beta-Microseminoprotein in human spermatozoa and its potential role in male fertility

beta-Microseminoprotein (MSMB) is one of the most abundant proteins in human seminal plasma. The objectives of this study were: (1) to purify MSMB from seminal plasma (SP) and generate antibodies against the pure protein; (2) to investigate the interaction of MSMB with ejaculated spermatozoa and its possible effect on the spontaneous acrosome reaction (AR); and (3) to quantify MSMB content in SP and examine its relationship with the clinical sperm parameters. MSMB was purified from SP and its presence on the sperm surface was examined by indirect immunofluorescence using a specific polyclonal antibody. The effect of MSMB on the AR was evaluated using guinea pig epididymal spermatozoa as a model. MSMB quantification assay was performed with a two-site binding ELISA using two polyclonal antibodies against MSMB. MSMB was assessed in semen samples from fertile donors (controls) and subfertile patients according to World Health Organization criteria. MSMB was detected on the sperm surface and mainly localized to the acrosomal region of the head and neck. A significant spontaneous AR inhibition was observed when guinea pig epididymal spermatozoa were preincubated with MSMB. Finally, MSMB was significantly increased in subfertile patients when compared with fertile controls (P<0.02). The association of MSMB to the sperm surface, the inhibitor effect on the spontaneous AR and the increased MSMB levels found in SP in subfertile men suggests a relationship between this protein and semen quality and a possible role in the process of fertilization.     

Lipoxygenase activity associated to fruit ripening and senescence in chayote (Sechium edule Jacq. Sw. cv. “virens levis”)

Lipoxygenase (LOX) enzyme activity and their putative isoforms were investigated during postharvest life in chayote fruit (Sechium edule Jacq. Sw. cv. “virens levis”). Possible associations of LOX with fruit quality parameters are discussed. Five LOX isoforms were identified (SeLOX‐1 to ?5) displaying different activity patterns during ripening and senescence as well as in roots, stems, and leaves. The probable role of SeLOX‐5 as a specific isoform linked to senescence was examined. The highest relative activity of LOX was registered in fruit tissue, followed by leaves, stem, and roots. Correlations were found between LOX and fruit composition variables such as the contents of linoleic (LA) and linolenic (LNA) acids, weight loss, CO₂ and ethylene production rates. LOX activity, and LA and LNA concentration decreased from Day 1 to Days 13–17, when early seed germination events became visible, indicating a transition stage between late fruit ripening and early senescence characterized by a deteriorative process.

Practical applications

Detrimental effects on fruit composition variables such as dehydration, weight loss, wilting, and sprouting symptoms, have been reported as the main causes that reduce the commercial quality and shelf life in chayote fruit and prevent their export to distant markets. To the best of our knowledge, the association of lipoxygenase (LOX) enzymes to non‐climacteric fruit ripening—like chayote—or their loss of commercial quality during prolonged shelf life has not yet been described. This is the first study that explores the role of chayote LOX activity in fruit, identifies various specific LOX isoforms associated to ripening or to the senescence process and provides new evidence that supports the hypothesis that putative LOX isoforms might be related to several postharvest detrimental effects on chayote fruit. This information could be useful to food processors or packers to pursue better profitability and consumer satisfaction.     

Access to common resources and food security: Evidence from National Surveys in Nigeria

Common resources (CRs) provide a “hidden harvest” for rural households and can also act as a safety net in the event of poor agricultural output or seasonal food gaps, hence contributing to food security. Yet only limited empirical research has assessed the relationship between CRs and the self-assessed food security conditions recorded among rural households. This exploratory paper draws on recent data from the Nigerian General Household Survey (GHS), a nationally representative sample of households administered in 2012–2013 as part of the World Bank Living Standards Measurement Study — Integrated Surveys on Agriculture (LSMS-ISA). A sustainable livelihood framework was used to contextualise CR access within the broader set of food security drivers. In Nigeria, access to common pasture and water resources is significantly associated with less reporting of food insecurity. In contrast, access to common forest tends to be associated with food insecurity, suggesting that households with access to common forest remain vulnerable (i.e. isolated from services and opportunities) despite having the advantage of the forest as a source of food. Echoing existing literature, the relative importance of these commons decreases when income of households increases. However, there are no clear signs that access to commons acts as a seasonal safety net for households during the lean season. The paper advocates streamlining CR data collection alongside agricultural data for a more integrated food security policy intervention aimed at the most vulnerable.     

A case study of pellet size fraction influence on pelletizing operation

Pellet production is constantly optimized considering different aspects of the production chain from run of mining (ROM) to metallic iron. Industrially, the trade-off between an optimum pellet-size-ratio and the maximum performance in the steel production chain is a relevant subject. The present case study at a Brazilian operation shows the impact of different pellet size fractions on performance of operation, improvements on the fired pellets, less fine generation during handling, and superior metallurgical behavior during the reduction process, resulting in the production of direct reduction iron (DRI) that add more value to the economic performance of the electric arc furnaces (EAF).     

Natural Mallow Fiber-Reinforced Epoxy Composite for Ballistic Armor Against Class III-A Ammunition

Epoxy matrix composites reinforced with up to 30 vol pct of continuous and aligned natural mallow fibers were for the first time ballistic tested as personal armor against class III-A 9 mm FMJ ammunition. The ballistic efficiency of these composites was assessed by measuring the dissipated energy and residual velocity after the bullet perforation. The results were compared to those in similar tests of aramid fabric (Kevlar?) commonly used in vests for personal protections. Visual inspection and scanning electron microscopy analysis of impact-fractured samples revealed failure mechanisms associated with fiber pullout and rupture as well as epoxy cracking. As compared to Kevlar?, the mallow fiber composite displayed practically the same ballistic efficiency. However, there is a reduction in both weight and cost, which makes the mallow fiber composites a promising material for personal ballistic protection.     

Gelatine–starch films: Physicochemical properties and their application in extending the post‐harvest shelf life of avocado (Persea americana)

BACKGROUND: Several storage techniques have been developed to extend the post‐harvest shelf life of horticultural products. One method involves the use of edible or biodegradable coatings. Such coatings are made of biological materials that are used to coat fresh products, providing a semi‐permeable barrier to water vapour and gases, e.g. O₂ and CO₂. The influence of starch concentration, glycerol content and pH on the carbon dioxide permeability (CO₂P) and mechanical properties of gelatine–starch edible films were evaluated. RESULTS: Results showed that increments in the starch concentration and pH resulted in higher CO₂P values. Film puncture strength increased when the starch concentration decreased and the maximum resistance value (32.6 N) was obtained at pH 6. Deformation was mainly affected by glycerol and starch content. Some films were chosen in order to evaluate their effect, as coatings, in the post‐harvest shelf life of avocados (Persea americana Mill c.v. Hass). Fruits were immersed in the coating solutions, air dried and stored at two temperatures. Changes in colour, weight loss and pulp firmness were determined in fruits stored at 6 °C. In addition, respiration rate was measured in avocados kept at 20 °C. CONCLUSION: The application of gelatine–starch coatings delayed the ripening process of avocados, as indicated by a better pulp firmness and retention of skin colour, and lower weight loss of coated fruits in comparison with control avocados. The coatings also resulted in a delayed respiratory climacteric pattern, by 3 days, for coated fruits. Copyright © 2007 Society of Chemical Industry     

The Modulation of SCO2730/31 Copper Chaperone/Transporter Orthologue Expression Enhances Secondary Metabolism in Streptomycetes

Streptomycetes are important biotechnological bacteria that produce several clinically bioactive compounds. They have a complex development, including hyphae differentiation and sporulation. Cytosolic copper is a well-known modulator of differentiation and secondary metabolism. The interruption of the Streptomyces coelicolor SCO2730 (copper chaperone, SCO2730::Tn5062 mutant) blocks SCO2730 and reduces SCO2731 (P-type ATPase copper export) expressions, decreasing copper export and increasing cytosolic copper. This mutation triggers the expression of 13 secondary metabolite clusters, including cryptic pathways, during the whole developmental cycle, skipping the vegetative, non-productive stage. As a proof of concept, here, we tested whether the knockdown of the SCO2730/31 orthologue expression can enhance secondary metabolism in streptomycetes. We created a SCO2730/31 consensus antisense mRNA from the sequences of seven key streptomycetes, which helped to increase the cytosolic copper in S. coelicolor, albeit to a lower level than in the SCO2730::Tn5062 mutant. This antisense mRNA affected the production of at least six secondary metabolites (CDA, 2-methylisoborneol, undecylprodigiosin, tetrahydroxynaphtalene, α-actinorhodin, ε-actinorhodin) in the S. coelicolor, and five (phenanthroviridin, alkylresorcinol, chloramphenicol, pikromycin, jadomycin G) in the S. venezuelae; it also helped to alter the S. albus metabolome. The SCO2730/31 consensus antisense mRNA designed here constitutes a tool for the knockdown of SCO2730/31 expression and for the enhancement of Streptomyces’ secondary metabolism.     

A novel approach for the detection of anomalous energy consumption patterns in industrial cyber-physical systems

Most scenarios emerging from the Industry 4.0 paradigm rely on the concept of cyber-physical production systems (CPPS), which allow them to synergistically connect physical to digital setups so as to integrate them over all stages of product development. Unfortunately, endowing CPPS with AI-based functionalities poses its own challenges: although advances in the performance of AI models keep blossoming in the community, their penetration in real-world industrial solutions has not so far developed at the same pace. Currently, 90% of AI-based models never reach production due to a manifold of assorted reasons not only related to complexity and performance: decisions issued by AI-based systems must be explained, understood and trusted by their end users. This study elaborates on a novel tool designed to characterize, in a non-supervised, human-understandable fashion, the nominal performance of a factory in terms of production and energy consumption. The traceability and analysis of energy consumption data traces and the monitoring of the factory's production permit to detect anomalies and inefficiencies in the working regime of the overall factory. By virtue of the transparency of the detection process, the proposed approach elicits understandable information about the root cause from the perspective of the production line, process and/or machine that generates the identified inefficiency. This methodology allows for the identification of the machines and/or processes that cause energy inefficiencies in the manufacturing system, and enables significant energy consumption savings by acting on these elements. We assess the performance of our designed method over a real-world case study from the automotive sector, comparing it to an extensive benchmark comprising state-of-the-art unsupervised and semi-supervised anomaly detection algorithms, from classical algorithms to modern generative neural counterparts. The superior quantitative results attained by our proposal complements its better interpretability with respect to the rest of algorithms in the comparison, which emphasizes the utmost relevance of considering the available domain knowledge and the target audience when design AI-based industrial solutions of practical value. Finally, the work described in this paper has been successfully deployed on a large scale in several industrial factories with significant international projection.     

Development of an Automatic Pipeline for Participation in the CELPP Challenge

The prediction of how a ligand binds to its target is an essential step for Structure-Based Drug Design (SBDD) methods. Molecular docking is a standard tool to predict the binding mode of a ligand to its macromolecular receptor and to quantify their mutual complementarity, with multiple applications in drug design. However, docking programs do not always find correct solutions, either because they are not sampled or due to inaccuracies in the scoring functions. Quantifying the docking performance in real scenarios is essential to understanding their limitations, managing expectations and guiding future developments. Here, we present a fully automated pipeline for pose prediction validated by participating in the Continuous Evaluation of Ligand Pose Prediction (CELPP) Challenge. Acknowledging the intrinsic limitations of the docking method, we devised a strategy to automatically mine and exploit pre-existing data, defining—whenever possible—empirical restraints to guide the docking process. We prove that the pipeline is able to generate predictions for most of the proposed targets as well as obtain poses with low RMSD values when compared to the crystal structure. All things considered, our pipeline highlights some major challenges in the automatic prediction of protein–ligand complexes, which will be addressed in future versions of the pipeline.