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Organophosphate pesticides (OPPs) are widely prevalent in the environment primarily due to their low cost and extensive use in agricultural lands. However, it is estimated that only about 5% of these applied pesticides reach their intended target organisms. The remaining 95% residue linger in the environment as contaminants, posing significant ecological and health risks. This underscores the need for materials capable of effectively removing, recovering, and recycling these contaminants through adsorption processes. In this research, adsorbent materials composed of electro-spun carbon nanofibers (ECNFs) derived from polyacrylonitrile was developed. The materials were characterized through several techniques, including scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), Fourier Transform Infrared Spectroscopy (FTIR), Brunauer-Emmett-Teller (BET) analysis, and contact angle measurements. SEM analysis revealed details of the structural properties and inter-fiber spacing variations of the carbon nanofibers. The results revealed that ECNFs possess remarkable uniformity, active surface areas, and high efficiency for adsorption processes. The adsorption studies were conducted using batch experiments with ethion pesticide in aqueous solution. High-Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) was utilized to quantify the concentrations of the OPP. Various parameters, including adsorbent dosage, pH, contact time, and initial ethion concentration, were investigated to understand their impact on the adsorption process. The adsorption isotherm was best described by the Freundlich model, while the kinetics of adsorption followed a non-integer-order kinetics model. The adsorption capacity of the ECNFs for OPP removal highlights a significant advancement in materials designed for environmental remediation applications. This study demonstrates the potential of ECNFs to serve as effective adsorbents, contributing to the mitigation of pesticide contamination in agricultural environments.

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The development of drug resistance is a nearly universal phenomenon in patients with glioblastoma multiforme (GBM) brain tumors. Upon treatment, GBM cancer cells may initially undergo a drug-induced cell-state change to a drug-tolerant, slow-cycling state. The kinetics of that process are not well understood, in part due to the heterogeneity of GBM tumors and tumor models, which can confound the interpretation of kinetic data. Here, we resolve drug-adaptation kinetics in a patient-derived in vitro GBM tumor model characterized by the epithelial growth factor receptor (EGFR) variant(v)III oncogene treated with an EGFR inhibitor. We use radiolabeled 18F-fluorodeoxyglucose (FDG) to monitor the glucose uptake trajectories of single GBM cancer cells over a 12 h period of drug treatment. Autocorrelation analysis of the single-cell glucose uptake trajectories reveals evidence of a drug-induced cell-state change from a high- to low-glycolytic phenotype after 5-7 h of drug treatment. Information theoretic analysis of a bulk transcriptome kinetic series of the GBM tumor model delineated the underlying molecular mechanisms driving the cellular state change, including a shift from a stem-like mesenchymal state to a more differentiated, slow-cycling astrocyte-like state. Our results demonstrate that complex drug-induced cancer cell-state changes of cancer cells can be captured via measurements of single cell metabolic trajectories and reveal the extremely facile nature of drug adaptation.

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The 2023 wildfire season in Canada was unprecedented in its scale and intensity, spanning from mid-April to late October and across much of the forested regions of Canada. Here, we summarize the main causes and impacts of this exceptional season. The record-breaking total area burned (~15 Mha) can be attributed to several environmental factors that converged early in the season: early snowmelt, multiannual drought conditions in western Canada, and the rapid transition to drought in eastern Canada. Anthropogenic climate change enabled sustained extreme fire weather conditions, as the mean May-October temperature over Canada in 2023 was 2.2 °C warmer than the 1991-2020 average. The impacts were profound with more than 200 communities evacuated, millions exposed to hazardous air quality from smoke, and unmatched demands on fire-fighting resources. The 2023 wildfire season in Canada not only set new records, but highlights the increasing challenges posed by wildfires in Canada.

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We report a methodology for averaging quantum photoexcitation vibronic dynamics over the initial orientations of the molecules with respect to an ultrashort light pulse. We use singular value decomposition of the ensemble density matrix of the excited molecules, which allows the identification of the few dominant principal molecular orientations with respect to the polarization direction of the electric field. The principal orientations provide insights into the specific stereodynamics of the corresponding principal molecular vibronic states. The massive compaction of the vibronic density matrix of the ensemble of randomly oriented pumped molecules enables a most efficient fully quantum mechanical time propagation scheme. Two examples are discussed for the quantum dynamics of the LiH molecule in the manifolds of its electronically excited Σ and Π states. Our results show that electronic and vibrational coherences between excited states of the same symmetry are resilient to averaging over an ensemble of molecular orientations and can be selectively excited at the ensemble level by tuning the pulse parameters.

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Microorganisms encode proteins that function in the transformations of useful and harmful nitrogenous compounds in the global nitrogen cycle. The major transformations in the nitrogen cycle are nitrogen fixation, nitrification, denitrification, anaerobic ammonium oxidation, and ammonification. The focus of this report is the complex biogeochemical process of denitrification, which, in the complete form, consists of a series of four enzyme-catalyzed reduction reactions that transforms nitrate to nitrogen gas. Denitrification is a microbial strain-level ecological trait (characteristic), and denitrification potential (functional performance) can be inferred from trait rules that rely on the presence or absence of genes for denitrifying enzymes in microbial genomes. Despite the global significance of denitrification and associated large-scale genomic and scholarly data sources, there is lack of datasets and interactive computational tools for investigating microbial genomes according to denitrification trait rules. Therefore, our goal is to categorize archaeal and bacterial genomes by denitrification potential based on denitrification traits defined by rules of enzyme involvement in the denitrification reduction steps. We report the integration of datasets on genome, taxonomic lineage, ecosystem, and denitrifying enzymes to provide data investigations context for the denitrification potential of microbial strains. We constructed an ecosystem and taxonomic annotated denitrification potential dataset of 62,624 microbial genomes (866 archaea and 61,758 bacteria) that encode at least one of the twelve denitrifying enzymes in the four-step canonical denitrification pathway. Our four-digit binary-coding scheme categorized the microbial genomes to one of sixteen denitrification traits including complete denitrification traits assigned to 3280 genomes from 260 bacteria genera. The bacterial strains with complete denitrification potential pattern included Arcobacteraceae strains isolated or detected in diverse ecosystems including aquatic, human, plant, and Mollusca (shellfish). The dataset on microbial denitrification potential and associated interactive data investigations tools can serve as research resources for understanding the biochemical, molecular, and physiological aspects of microbial denitrification, among others. The microbial denitrification data resources produced in our research can also be useful for identifying microbial strains for synthetic denitrifying communities.

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Herein, we present a novel esterase enzyme, Ade1, isolated from a metagenomic library of Amazonian dark earths soils, demonstrating its broad substrate promiscuity by hydrolyzing ester bonds linked to aliphatic groups. The three-dimensional structure of the enzyme was solved in the presence and absence of substrate (tributyrin), revealing its classification within the α/ß-hydrolase superfamily. Despite being a monomeric enzyme, enzymatic assays reveal a cooperative behavior with a sigmoidal profile (initial velocities vs substrate concentrations). Our investigation brings to light the allokairy/hysteresis behavior of Ade1, as evidenced by a transient burst profile during the hydrolysis of substrates such as p-nitrophenyl butyrate and p-nitrophenyl octanoate. Crystal structures of Ade1, coupled with molecular dynamics simulations, unveil the existence of multiple conformational structures within a single molecular state (E̅1). Notably, substrate binding induces a loop closure that traps the substrate in the catalytic site. Upon product release, the cap domain opens simultaneously with structural changes, transitioning the enzyme to a new molecular state (E̅2). This study advances our understanding of hysteresis/allokairy mechanisms, a temporal regulation that appears more pervasive than previously acknowledged and extends its presence to metabolic enzymes. These findings also hold potential implications for addressing human diseases associated with metabolic dysregulation.

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In this study, an easy and low-cost production method for a cellulose acetate-based gel polymer containing lithium perchlorate and propylene carbonate is described, as well as the investigation of its properties for potential use as an electrolyte in electrochemical devices. Cellulose acetate, a biopolymer derived from natural matrix, is colourless and transparent, as confirmed by the UV-Vis spectroscopy, with 85 % transparency in visible spectrum. The gels were prepared and tested at different concentrations and proportions to optimise their properties. Thermogravimetry, XRD, and FTIR analyses revealed crucial characteristics, including a substantial 90 % mass loss between 150 and 250 °C, a semi-crystalline nature with complete salt dissociation within the polymer matrix, and a decrease in intensity at 1780 cm-1 with increasing Li+ ion concentration, suggesting an improvement in ionic conduction capacity. In terms of electrochemical performance, the gel containing 10 % by mass of cellulose acetate and 1.4 M of LiClO4 emerged as the most promising. It exhibited a conductivity of 2.3 × 10-4 S.cm-1 at 25 °C and 3.0 × 10-4 S.cm-1 at 80 °C. Additionally, it demonstrated an ideal shape of cyclic voltammetry curves and stability after 400 cycles, establishing its suitability as an electrolyte in electrochemical devices.

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In bodybuilders' diets, protein plays a crucial role in supporting muscle growth and repairing damaged muscle tissue. These individuals meet their protein needs by combining dietary sources with supplements. Animal-based proteins are often preferred over plant-based proteins because they are believed to better support muscle protein synthesis. This review explores the meat consumption patterns of bodybuilders and high-level meat consumers, focusing on rabbit, beef, chicken, turkey, and lamb. We describe and compare the types of meat bodybuilders commonly consume and provide an overview of protein supplements, including meat-based options, plant-based alternatives, and whey-based products. Our aim is to gain insight into the dietary preferences of bodybuilders and high-level meat consumers, considering their nutritional requirements and the potential effect on the meat industry. We conducted an extensive search across various databases, including Scopus, Web of Science, PubMed, and Google Scholar. We found that individual choices vary based on factors such as attitudes, trust, taste, texture, nutritional content, ethical considerations, and cultural influences. Nutritional factors, including protein content, amino acid profiles, and fat levels, significantly influence the preferences of bodybuilders and high-level meat consumers. However, it is crucial to maintain a balance by incorporating other essential nutrients such as carbohydrates, healthy fats, vitamins, and minerals to ensure a complete and balanced diet. The findings from this review can inform strategies and product development initiatives tailored to the needs of bodybuilders and discerning meat enthusiasts.

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Despite being recognized primarily as an analytical technique, mass spectrometry also has a large potential as a synthetic tool, enabling access to advanced synthetic routes by reactions in charged microdroplets or ionic thin layers. Such reactions are special and proceed primarily at surfaces of droplets and thin layers. Partial solvation of the reactants is usually considered to play an important role for reducing the activation barrier, but many mechanistic details still need to be clarified. In our study, we showcase the synergy between two sequentially applied "preparative mass spectrometry" methods: initiating accelerated reactions within microdroplets during electrospray ionization to generate gaseous ionic intermediates in high abundance, which are subsequently mass-selected and soft-landed to react with a provided reagent on a substrate. This allows the generation of products at a nanomolar scale, amenable to further characterization. In this proof-of-concept study, the contrasting reaction pathways between intrinsically neutral and pre-charged reagents, respectively, both in microdroplets and in layers generated by ion soft-landing are investigated. This provides new insights into the role of partially solvated reagents at microdroplet surfaces for increased reaction rates. Additionally, further insights into reactions of ions of the same polarity under various conditions is obtained.

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Rivers in Southeast Brazil are essential as sources of drinking water, energy production, irrigation, and industrial processes. The Piracicaba, Capivari, and Jundiaí rivers basin, known as the PCJ basin, comprises major cities, industrial hubs, and large agricultural areas, which have impacted the water quality in the region. Emerging contaminants such as pesticides, hormones, pharmaceuticals, industrial chemicals, and per- and polyfluoroalkyl substances (PFAS) are likely to be released into the rivers in the PCJ basin; however, the current Brazilian legislation does not require monitoring of most of these chemicals. Thus, the extent of emerging contaminants pollution and their risks to aquatic and human life in the basin are largely unknown. In this study, we investigated the occurrence of several pesticides, hormones, pharmaceuticals, and personal care products in 15 sampling points across the PCJ basin, while industrial chemicals and PFAS were assessed in 11 sampling points. The results show that agriculture and industrial activities are indeed causing the pollution of most rivers. Multivariate analysis indicates that some sampling points, such as Jundiaí, Capivari, and Piracicaba rivers, are largely impacted by pesticides used in agriculture. In addition, to the best of our knowledge, this is the first study reporting the presence of PFAS in rivers in São Paulo, the most populous state in Brazil. Four out of eight species of PFAS assessed in our study were detected in at least 5 sampling points at concentrations ranging from 2.0 to 50.0 ng L-1. The preliminary risk assessment indicates that various pesticides, caffeine, industrial chemicals, and PFAS were present at concentrations that could threaten aquatic life. Notably, risk quotients of 414, 340, and 178 were obtained for diuron, atrazine, and imidacloprid, respectively, in the Jundiaí River. Our study suggests that establishing a comprehensive monitoring program is needed to ensure the protection of aquatic life and human health.

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Electronic coherence signatures can be directly identified in the time-frequency maps measured in two-dimensional electronic spectroscopy (2DES). Here, we demonstrate the theory and discuss the advantages of this approach via the detailed application to the fast-femtosecond beatings of a wide variety of electronic coherences in ensemble dimers of quantum dots (QDs), assembled from QDs of 3 nm in diameter, with 8% size dispersion in diameter. The observed and computed results can be consistently characterized directly in the time-frequency domain by probing the polarization in the 2DES setup. The experimental and computed time-frequency maps are found in very good agreement, and several electronic coherences are characterized at room temperature in solution, before the extensive dephasing due to the size dispersion begins. As compared to the frequency-frequency maps that are commonly used in 2DES, the time-frequency maps allow exploiting electronic coherences without additional post-processing and with fewer 2DES measurements. Towards quantum technology applications, we also report on the modeling of the time-frequency photocurrent response of these electronic coherences, which paves the way to integrating QD devices with classical architectures, thereby enhancing the quantum advantage of such technologies for parallel information processing at room temperature.

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Following a single photon VUV absorption, the N2 molecule dissociates into distinct channels leading to N atoms of different reactivities. The optically accessible singlets are bound, and dissociation occurs through spin-orbit induced transfer to the triplets. There is a forest of coupled electronic states, and we here aim to trace a path along the nonadiabatic couplings toward a particular exit channel. To achieve this, we apply a time-reversed quantum dynamical approach that corresponds to a dissociation running back. It begins with an atom-atom relative motion in a particular product channel. Starting with a Gaussian wave packet at the dissociation region of N2 and propagating it backward in time, one can see the population transferring among the triplets due to a strong nonadiabatic interaction between these states. Simultaneously, the optically active singlets get populated because of spin-orbit coupling to the triplets. Thus, backward propagation traces the nonradiative association of nitrogen atoms.

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Precise, efficient, and effective control of chemical reaction conditions is a viable measure for the environment-conscious time and energy resource management in modern laboratories and in industry. Parameter changes such as surface enlargement, pH, local reactant accumulation by solvent evaporation and polarization effects, etc., have been shown to greatly affect the reaction rate of a chemical reaction. In electrospray (ES) ionization - a soft ionization method often used for mass spectrometry - all these parameters change constantly and with high dynamics during the nebulization process that generates droplets as the ultimate confined µ-reaction vessels. Therefore, high acceleration factors are reported in literature for a manifold of such µ-droplet reactions. Here, the tri-molecular Mannich reaction was identified as a suitable candidate for studying thermal, electronic, and fluidic manipulation of the ES process to achieve high conversion rates with short reaction times and compare them to the batch reaction. Some of these manipulations were conducted separately to better quantify their individual contributions. Here, the keto-enol-tautomerism of the used ß-diketones, the high proton concentrations, and the longer reaction times in the µ-droplets are presumed to have the greatest impact on these enhancement factors. Experiments were performed to find ES conditions with small initial droplets and long droplet flight times where the highest reaction conversion rates are obtained. A sharp increase in the product peak was found at large distances between the mass spectrometry (MS) inlet and ES source at high voltages. Moreover, different trends were found for the two ketones studied, acetylacetone (AcAc) and 1,3-cyclohexanedione (Cyclo), by changing the temperature of the heated ES source. Finally, high conversion rates were obtained for the combination of formaldehyde (Fal) and piperidine (Pip) with AcAc and Cyclo, respectively, with over 90%. With respect to the batch reaction, this is mainly due to an increase in reaction kinetics as well as a shift in thermodynamics for the µ-droplet reaction environment.

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Multi-state electronic dynamics at higher excitation energies is needed for the understanding of a variety of energy rich situations, including chemistry under extreme conditions, vacuum ultraviolet (VUV) induced astrochemistry, and attochemistry. It calls for an understanding of three stages, energy acquisition, dynamical propagation, and disposal. It is typically not possible to identify a basis of uncoupled quantum states that is sufficient for the three stages. The handicap is the large number of coupled quantum states that is needed to describe the system. Progress in quantum chemistry provides the necessary background to the energetics and the coupling. Progress in quantum dynamics takes this as input for the propagation in time. Right now, it seems that we have come of age with potential detailed applications. We here report a demonstration to a coupled electron-nuclear quantum dynamics through a maze of 47 electronic states and with attention to the order in perturbation theory that is indicated using propensity rules for couplings. Close agreement with experimental results for the VUV photodissociation of 14N2 and its isotopomer 14N15N is achieved. We pay special attention to the coupling between two dissociative continua and an optically accessible bound domain. The computations reproduce and interpret the non-monotonic branching between the two exit channels producing N(2D) and N(2P) atoms as a function of excitation energy and its variation with the mass.

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The Hamiltonian of a quantum system governs the dynamics of the system via the Schrodinger equation. In this paper, the Hamiltonian is reconstructed in the Pauli basis using measurables on random states forming a time series data set. The time propagation is implemented through Trotterization and optimized variationally with gradients computed on the quantum circuit. We validate our output by reproducing the dynamics of unseen observables on a randomly chosen state not used for the optimization. Unlike existing techniques that try and exploit the structure/properties of the Hamiltonian, our scheme is general and provides freedom with regard to what observables or initial states can be used while still remaining efficient with regard to implementation. We extend our protocol to doing quantum state learning where we solve the reverse problem of doing state learning given time series data of observables generated against several Hamiltonian dynamics. We show results on Hamiltonians involving XX, ZZ couplings along with transverse field Ising Hamiltonians and propose an analytical method for the learning of Hamiltonians consisting of generators of the SU(3) group. This paper is likely to pave the way toward using Hamiltonian learning for time series prediction within the context of quantum machine learning algorithms.

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Global demand for crops will continue increasing over the next few decades to cover both food and biofuel needs. This demand will put further pressure to expand arable land and replace natural habitats. However, we are only beginning to understand the combined effects of agrochemicals and land-use change on tropical freshwater biodiversity. In this study, we analyzed how pond-dwelling anuran larvae responded to pond characteristics, landscape composition, and agrochemical contamination in a sugarcane-dominated agroecosystem in Brazil. Then we used an information theoretical approach with generalized linear models to relate species richness and abundance to predictor variables. The variation in tadpole abundance was associated with both agrochemical concentration (e.g., ametryn, diuron, and malathion) and landscape variables (e.g., percentage of forest, percentage of agriculture, and distance to closest forest). The relationship between species abundance and agrochemicals was species-specific. For example, the abundances of Scinax fuscovarius and Physalaemus nattereri were negatively associated with ametryn, and Dendropsophus nanus was negatively associated with tebuthiuron, whereas that of Leptodactylus fuscus was positively associated with malathion. Conversely, species richness was associated with distance to forest fragments and aquatic vegetation heterogeneity, but not agrochemicals. Although we were unable to assign a specific mechanism to the variation in tadpole abundance based on field observations, the lower abundance of three species in ponds with high concentrations of agrochemicals suggest they negatively impact some frog species inhabiting agroecosystems. We recommend conserving ponds near forest fragments, with abundant stratified vegetation, and far from agrochemical runoffs to safeguard more sensitive pond-breeding species.

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Dysfunction of the adipose tissue metabolism is considered as a significant hallmark of aging. It has been proposed that α-ß hydrolase domain containing 5 (ABHD5) plays a critical role in the control of lipolysis. However, the role of ABHD5 in the control of lipolysis during aging or exercise is unknown. Here we combined the experimental mouse model with transcriptomic analyzes by using murine and human databases to explore the role of ABHD5 in the adipose tissue during aging and in response to exercise. Transcriptomic data revealed a downregulation of Abhd5 messenger RNA levels in the subcutaneous white adipose tissue (scWAT) over time in individuals from 20 to 69 years old. Aged mice displayed dramatic reduction of ABHD5 protein content and lipolytic-related proteins in the scWAT. Interestingly, 4 weeks of high-intensity interval training increased ABHD5 protein level and restored the lipolytic pathway in the scWAT of aged mice. Altogether, our findings demonstrated that aging affects ABHD5 content in the adipose tissue of mice and humans. Conversely, exercise increases ABHD5 activity, recovering the lipolytic activity in aged mice.

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Quantum state tomography is an integral part of quantum computation and offers the starting point for the validation of various quantum devices. One of the central tasks in the field of state tomography is to reconstruct, with high fidelity, the quantum states of a quantum system. From an experiment on a real quantum device, one can obtain the mean measurement values of different operators. With such data as input, in this report we employ the maximal entropy formalism to construct the least biased mixed quantum state that is consistent with the given set of expectation values. Even though, in principle, the reported formalism is quite general and should work for an arbitrary set of observables, in practice we shall demonstrate the efficacy of the algorithm on an informationally complete (IC) set of Hermitian operators. Such a set possesses the advantage of uniquely specifying a single quantum state from which the experimental measurements have been sampled and hence renders the rare opportunity not only to construct a least-biased quantum state but even replicate the exact state prepared experimentally within a preset tolerance. The primary workhorse of the algorithm is reconstructing an energy function which we designate as the effective Hamiltonian of the system, and parameterizing it with Lagrange multipliers, according to the formalism of maximal entropy. These parameters are thereafter optimized variationally so that the reconstructed quantum state of the system converges to the true quantum state within an error threshold. To this end, we employ a parameterized quantum circuit and a hybrid quantum-classical variational algorithm to obtain such a target state, making our recipe easily implementable on a near-term quantum device.

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In this study, we developed and optimized a growth medium using various nitrogen sources for the cultivation of Lactobacillus delbrueckii ssp. bulgaricus, a probiotic and essential dairy starter culture. The composition of de Man, Rogosa, and Sharpe (MRS) culture medium was modified, and the nitrogen content was replaced by alternative nitrogen sources X-Seed Nucleo Max, X-Seed KAT, and X-Seed Carbo Max (Ohly GmbH) in various blends of 5 and 10 g/L. Results showed that bacterial growth was significantly higher when the nitrogen source blend of 10 g/L of KAT and 10 g/L of Carbo Max [KCMax (10/10)] was used. The optical densities of the Lb. bulgaricus strains were significantly higher in the KCMax (10/10) medium than in the MRS medium. There was no significance in bacterial counts for both the MRS and the KCMax (10/10) medium, and all bacterial counts were estimated at 8 log cfu/mL. The buffering capacity of the KCMax (10/10) medium was also tested and supplemented with l-histidine and was significantly higher than that of the MRS control medium. KCMax (10/10) also supported the freeze-stability and viability of the Lb.bulgaricus cells during freezing and freeze-drying operations. Our results suggest that the alternative nitrogen sources X-Seed Nucleo Max, X-Seed KAT and X-Seed Carbo Max can substantially support the growth of lactic acid bacteria as demonstrated with Lb. bulgaricus. These alternative nitrogen sources could thus be recommended for lactic acid bacteria fermentation and for the cultivation of dairy starter cultures.

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Lactic acid bacteria (LAB) are essential dairy starter cultures that are significantly employed for the manufacture of fermented dairy products such as yogurt and cheese. LAB predominantly produce lactic acid as a major end product of fermentation, and they synthesize important metabolites that impart the organoleptic characteristics of fermented food products. LAB are fastidious bacteria that thrive in many environments when adequate nutritional requirements are fulfilled. The demand for superior LAB dairy starter cultures for fermentation applications in the food and dairy industry, has resulted in the need to provide viable and active cultures for all bioprocessing operations. The development of a standard protocol for ensuring the viability and enhanced functionality of LAB cultures in the laboratory as well as dairy processing environments is thus very critical. In addressing concerns linked to resuscitating weak, stressed, and injured LAB culture cells, a protocol that vividly outlines salient steps to recover, enhance cell regeneration, and improve metabolic functionality of LAB strains is of the utmost importance. The maintenance of culture purity, functionality, and viability for LAB starter cultures is likewise critical. Therefore, adherence to a unique protocol guideline will result in the promotion of fermentation performance for many LAB strains dedicated to fermentation and biotechnology processes. As a result, the Food Microbiology and Biotechnology Laboratory at North Carolina Agriculture and Technical State University has developed a standard protocol for the activation and quality control of selected LAB strains that has resulted in highly functional and viable LAB culture strains employed for fermentation research. The adaptation and recommendation of a protocol such as this for use in the dairy and food industry will help to ensure LAB viability and functionality for many applications.

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