Guadalupe Virginia Nevárez-Moorillón

Prebiotic potential refers to the stimulation of beneficial bacteria over pathogenic strains. This preliminary study evaluated the prebiotic potential of five agave-derived carbohydrate preparations using lactic acid bacteria (LAB) and Escherichia coli (pathogenic) strains. The tested substrates included commercial inulin, commercial agave syrup, artisanal maguey syrup, aqueous and cooked agave extract. Six Lactobacillus strains (Lactobacillus acidophilus, Lacticaseibacillus casei, Lactiplantibacillus plantarum ATCC 8014, Limosilactobacillus reuteri NRRL B-14171, Lactiplantibacillus plantarum NRRL B-4496, and Lacticaseibacillus rhamnosus) were evaluated against E. coli ATCC 43888 and E. coli clinical isolates. Carbohydrate characterization included analyses of total and reducing carbohydrates and thin-layer chromatography (TLC) to assess the degree of polymerization (DP). Prebiotic Index (PI) and Prebiotic Activity Score (PAS) were calculated to determine selective growth stimulation at 24 and 48 h. TLC analysis revealed two distinct groups: high-molecular-weight compounds (aqueous agave extract and commercial inulin), and low-molecular-weight compounds (cooked agave extract, commercial agave syrup, and artisanal maguey syrup). L. reuteri NRRL B-14171 exhibited the highest PI (approaching 2.0) with aqueous agave extract at 24 h. L. rhamnosus demonstrated superior PAS values across all prebiotic sources, while commercial inulin and artisanal maguey syrup showed the most favorable PAS values against clinical E. coli isolates, indicating preferential in vitro growth of LAB over the pathogen. These findings represent preliminary indications of selective carbohydrate utilization by LAB strains under controlled in vitro conditions. Further studies, incorporating digestion resistance, fermentation by complex microbiota, metabolite production, and host-related effects are required before confirming prebiotic functionality.

Tuberculosis (TB) remains a leading cause of morbidity and mortality among people living with human immunodeficiency virus (HIV), in whom immunosuppression often results in atypical clinical manifestations, paucibacillary disease, extrapulmonary involvement, and disseminated forms that complicate timely diagnosis. This narrative review summarizes current and emerging diagnostic approaches for TB-HIV, with emphasis on their diagnostic performance, clinical applicability, implementation challenges, and potential integration into future algorithms. Conventional methods, including sputum smear microscopy, mycobacterial culture, and chest radiography, remain relevant but have important limitations in people living with HIV (PLHIV), particularly in advanced immunosuppression. Rapid molecular tests, especially Xpert MTB/RIF and Xpert MTB/RIF Ultra, have improved early detection of Mycobacterium tuberculosis and rifampicin resistance, although diagnostic gaps persist in sputum-scarce and extrapulmonary disease. Non-sputum-based tests, particularly WHO-recommended urine LF-LAM and emerging next-generation assays such as FujiLAM II, offer important opportunities for severely ill patients and those with advanced HIV disease. Host-derived biomarkers, transcriptomic signatures, and artificial intelligence-assisted chest imaging may further strengthen screening, triage, and diagnostic prioritization. Integrated, context-adapted diagnostic algorithms combining microbiological, molecular, urinary, imaging, and host-response tools are needed to improve early TB detection and reduce mortality in resource-limited settings.

Currently, the search for a healthier lifestyle has led to an increase in the popularity and demand for functional beverages. These products, which go beyond providing hydration, are formulated with specific ingredients aimed at offering additional health benefits through biotechnological processes. Taking into account reports on functional beverages obtained through biotechnological processes from different substrates, we have identified that the documentation of processes and products is not sufficiently complete. Therefore, it is necessary to update the biotechnological processes that influence the quality and acceptance by consumers, including some of the new technologies involved, such as precision fermentation, as well as the nutrients, chemical properties, and health benefits. According to the reviewed studies, it can be projected that functional beverages obtained from different substrates through biotechnological processes will occupy an important place in the new innovations demanded by the functional food market.

Biosurfactants are amphipathic compounds produced by various microorganisms, including fungi and yeasts, with those produced by the latter being of particular interest as they are considered microorganisms of low or no sanitary risk. This article presents an analysis of the available information regarding the role these compounds play within the ecological habitat where yeasts inhabit, as well as their potential biotechnological applications in commercial areas. Some of the biological roles that biosurfactants play for their producing microorganisms are unknown and can be highly diverse, depending on the adaptive needs microorganisms have to survive the environmental conditions prevalent in their habitat. However, some of these roles that have been reported are related to nutrient availability, cellular communication, and competition, as well as surface colonization. The structures of biosurfactant molecules produced by yeasts are highly diverse, and so far, have been reported as sophorolipids, carbohydrate–protein–lipid complexes, carbohydrate–protein polymers, mixtures of lactones, and mannosylerythritol lipids. In addition to their properties as surfactants and/or emulsifiers, many of these molecules have also been reported to possess biological activities, including antimicrobial, antifungal, antitumoral, antioxidant, antiadhesive, antiviral, ultraviolet (UV)-protectant, anti-aging agent, moisturizing, and enzyme-activator/inhibitor properties. By understanding the functions that biosurfactants perform in nature, novel and efficient methods for their production can be proposed, as well as new applications in areas such as pharmaceuticals, food, and cosmetics. The latter is of particular interest due to the growing biosurfactant market and the processes that demand greater knowledge about their production, biological, and environmental interactions for their management and disposal.

Food security among college students is an increasing concern, with potential implications for their health, academic performance, and future well-being. This study investigated food security within a college community in Mexico, focusing on food availability, access (both economic and physical), and consumption patterns. A mixed-methods approach was employed at Ciudad Universitaria, BUAP, Mexico, between 2023 and 2024. Stratified random sampling was used, resulting in a final sample of 606 students. Data were collected through structured questionnaires covering sociodemographic characteristics and eating habits, the ELCSA, structured cafeteria observations, semi-structured interviews with key informants, and three focus groups. Statistical analysis was performed using chi-square tests (p < 0.05). Post hoc analysis with Bonferroni adjustment confirmed that origin (p = 0.0017), mode of transportation (p = 2.31 × 10⁻⁵) and private vehicles (p = 1.77 × 10⁻⁵) were the key determinants. Although the environment offered a variety of options, processed and ultra-processed products dominated the food choices. A total of 95.9% of students purchased food on campus, yet only 21.8% reported engaging in healthy eating habits. Focus groups revealed that students’ food choices were influenced by availability, access, and perceptions of affordability and convenience. These findings highlight the urgent need for targeted interventions to improve food security and promote healthier dietary practices within the college setting.

Machine Learning and Predictive Microbiology: Enhancing Food Safety Models 14The goal of food safety is to guarantee that the food provided to consumers does not represent a 15 health risk due to the presence of chemical, physical, or biological hazards. In particular, microbial 16 growth of spoilage or pathogenic microorganisms can reduce the shelf life or pose a health hazard. 17The composition, physical, and chemical properties of a food product can either promote or inhibit 18 microbial growth; also, food processing methods can favor or restrain microbial proliferation. The 19 response of microorganisms to food composition, processing, or storage conditions will determine 20 their growth capacity. Traditional microbial growth models, often used in laboratory settings, do not 21 always translate well to real-world food environments due to the unique conditions present in food 22 systems. Predictive microbiology has emerged as a valuable tool in this context, enabling researchers 23 to predict the behavior of pathogenic and spoilage microorganisms in food systems based on growth 24 results obtained under controlled conditions (Kumar et al. 2024). 25The food industry constantly modifies processing conditions, develops or enhances more efficient 26 preservation methods, and creates new food products. In all these scenarios, the use of predictive 27 microbiology can help select the best conditions to increase shelf life and reduce the risk of pathogen 28 contamination. Even when predictive models have been utilized in the food industry as a complement 29 to quality control programs, such as HACCP (Hazard Analysis and Critical Control Points), 30 numerous challenges remain in this research area. The development of new predictive primary 31 models is an ongoing task, as new variables can be incorporated and new statistical and mathematical 32 methods become available. Typically, predictive models examine the growth of an organism under 33 controlled conditions; however, the impact of interactions with other organisms present in the food 34 environment is often overlooked. Additionally, the initial physiological state of the microorganisms needs to be taken into consideration (Koseki et al., 2021). The incorporation of new information 36 provided by the "omics" sciences, particularly functional genomics, can also improve the prediction 37 of microbial growth in foods. Tools such as data mining or machine learning can utilize up-to-date 38 information on microbial growth in food systems to generate more comprehensive predictive models 39 (Taiwo et al. 2024). 40In the present Research Topic, the combination of preservation methods is reported as efficient in 41 increasing the shelf life of food products. In Chen et al (2024), the antimicrobial effect of lemon 42 essential oil alone and in nanoemulsion was tested against common foodborne pathogens 43 (Escherichia coli, Staphylococcus aureus, Listeria monocytogenes). The effect was also tested on the 44 shelf life of fresh-cut kiwifruits, showing that the increase in shelf life was related to the 45 antimicrobial and antioxidant effects of the nanoemulsion. In another study, the effect of lactic acid 46 bacteria (LAB) inoculants on the quality of oat silage was investigated, seeking to reduce the 47 concentration of biogenic amines and thereby improve product safety (Huang and Jia, 2025 was used to construct the secondary and tertiary models, which were then validated with 60 experimental data. The author emphasizes the importance of developing tertiary models that can be 61 used in the food industry. 62The incorporation of novel strategies to manage data, such as data mining, neural networks, and 63 machine learning, presents an opportunity to enhance the goals of predictive microbiology. A better 64 understanding of the physiological stages of microorganisms in food systems, along with the changes 65 in growth conditions at different steps in the food management chain, can also provide a more 66 accurate view of the effects of processing on food preservation and safety. Several questions remain 67 to be answered in this topic. 68

Two types of chito were evaluated: non-pressed (NP, immediate consumption) and pressed (P, for sale). The characteristics were analysed in samples of three years (2021–2023). The pH, water activity (a_w), proximate composition, heme iron, sodium chloride (NaCl), water soluble nitrogen (WSN), color, metmyoglobin (MMb), texture, lipid oxidation (Thiobarbituric acid reactive substances, TBARS), and microbiological analysis were evaluated, while volatile compounds were identified in NP and P. The a_w value showed a mean value of 0.70 in NP and P, values reported for typical commercial dried meat samples. However, P showed higher pH values (5.65–5.75), as well as a high level of fat (6.44–15.03%), NaCl (10.93–11.21%), lipid oxidation (3.88–6.32 mg MDA/kg meat), and hardness (223.67–574.01 N), with a browner color than NP, whereas microbial counts were similar between NP and P. Typical breakdown products derived from lipid oxidation were the main volatile compounds detected in chito, with aldehydes and alcohols being the most detected in P. The results suggest that some of the physicochemical characteristics, as well as the volatile profile, showed some differences between both types of chito, which suggests that there was a variation in the meat product associated with the making processes.