-based in vitro assays that involve testing the dry powders in suspension. This experimental setting is not adequate, as both the lung and the nasal cavity are devoid of abundant liquid. However, devices that permit powder insufflation over cells in culture are either scarce or technically complex and expensive, which is not feasible in early stages of research. In this context, this work proposes the development of a device that allows the delivery of dry powders onto cell surfaces, thus simulating inhalation more appropriately. Subsequently, a quartz crystal microbalance (QCM) was used to establish a technique enabling the determination of dry powder deposition profiles. Additionally, the determination of the viability of respiratory cells (A549) after the insufflation of a dry powder using the developed device was performed. In all, a prototype for dry powder insufflation was designed and developed, using 3D printing methods for its production. It allowed the homogenous dispersion of the insufflated powders over a petri dish and a QCM crystal, and a more detailed study on how dry powders disperse over the supports. The device, already protected by a patent, still requires further improvement, especially regarding the method for powder weighing and the efficiency of the insufflation process, which is being addressed. The impact of insufflation of air and of locust bean gum (LBG)-based microparticles revealed absence of cytotoxic effect, as cell viability roughly above 70 % was always determined.

Electrochemically Mediated Atom Transfer Radical Polymerization Driven by Alternating Current.

Alternating current (AC) and pulsed electrolysis are gaining traction in electro(organic) synthesis due to their advantageous characteristics. We employed AC electrolysis in electrochemically mediated Atom Transfer Radical Polymerization (eATRP) to facilitate the regeneration of the activator CuI complex on Cu0 electrodes. Additionally, Cu0 served as a slow supplemental activator and reducing agent (SARA ATRP), enabling the activation of alkyl halides and the regeneration of the CuI activator through a comproportionation reaction. We harnessed the distinct properties of Cu0 dual regeneration, both chemical and electrochemical, by employing sinusoidal, triangular, and square-wave AC electrolysis alongside some of the most active ATRP catalysts available. Compared to linear waveform (DC electrolysis) or SARA ATRP (without electrolysis), pulsed and AC electrolysis facilitated slightly faster and more controlled polymerizations of acrylates. The same AC electrolysis conditions could successfully polymerize eleven different monomers across different mediums, from water to bulk. Moreover, it proved effective across a spectrum of catalyst activity, from low-activity Cu/2,2-bipyridine to highly active Cu complexes with substituted tripodal amine ligands. Chain extension experiments confirmed the high chain-end fidelity of the produced polymers, yielding functional and high molecular-weight block copolymers. SEM analysis indicated the robustness of the Cu0 electrodes, sustaining at least 15 consecutive polymerizations.

A Targeted and an Untargeted Metabolomics Approach to Study the Phytochemicals of Tomato Cultivars Grown Under Different Salinity Conditions.

In this study, we evaluated the effect of increasing the salinity of irrigation water on the metabolic content and profiles of two tomato cultivars ('Jaune Flamme' (JF) and 'Red Pear' (RP)) using targeted and untargeted metabolomics approaches. Irrigation of tomato plants was performed with four different salt concentrations provided by chloride (treatment 1) and sulfate (treatment 2) salts. Targeted analysis of the methanolic extract resulted in the identification of nine major polyphenols. Among them, chlorogenic acid, rutin, and naringenin were the prominent compounds in both cultivars. In addition, the quantification of 18 free amino acids from both tomato cultivars showed that different salinity treatments significantly enhanced the levels of glutamine, glutamic acid, and γ-aminobutyric acid (GABA). Using the untargeted metabolomic approach, we identified 129 putative metabolites encompassing a diverse array of phytochemicals including polyphenols, organic acids, lipids, sugars, and amino acids. Principal component analysis (PCA) of mass spectral data acquired under positive and negative ionization modes showed a clear separation between the two cultivars. However, only positive ionization showed separation among different salinity treatments. Unsupervised and supervised learning algorithms were applied to mine the generated data and to pinpoint metabolites different from the two cultivars. These findings suggest that different salinity conditions significantly influenced the accumulation of phytochemicals in tomato cultivars. This study will help tomato breeding programs to develop value-added tomato cultivars under varying environmental conditions.

The biotechnology revolution in textile dyeing.

Biotechnology holds the potential to revolutionize textile dyeing by utilizing biopigments, biodegradable dyes, and fermentative dyeing methods as alternatives to synthetic options. While some challenges exist, these biotechnological approaches offer innovative solutions to minimize environmental impact and foster sustainable practices, leading toward a greener, circular and efficient textile bioindustry.