Class Of Products Research Articles

Discovery and Heterologous Expression of Trilenodin, an Antimicrobial Lasso Peptide with a Unique Tri-Isoleucine Motif.

Lasso peptides are an increasingly relevant class of peptide natural products with diverse biological activities, intriguing physical properties, and unique chemical structures. Most characterized lasso peptides have been from Actinobacteria and Proteobacteria, despite bioinformatic analyses suggesting that other bacterial taxa, particularly those from Firmicutes, are rich in biosynthetic gene clusters (BGCs) encoding lasso peptides. Herein, we report the bioinformatic identification of a lasso peptide BGC from Paenibacillus taiwanensis DSM18679 which we termed pats. We used a bioinformatics-guided isolation approach and high-resolution tandem mass spectrometry (HRMS/MS) to isolate and subsequently characterize a new lasso peptide produced from the pats BGC, which we named trilenodin, after the tri-isoleucine motif present in its primary sequence. This tri-isoleucine motif is unique among currently characterized lasso peptides. We confirmed the connection between the pats BGC and trilenodin production by establishing the first Bacillus subtilis 168-based heterologous expression system for expressing Firmicutes lasso peptides. We finally determined that trilenodin exhibits potent antimicrobial activity against B. subtilis and Klebsiella pneumoniae, making trilenodin the first characterized biologically active lasso peptide from Firmicutes. Collectively, we demonstrate that bacteria from Firmicutes can serve as high-potential sources of chemically and biologically diverse lasso peptides.

Implementation of a community-based LC-UV drug checking service: promising preliminary findings on feasibility and validity

BackgroundThe increasing diversity of psychoactive substances on the unregulated drug market poses significant health, psychological, and social risks to people who use drugs (PWUD). To address these risks, various harm reduction (HR) policies have been implemented, including drug checking services (DCS). Many analytical methods are used for DCS. While qualitative methods (e.g., thin layer chromatography, spectroscopy) are easier to implement, they are not as accurate as quantitative methods (e.g., LC-UV, LC-MS). Some HR programmes have implemented high-performance liquid chromatography coupled with UV detection (LC-UV). This article presents the cross-validation of this quantitative method with a reference liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) method.MethodsDrug samples were provided by PWUD to a DCS called DrugLab in Marseille, France. The samples were weighed and prepared through dissolution in methanol, followed by ultrasonic bathing. Samples were analysed onsite using LC-UV analysis. They were then subsequently analysed with the reference LC-HRMS method. The LC-UV instrument in DrugLab was calibrated after being purchased; analysis of standard solutions was routinely performed once a month and after maintenance operations. For the LC-HRMS instrument, calibration and quality control procedures followed European Medicines Agency (EMA) guidelines. Statistical analyses were conducted including Spearman correlation tests using IBM® SPSS® Statistics version 20.ResultsA total of 102 samples representing different product classes and cutting agents were cross-validated. Differences between both analyses methods for each molecule analysed were ≤ 20%, with significant correlations between both methods’ results for most substances. Notably, LC-HRMS provided lower concentration values for cocaine and acetaminophen, whereas it provided higher values for other substances. Correlations were significant for cocaine, ketamine, MDMA, heroin, amphetamine, caffeine, acetaminophen, and levamisole.ConclusionsThis study demonstrates that the results provided by DrugLab were accurate and reliable, making LC-UV an adaptable, stable, and suitable analytical method for simple matrices like drugs in a DCS context. However, this cross validation does not guarantee accuracy over time. A proficiency test project in HR laboratories across France is currently under development in order to address potential drifts in LC-UV accuracy.

HIV Prevention Product Acceptability and Preference Among Women in Sub-Saharan Africa to Inform Novel Biomedical Options in Development: A Systematic Review.

The availability of several HIV prevention options may allow women to choose a product that suits their lifestyle and preferences. Product attributes and contextual factors influence product acceptability, which affects uptake and effective use. We conducted a systematic review of acceptability and preference for biomedical HIV prevention products among women in sub-Saharan Africa (SSA) to inform the development of novel products. We used a comprehensive strategy to search three databases for peer-reviewed literature from SSA published between January 2015 and December 2023. A two-stage review process assessed references against eligibility criteria. Data were abstracted using a standardized spreadsheet, then organized by constructs from two theoretical frameworks of acceptability. Results were synthesized based on product classes defined by route of administration. We identified 408 unique references; 100 references met eligibility criteria. References assessed oral PrEP (n = 65), vaginal ring (n = 44), long-acting systemic products (injectable, implant, microarray patch) (n = 28), and other vaginal products (film, insert, gel) (n = 20). Over two-thirds reported qualitative or mixed-methods data, primarily from adolescent girls and young women. Frequent dosing, especially noted for daily oral PrEP, and perceived/experienced side effects were notably negative influences. Most end-users preferred long-acting products (systemically or vaginally delivered), though on-demand products offering user control were also valued. Influencing factors, especially partners, shaped end-user perceptions of product attributes and acceptability. All products were linked to at least some barriers to uptake and/or use, highlighting the need to provide end-users with a range of options and assist them in identifying one that best suits their circumstances and needs. Biomedical HIV prevention development should advance products that address gaps in available options while optimizing favorable product attributes to achieve high acceptability that ultimately supports adoption and use.

Catalytic Transformation of Biomass into Sustainable Carbocycles: Recent Advances, Prospects, and Challenges.

Organic compounds bearing one or more carbocycles in their molecular structure have a discernible presence in all major classes of organic products of industrial significance. However, sourcing carbocyclic compounds from exhaustible, anthropogenic carbon (e.g., petroleum) raises serious concerns about sustainability in the chemical industries. This review discusses recent advances in the renewable synthesis of carbocyclic compounds from biomass components following catalytic pathways. The mechanistic insights, process optimizations, green metrics, and alternative synthetic strategies of carbocyclic compounds have been detailed. Moreover, the renewable syntheses of carbocycles have been assessed against their existing synthetic routes from petroleum for better perspectives on their sustainability and technological preparedness. This work will assist the researchers in acquiring updated information on the sustainable synthesis of carbocyclic compounds from various biomass components, comprehending the research gaps, and developing superior synthetic processes for their commercial production.

A General Entry to Ganoderma Meroterpenoids: Synthesis of Applanatumol E, H, and I, Lingzhilactone B, Meroapplanin B, and Lingzhiol.

Ganoderma meroterpenoids are fungal derived hybrid natural product class containing a 1,2,4-trisubstituted benzene ring and a polycyclic terpenoid part. The representatives applanatumol E, H and I, lingzhilactone B, and meroapplanin B share the same bicyclic lactone moiety connected to the arene. Employing photo-Fries rearrangements as the key step enabled a general entry to these natural products. For the synthesis of the tetracyclic framework of lingzhiol, we made use of a powerful photoredox oxidative decarboxylation/Friedel-Crafts sequence.

Context-aware feature reconstruction for class-incremental anomaly detection and localization

With the development of deep learning, the unsupervised visual anomaly detection and localization task has gained significant attention in both academia and industry, where only normal data are used for training. Existing methods for this task typically train using all training data simultaneously. However, in practical industrial scenarios, new product classes are usually introduced incrementally, leading to the sequential availability of training data. Such scenarios demand methods for class-incremental anomaly detection and localization (CADL). The main challenge of class-incremental learning is to retain knowledge of old classes when learning new classes. In this article, we aim to effectively leverage limited exemplars of old classes to retain knowledge for the CADL task. Achieving this goal requires a model that can efficiently capture anomaly-identification-related knowledge from limited exemplars. Considering that pixel-level anomaly identification requires an understanding of the surrounding context, we treat context within inputs as valuable anomaly-identification-related knowledge and design a context-aware feature reconstruction (CFR) model to capture such knowledge. Moreover, to avoid inter-class context conflict that may arise with class increments, we design an intermediate feature organization strategy. This strategy and output-level knowledge distillation jointly form dual constraints to regularize the model at both mid-feature and output levels. Utilizing the CFR model with Dual Constraints, the proposed CFRDC can effectively retain old-class knowledge while learning new classes, thus addressing the CADL task. Experimental results on the commonly-used MVTec-AD dataset demonstrate the effectiveness and outstanding performance of the proposed method in CADL.

Recent trends in the elucidation of complex triterpene biosynthetic pathways in horticultural trees

Abstract Triterpene (C30 isoprene compounds) represents the most structurally diverse class of natural products and has been extensively exploited in the food, medicine and industrial sectors. Decades of research on medicinal triterpene biosynthetic pathways have revealed their roles in stress tolerance and shaping microbiota. However, the biological function and mechanism of triterpenes are not fully identified. Even this scientific window narrows down for horticultural trees. The lack of knowledge and a scalable production system limits the discovery of triterpene pathways. Recent synthetic biology research revealed several important biosynthetic pathways that define their roles and address many societal sustainability challenges. Here, I review the chemical diversity and biosynthetic enzymes involved in triterpene biosynthesis of horticultural trees. This review also outlines the integrated Design-Build-Test-Learn (DBTL) pipelines for the discovery, characterization and optimization of triterpene biosynthetic pathways. Further, these DBTL components share many fundamental and technical difficulties, highlighting opportunities for interdisciplinary collaboration between researchers worldwide. This advancement opens up unprecedented opportunities for the bioengineering of triterpene compounds towards development and scaleup processes.

Mps1-Targeted Molecular Design of Melatonin for Broad-Spectrum Antifungal Agent Discovery.

Melatonin, a multifunctional class of natural products, has demonstrated antifungal activity, making it a promising candidate for developing antifungal agents. The mitogen-activated protein kinase (Mps1) within fungal pathogens has a target inhibitory effect of melatonin in fungi. We use a virtual screening strategy to design melatonin derivatives based on the melatonin-Mps1 targeting model. Of these, a multiflorane-substitution compound M-12 emerges as a potent antifungal agent, exhibiting broad-spectrum efficacy against eight phytopathogenic fungal species, and effectively reduces the severity of tomato gray mold, Fusarium head blight in wheat, Sclerotinia stem rot in rape, and peach brown rot. M-12 half-maximal effective concentration values (5.50 μM against Botrytis cinerea, 5.21 μM against Fusarium graminearum, 10.6 μM against Rhizoctonia solani, and 9.02 μM against Sclerotinia sclerotiorum) are better than those of commercial broad-spectrum fungicide azoxystrobin (55.0, 23.2, 46.5, and 17.7 μM, respectively). Antifungal activity of enantiomer (S)-M-12 (5.02 μM) is significantly greater than its (R)-enantiomer (23.6 μM) against B. cinerea. Molecular docking and transcriptome analysis reveal that M-12 achieves its antifungal effects by inhibiting Mps1 kinase, thereby suppressing fungal growth and virulence.

Inhibitor development upon switching from plasma-derived to recombinant factor VIII in previously untreated patients with severe hemophilia A: the PUP-SWITCH study

BackgroundThe SIPPET randomized clinical trial showed that in previously untreated patients (PUPs) with severe hemophilia A treatment with plasma-derived FVIII (pdFVIII) within the first 50 exposure days (EDs) was associated with a lower cumulative incidence of inhibitors than with recombinant FVIII (rFVIII). Switching to rFVIII beyond 50 EDs with pdFVIII is a treatment often implemented by many centers. The question is whether or not this switch may induce a risk of inhibitor development. ObjectivesWe investigated if in PUPs with severe hemophilia A switched after 50 EDs from pdFVIII to rFVIII, a novel inhibitor peak appears. MethodsThe PUP-SWITCH observational retrospective study was designed to investigate the cumulative incidence of novel inhibitors after switching PUPs to rFVIII after 50 and before 150 EDs. Hemophilia centers who routinely switched PUPs from pdFVIII to rFVIII within this exposure time frame were invited to participate. Patients were followed up for at least 50 EDs after the switch. ResultsNinety-seven patients were evaluated and 87 were included according to eligibility criteria between 2020 and 2022. Only one of them developed an inhibitor 20 EDs post-switching, so the cumulative incidence was 1.15% (95% CI 0.03 – 6.24%). ConclusionPUP-SWITCH, a study focusing on PUPs undergoing a product class switch from pdFVIII to rFVIII after 50 EDs, showed that switching appears to be safe pertaining to the risk of development of new inhibitors.

Do You “Relay” Want to Give Me Away? – Forensic Cues of Smart Relays and Their IoT Companion Apps

As IoT devices become more prevalent in everyday environments, their relevance to digital investigations increases. The product class of “smart relays”, which are connected to the low-voltage grid and usually installed in sockets behind walls, has not yet received much attention in the context of smart home forensics. To close a category-specific gap in the device forensics literature, we conducted a multi-device analysis of 16 smart relays from 9 manufacturers, which support six different companion apps in total. Our examination shows that forensic artifacts can be found locally on the smart relays and in the companion app data, as well as remotely on cloud servers of the vendors. Based on our findings, we developed a Python framework to extract forensic artifacts automatically from obtained firmware dumps, from companion app data, and from captured network traffic.

Faktor–Faktor Yang Memengaruhi Intensi Berwirausaha Pertanian Siswa SMK Agribisnis Di Kabupaten Cianjur

Cianjur Regency is one of the areas that relies on agriculture as a support for the economy and welfare of its people. In 2020, the number of poor people in Cianjur Regency decreased, allegedly due to increasing financial prosperity. Simultaneously, the number of entrepreneurs in Cianjur Regency has increased quite rapidly. This then suggests that one of the reasons for the increasing financial welfare of the people of Cianjur Regency is entrepreneurship. The majority of the population in the productive class aged 15-19 years who are currently studying at vocational high schools (SMK) are important capital for advancing agriculture in Cianjur Regency through entrepreneurship. The aim of this research is to analyze the factors that influence the agricultural entrepreneurship intentions of Agribusiness Vocational School students in Cianjur Regency. Determination of the sample in this study used proportionate stratified random sampling. The analytical method used is descriptive analysis and PLS-SEM analysis. The research results show that the factors that influence the agricultural entrepreneurship intentions of Agribusiness Vocational School students in Cianjur Regency are attitudes towards behavior, subjective norms and behavioral control. This research suggests that collaboration between the government, schools and universities is needed so that vocational school students maintain and improve the factors that can influence entrepreneurial intentions.

Proposal for the design of studies of intramammary antimicrobials to be conducted in Brazil for registration with the Ministry of Agriculture and Livestock

Before being made available to the Brazilian market, all veterinary medicines must be registered with the Ministry of Agriculture and Livestock after their efficacy, safety, and quality have been proven through clinical studies and scientific literature. Depending on the product class, the studies required by the regulatory authority must be carried out per Brazilian regulations and international reference guides. Some international organizations pursue the harmonization of these requirements, aiming at the mutual acceptance of studies conducted in different regions to facilitate international trade and reduce the use of animals in clinical research. Mastitis is one of the most prevalent and costly diseases in dairy cows, and it is associated with negative impacts on milk production and quality, cow welfare, and the profitability of the dairy industry. Normative Instruction No. 26/2009 determines a few rules for conducting studies for registering intramammary antimicrobials for cows with mastitis. However, the regulated sector and researchers report difficulties in following the recommendations of specific guidelines, which complement this regulation due to the peculiarities of Brazil’s production systems. This review article aims to provide subsidies and orientations that scientifically support the conduction and critical analysis of clinical studies proving the efficacy of intramammary products for treating clinical and subclinical mastitis in cows. Considering the need for scientific rigor in the studies, the recommendations available in international guidelines, and the need to adapt the protocols to the current situation of veterinary clinical research in Brazil, this document is intended to contribute to the internal harmonization of experimental protocols that support both the regulated sector and the regulatory authority.

Social Media as a Source of Information for the Detection of Adverse Drug Reactions in Post-Marketing Surveillance: A Review

INTRODUCTION. With the development of the Internet and the increasing availability of social networks and fora, patients have received an opportunity to share their medication experiences online. According to the guidelines on Good Pharmacovigilance Practices, social media can be considered an important additional source of patient-derived information in post-marketing surveillance, but the effectiveness of their use in detecting adverse drug reactions (ADRs) is still being investigated.AIM. This study aimed to analyse the results of relevant original studies and assess the potential of using social networks and online patient fora as a source of information on ADRs associated with the use of medicinal products.DISCUSSION. Published studies indicate that posts on social networks and patient fora describe both minor and serious ADRs, including new ADRs. The relevance of social media as a source of information about the safety of a medicinal product varies depending on several factors, including the medicinal product class and time on the market, as well as the platform demographics. Young users (18–44 years) are interested in online discussions about medicinal products for mental and reproductive system disorders. Users aged 45–64 years tend to discuss the use of medicinal products for chronic pain (including muscle pain), menopause, and gastritis. Discussions among users over 65 years old predominantly focus on medicinal products for diabetes, heart conditions, and muscle pain. People are much more likely to describe ADRs associated with the use of medicinal products for orphan diseases and cancer on fora for patients than on social networks in general, and vice versa for ADRs associated with the use of medicinal products for mental disorders. In addition, social media may be of interest as a source of information about cases of overdose, misuse and off-label use of medicinal products, and use of medicinal products during pregnancy and lactation.CONCLUSIONS. Social media can be a source of valuable information about the safety of medicinal products and the impact of ADRs on the quality of patients’ lives. Marketing authorisation holders can obtain new information about the safety of medicinal products by extending their safety monitoring strategies to include social media. Nevertheless, since the relevance of a particular social network or patient forum for the detection of ADR cases varies considerably, a preliminary assessment is necessary to ascertain the presence of information on the medicinal product of interest.

Natural polymers for emerging technological applications: cellulose, lignin, shellac and silk

AbstractIn an effort to stave off the growth of electronic waste (e‐waste) that poses a critical environmental dilemma, scientists often look into nature as an unending inspirational pool of materials and chemical processes that ensure functionality, performance and safe dissolution at the end of life cycle. This short review highlights only four organic polymer materials of natural origin (i.e. cellulose, lignin, shellac and silk) from the very large pool of natural (bio)polymeric materials and looks not only into the recent developments at the industrial scale but also into the emerging niche applications of these materials, while highlighting their implementation into electronics and sensor development. This review exemplifies that natural polymeric materials have great potential for the development of eco‐friendly electronics, in other words the class of industrial products that has carefully considered the important issues of biocompatibility, biodegradability (even compostability), cost of production and energy expanded in production (i.e. the carbon footprint). © 2024 The Author(s). Polymer International published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Models and P4R asset description for digital twin-based advanced planning and scheduling using cyber-physical integration for resilient production operation

Advanced planning and scheduling (APS) addresses the complex and uncertain nature of production control. A digital twin (DT), which incorporates simulations through cyber-physical integration, provides an advanced functionality for APS. To facilitate efficient design and implementation, a DT-based APS must satisfy three requirements: technical functionalities for resilience, robust models for diverse operational constraints, and efficient interoperability through cyber-physical integration. Although several studies have proposed the use of DT as a primary technology for APS, proposals that address the process, functionality, integration, and information models are lacking. Additionally, the existing asset descriptions cannot adequately capture the sophisticated characteristics of DT and necessary informational elements for APS. Thus, this study designed a process model, functionalities, and integration models for the DT-based APS and asset descriptions for snapshot synchronization. Crucial service-compositions and functionalities were defined using work-center-level lifecycles. Consequently, a process model was developed, which focused on core activities for resilience. Moreover, horizontal integration between DT and control functionalities and vertical integration between DT and standards, were proposed to enhance the DT-based APS. The proposed method effectively managed the product, process, plan, plant, and resource classes by ensuring adherence to asset administration shell principles. To validate the effectiveness of the proposed methods, two work centers with distinctly different characteristics were employed and demonstrated dominant preventive measures compared to static functionality-based methods. The primary contributions encompass the facilitation of integration and interoperability within a DT-based APS. The proposed methods support the advanced characteristics of DT, ensuring robustness and neutrality across heterogeneous operational contexts.

Biosynthesis of peptide-nucleobase hybrids in ribosomal peptides.

The main biopolymers in nature are oligonucleotides and polypeptides. However, naturally occurring peptide-nucleobase hybrids are rare. Here we report the characterization of the founding member of a class of peptide-nucleobase hybrid natural products with a pyrimidone motif from a widely distributed ribosomally synthesized and post-translationally modified (RiPP) biosynthetic pathway. This pathway features two steps where a heteromeric RRE-YcaO-dehydrogenase complex catalyzes the formation of a six-membered pyrimidone ring from an asparagine residue on the precursor peptide, and an acyl esterase selectively recognizes this moiety to cleave the C-terminal follower peptide. Mechanistic studies reveal that the pyrimidone formation occurs in a substrate-assisted catalysis manner, requiring a His residue in the precursor to activate asparagine for heterocyclization. Our study expands the chemotypes of RiPP natural products and the catalytic scope of YcaO enzymes. This discovery opens avenues to create artificial biohybrid molecules that resemble both peptide and nucleobase, a modality of growing interest.

Physicochemical, Antimicrobial Properties and Mineral Content of Several Commercially Available Honey Samples

Ensuring food safety and protecting consumers are major aspects for commercialized products. Honey, the most prominent in the class of bee products, requires special regulations due to its origin as a natural product. Mislabeling, imitation, and adulteration represent a source of risks for human health. Specific determinations and analyses are essential for controlling the sector and preventing unfair competition. To compare and establish the correct labeling of several different honeys, melissopalynological, physicochemical, mineral content, and microbiological analyses were carried out on 18 samples commercially available in different countries, namely Türkiye, Romania, Bulgaria, and Northern Cyprus. The honey labels were in accordance with the determined pollen content. The physiochemical parameters showed high variability: 4.07–5.25 (pH), 79.95–83.45 (°Brix), 0.262–1.452 µS/cm (electrical conductivity), and 14.6–18.4% (moisture). The samples were quantitatively high in K, P, Na, and Ca, with the highest cumulative mineral content being found for honeys containing Fagaceae pollen. Additionally, the antimicrobial potential of the various honey samples was evaluated against selected bacteria, employing the disk diffusion and serial dilution methods. Results revealed that the honey samples exhibited increased antibacterial activity against Gram-negative bacteria, with notable activity against S. typhimurium, and moderate activity against Gram-positive S. aureus.

Construction d’une méthodologie d’évaluation clinique des dispositifs médicaux grâce aux outils de simulation et illustration à travers trois études

European regulations have recently moved towards more stringent requirements for demonstrating the safety and performance of medical devices (MDs). To apply an innovative testing method using medical simulation to the evaluation of three medical devices at different stages of their life cycle. The methodology for evaluating DMs using simulation is based on seven stages: definition of the context, training, construction of a scenario to test the DM, validation of the scenario, realization of the scenario, evaluation of the scenario by the players and validation and exploitation of the results. Our evaluation methodology enabled us to assess three DMs at different stages of their development: a respiratory protection device at the initial stage (prototype definition), a respiratory protection mask (prototype optimization) and bottle adapters (post-marketing). Simulation is a valuable tool for evaluating DM. The proposed methodology enables it to be used and adapted to different contexts. It responds to the specificities of clinical evaluation of this class of products, and helps to better anticipate certain risks.

A Study on Korean Language and Digital Education in the Age of AI: Effects of Digital Team Presentation Video Production Class on Middle School Students' Participation in Class and Learning Experience

A Study on Korean Language and Digital Education in the Age of AI: Effects of Digital Team Presentation Video Production Class on Middle School Students' Participation in Class and Learning Experience

A novel classification algorithm for customer churn prediction based on hybrid Ensemble-Fusion model

Nowadays, customer churn issues are becoming more and more important, which is one of the most important metrics for evaluating the health of a business it is difficult to measure success without measuring customer churn metrics. However, it has become a challenge for the industry to predict when customers are churning or preparing to churn and to take the necessary action at the critical time before they do. At the same time, how to keep the place of deep research on the 17 machine learning algorithms in 9 major classes of machine learning classics production is the first problem we are facing. Through customer churn deep research, we mentioned the Ensemble-Fusion model based on machine learning and introduced a smart intelligent system to help reduce the actual customer churn about the production. Comparing with most popular predictive models, such as the Support vector machine algorithm, Random Forest algorithm, K-Nearest-Neighbor algorithm, Gradient boosting algorithm, Logistic regression algorithm, Bayesian algorithm, Decision tree algorithm, and Neural network algorithm are applied to check the effect on accuracy, AUC, and F1-score. By comparing with 17 algorithms in 9 categories of machine learning classics, the data prediction accuracy of the Ensemble-Fusion model reaches 95.35%, AUC score reaches 91% and F1-Score reaches 96.96%. The experimental results show that the data prediction accuracy of the Ensemble-Fusion model outperforms that of other benchmark algorithms.