Identification of Active Compounds against Melanoma Growth by Virtual Screening for Non-Classical Human DHFR Inhibitors.

Antifolates such as methotrexate (MTX) have been largely known as anticancer agents because of their role in blocking nucleic acid synthesis and cell proliferation. Their mechanism of action lies in their ability to inhibit enzymes involved in the folic acid cycle, especially human dihydrofolate reductase (hDHFR). However, most of them have a classical structure that has proven ineffective against melanoma, and, therefore, inhibitors with a non-classical lipophilic structure are increasingly becoming an attractive alternative to circumvent this clinical resistance. In this study, we conducted a protocol combining virtual screening (VS) and cell-based assays to identify new potential non-classical hDHFR inhibitors. Among 173 hit compounds identified (average logP = 3.68; average MW = 378.34 Da), two-herein, called C1 and C2-exhibited activity against melanoma cell lines B16 and A375 by MTT and Trypan-Blue assays. C1 showed cell growth arrest (39% and 56%) and C2 showed potent cytotoxic activity (77% and 51%) in a dose-dependent manner. The effects of C2 on A375 cell viability were greater than MTX (98% vs 60%) at equivalent concentrations and times. Our results indicate that the integrated in silico/in vitro approach provided a benchmark to identify novel promising non-classical DHFR inhibitors showing activity against melanoma cells.

The new world of philanthropy: How changing financial behavior, public policies, and COVID-19 affect nonprofit fundraising and marketing.

Evolving financial behavior, an unpredictable public policy atmosphere, and an unparalleled global pandemic have collaborated to disrupt nonprofit fundraising. The COVID-19 pandemic alone exacerbated consumer demands for nonprofit services while curtailing nonprofit organizations' ability to fundraise. Without fundraising, nonprofit organizations cannot achieve their mission or support their causes, leading to a precarious situation for societal well-being. Meanwhile, consumers are changing their financial behaviors, with younger generations often going cashless. At the same time, governments continue to change policies that affect nonprofit organizations. In keeping with the transformative consumer research movement, the present study provides a conceptual framework for the state of nonprofit fundraising amid the challenges associated with changes in financial behavior and public policy, coupled with the effects of the global pandemic. Marketing strategies for fundraising success are presented to aid nonprofits going forward and serve societal interests.

Hsa-miR-139-5p is a prognostic thyroid cancer marker involved in HNRNPF-mediated alternative splicing.

It is critical to identify biomarkers and functional networks associated with aggressive thyroid cancer to anticipate disease progression and facilitate personalized patient management. We performed miRNome sequencing of 46 thyroid tumors enriched with advanced disease patients with a median follow-up of 96 months. MiRNome profiles correlated with tumor-specific histopathological and molecular features, such as stromal cell infiltration and tumor driver mutation. Differential expression analysis revealed a consistent hsa-miR-139-5p downexpression in primary carcinomas from patients with recurrent/metastatic disease compared to disease-free patients, sustained in paired local metastases and validated in publicly available thyroid cancer series. Exogenous expression of hsa-miR-139-5p significantly reduced migration and proliferation of anaplastic thyroid cancer cells. Proteomic analysis indicated RICTOR, SMAD2/3 and HNRNPF as putative hsa-miR-139-5p targets in our cell system. Abundance of HNRNPF mRNA, encoding an alternative splicing factor involved in cryptic exon inclusion/exclusion, inversely correlated with hsa-miR-139-5p expression in human tumors. RNA sequencing analysis revealed 174 splicing events differentially regulated upon HNRNPF repression in our cell system, affecting genes involved in RTK/RAS/MAPK and PI3K/AKT/MTOR signaling cascades among others. These results point at the hsa-miR-139-5p/HNRNPF axis as a novel regulatory mechanism associated with the modulation of major thyroid cancer signaling pathways and tumor virulence.

Otoplasty Using the Combined Mustardé-Furnas Technique: Satisfaction and Objective Results.

BACKGROUND: To understand the level of satisfaction among patients undergoing otoplasty using the combined Mustardé-Furnas technique. To evaluate surgery outcomes using McDowell/Wright (MW) criteria. OBJECTIVES: The authors sought to analyze any possible correlation between satisfaction level and surgery outcome. METHODS: The authors conducted a retrospective study on patients who underwent combined Mustardé and Furnas otoplasty between 1996 and 2016. All patients were assessed 12 months after surgery employing MW goals and satisfaction surveys. RESULTS: The study includes 172 patients who underwent 343 otoplasty procedures. There were 134 patients (77.9%) who had all 6 of the criteria for surgical success as defined by MW 12 months after surgery, reporting satisfaction levels of 9 to 10. Fifteen patients (9.3%) had 5 of the 6 MW criteria, reporting satisfaction levels of 9 to 10, and 22 patients (12.79%) had only 4 MW objectives and reported satisfaction levels of 7 to 10. The Spearman rho coefficient was 0.545 and the Kendall coefficient was 0.375, with a statistically significant association (P < 0.001). CONCLUSIONS: Patient satisfaction increases as the number of MW goals are met, although the correlation is moderate to low. Patients perceive the results of the surgery as satisfactory or very satisfactory, even when ENT surgeons consider outcomes to be poor according to MW criteria.

[Clinical and genetic study patients with tuberous sclerosis complex]. / Estudio clínico genético en pacientes con complejo de esclerosis tuberosa.

Tuberous sclerosis complex (TSC) is a multisystem autosomal dominant disease caused by mutations in the tumor suppressor genes TSC1 or TSC2. OBJECTIVE: To characterize clinically and genetically patients diagnosed with TSC. PATIENTS AND METHOD: Descriptive study of clinical records of 42 patients from a pediatric neuropsychiatry department diagnosed with TSC and genetic study in 21 of them. The exon 15 of TSC1 gene and exons 33, 36 and 37 of TSC2 gene were amplified by polymerase chain reaction and sequenced. The relationship between the mutations found with the severity and clinical course were analyzed. RESULTS: In 61.9% of the patients the symptoms began before 6 months of age. The initial most frequent manifestations of TSC were new onset of seizures (73.8%) and the detection of cardiac rhabdomyomas (16.6%). During the evolution of the disease all patients had neurological involvement; 92.9% had epilepsy. All patients presented hypomelanotic spots, 47.6% facial angiofibromas, 23.8% Shagreen patch, 47.6 heart rhabdomyomas and 35.7% retinal hamartomas. In the genetic study of 21 patients two heterozygous pathogenic mutations in TSC1 and one in TSC2 genes were identified. The latter had a more severe clinical phenotype. CONCLUSIONS: Neurological and dermatological manifestations were the most frequent ones in patients with TSC. Two pathogenic mutations in TSC1 and one in TSC2 genes were identified. The patient with TSC2 mutation manifested a more severe clinical phenotype.

Development of a group contribution method for estimating free energy of peptides in a dodecane-water system via molecular dynamic simulations.

BACKGROUND: Calculation of the Gibbs free energy changes of biological molecules at the oil-water interface is commonly performed with Molecular Dynamics simulations (MD). It is a process that could be performed repeatedly in order to find some molecules of high stability in this medium. Here, an alternative method of calculation has been proposed: a group contribution method (GCM) for peptides based on MD of the twenty classic amino acids to obtain free energy change during the insertion of any peptide chain in water-dodecane interfaces. Multiple MD of the twenty classic amino acids located at the interface of rectangular simulation boxes with a dodecane-water medium were performed. RESULTS: A GCM to calculate the free energy of entire peptides is then proposed. The method uses the summation of the Gibbs free energy of each amino acid adjusted in function of its presence or absence in the chain as well as its hydrophobic characteristics. CONCLUSION: Validation of the equation was performed with twenty-one peptides all simulated using MD in dodecane-water rectangular boxes in previous work, obtaining an average relative error of 16%.

Proteins interaction network and modeling of IGVH mutational status in chronic lymphocytic leukemia.

BACKGROUND: Chronic lymphocytic leukemia (CLL) is an incurable malignancy of mature B-lymphocytes, characterized as being a heterogeneous disease with variable clinical manifestation and survival. Mutational statuses of rearranged immunoglobulin heavy chain variable (IGVH) genes has been consider one of the most important prognostic factors in CLL, but despite of its proven value to predict the course of the disease, the regulatory programs and biological mechanisms responsible for the differences in clinical behavior are poorly understood. METHODS: In this study, (i) we performed differential gene expression analysis between the IGVH statuses using multiple and independent CLL cohorts in microarrays platforms, based on this information, (ii) we constructed a simplified protein-protein interaction (PPI) network and (iii) investigated its structure and critical genes. This provided the basis to (iv) develop a Boolean model, (v) infer biological regulatory mechanism and (vi) performed perturbation simulations in order to analyze the network in dynamic state. RESULTS: The result of topological analysis and the Boolean model showed that the transcriptional relationships of IGVH mutational status were determined by specific regulatory proteins (PTEN, FOS, EGR1, TNF, TGFBR3, IFGR2 and LPL). The dynamics of the network was controlled by attractors whose genes were involved in multiple and diverse signaling pathways, which may suggest a variety of mechanisms related with progression occurring over time in the disease. The overexpression of FOS and TNF fixed the fate of the system as they can activate important genes implicated in the regulation of process of adhesion, apoptosis, immune response, cell proliferation and other signaling pathways related with cancer. CONCLUSION: The differences in prognosis prediction of the IGVH mutational status are related with several regulatory hubs that determine the dynamic of the system.

Machine Learning to Predict Enzyme-Substrate Interactions in Elucidation of Synthesis Pathways: A Review.

Enzyme-substrate interactions play a fundamental role in elucidating synthesis pathways and synthetic biology, as they allow for the understanding of important aspects of a reaction. Establishing the interaction experimentally is a slow and costly process, which is why this problem has been addressed using computational methods such as molecular dynamics, molecular docking, and Monte Carlo simulations. Nevertheless, this type of method tends to be computationally slow when dealing with a large search space. Therefore, in recent years, methods based on artificial intelligence, such as support vector machines, neural networks, or decision trees, have been implemented, significantly reducing the computing time and covering vast search spaces. These methods significantly reduce the computation time and cover broad search spaces, rapidly reducing the number of interacting candidates, as they allow repetitive processes to be automated and patterns to be extracted, are adaptable, and have the capacity to handle large amounts of data. This article analyzes these artificial intelligence-based approaches, presenting their common structure, advantages, disadvantages, limitations, challenges, and future perspectives.

Saccharomyces cerevisiae biofactory to produce naringenin using a systems biology approach and a bicistronic vector expression strategy in flavonoid production.

IMPORTANCE: Flavonoids are a group of compounds generally produced by plants with proven biological activity, which have recently beeen recommended for the treatment and prevention of diseases and ailments with diverse causes. In this study, naringenin was produced in adequate amounts in yeast after in silico design. The four genes of the involved enzymes from several organisms (bacteria and plants) were multi-expressed in two vectors carrying each two genes linked by a short viral peptide sequence. The batch kinetic behavior of the product, substrate, and biomass was described at lab scale. The engineered strain might be used in a more affordable and viable bioprocess for industrial naringenin procurement.

Modeling of the hypothalamic-pituitary-adrenal axis-mediated interaction between the serotonin regulation pathway and the stress response using a Boolean approximation: a novel study of depression.

Major depressive disorder (MDD) is a multifactorial disorder known to be influenced by both genetic and environmental factors. MDD presents a heritability of 37%, and a genetic contribution has also been observed in studies of family members of individuals with MDD that imply that the probability of suffering the disorder is approximately three times higher if a first-degree family member is affected. Childhood maltreatment and stressful life events (SLEs) have been established as critical environmental factors that profoundly influence the onset of MDD. The serotonin pathway has been a strong candidate for genetic studies, but it only explains a small proportion of the heritability of the disorder, which implies the involvement of other pathways. The serotonin (5-HT) pathway interacts with the stress response pathway in a manner mediated by the hypothalamic-pituitary-adrenal (HPA) axis. To analyze the interaction between the pathways, we propose the use of a synchronous Boolean network (SBN) approximation. The principal aim of this work was to model the interaction between these pathways, taking into consideration the presence of selective serotonin reuptake inhibitors (SSRIs), in order to observe how the pathways interact and to examine if the system is stable. Additionally, we wanted to study which genes or metabolites have the greatest impact on model stability when knocked out in silico. We observed that the biological model generated predicts steady states (attractors) for each of the different runs performed, thereby proving that the system is stable. These attractors changed in shape, especially when anti-depressive drugs were also included in the simulation. This work also predicted that the genes with the greatest impact on model stability were those involved in the neurotrophin pathway, such as CREB, BDNF (which has been associated with major depressive disorder in a variety of studies) and TRkB, followed by genes and metabolites related to 5-HT synthesis.

[Article on SEIMC Procedure No.42: Environmental microbiological monitoring]. / Control microbiológico ambiental.

The inanimate hospital environment is rarely implicated in infection transmission, except among vulnerable patients. Some authors argue against the use of environmental surveillance cultures because the tests can be expensive and time consuming, and because they should not be used instead of quality control and good practices in disinfection and maintenance procedures. Routine environmental sampling is not usually advised, except in situations where sampling is directed by epidemiologic principles, and results can be applied to adopt infection control measures. The incidence of health-care associated infections can be minimised by appropriate maintenance of medical equipment such as endoscope cleaning and disinfection, adherence to water-quality standards for haemodialysis, and to ventilation standards for specialised care environments such as isolation units, or operating rooms. This paper reviews the current knowledge on surveillance cultures in these settings in order to prevent iatrogenic infections in operating and isolation rooms, haemodialysis and endoscope reprocessing units, and cultures related to nosocomial infection outbreaks.

A Holistic Approach from Systems Biology Reveals the Direct Influence of the Quorum-Sensing Phenomenon on Pseudomonas aeruginosa Metabolism to Pyoverdine Biosynthesis.

Computational modeling and simulation of biological systems have become valuable tools for understanding and predicting cellular performance and phenotype generation. This work aimed to construct, model, and dynamically simulate the virulence factor pyoverdine (PVD) biosynthesis in Pseudomonas aeruginosa through a systemic approach, considering that the metabolic pathway of PVD synthesis is regulated by the quorum-sensing (QS) phenomenon. The methodology comprised three main stages: (i) Construction, modeling, and validation of the QS gene regulatory network that controls PVD synthesis in P. aeruginosa strain PAO1; (ii) construction, curating, and modeling of the metabolic network of P. aeruginosa using the flux balance analysis (FBA) approach; (iii) integration and modeling of these two networks into an integrative model using the dynamic flux balance analysis (DFBA) approximation, followed, finally, by an in vitro validation of the integrated model for PVD synthesis in P. aeruginosa as a function of QS signaling. The QS gene network, constructed using the standard System Biology Markup Language, comprised 114 chemical species and 103 reactions and was modeled as a deterministic system following the kinetic based on mass action law. This model showed that the higher the bacterial growth, the higher the extracellular concentration of QS signal molecules, thus emulating the natural behavior of P. aeruginosa PAO1. The P. aeruginosa metabolic network model was constructed based on the iMO1056 model, the P. aeruginosa PAO1 strain genomic annotation, and the metabolic pathway of PVD synthesis. The metabolic network model included the PVD synthesis, transport, exchange reactions, and the QS signal molecules. This metabolic network model was curated and then modeled under the FBA approximation, using biomass maximization as the objective function (optimization problem, a term borrowed from the engineering field). Next, chemical reactions shared by both network models were chosen to combine them into an integrative model. To this end, the fluxes of these reactions, obtained from the QS network model, were fixed in the metabolic network model as constraints of the optimization problem using the DFBA approximation. Finally, simulations of the integrative model (CCBM1146, comprising 1123 reactions and 880 metabolites) were run using the DFBA approximation to get (i) the flux profile for each reaction, (ii) the bacterial growth profile, (iii) the biomass profile, and (iv) the concentration profiles of metabolites of interest such as glucose, PVD, and QS signal molecules. The CCBM1146 model showed that the QS phenomenon directly influences the P. aeruginosa metabolism to PVD biosynthesis as a function of the change in QS signal intensity. The CCBM1146 model made it possible to characterize and explain the complex and emergent behavior generated by the interactions between the two networks, which would have been impossible to do by studying each system's individual components or scales separately. This work is the first in silico report of an integrative model comprising the QS gene regulatory network and the metabolic network of P. aeruginosa.

Omics approaches to understand cocoa processing and chocolate flavor development: A review.

The global market of chocolate has increased worldwide during the last decade and is expected to reach a value of USD 200 billion by 2028. Chocolate is obtained from different varieties of Theobroma cacao L, a plant domesticated more than 4000 years ago in the Amazon rainforest. However, chocolate production is a complex process requiring extensive post-harvesting, mainly involving cocoa bean fermentation, drying, and roasting. These steps have a critical impact on chocolate quality. Standardizing and better understanding cocoa processing is, therefore, a current challenge to boost the global production of high-quality cocoa worldwide. This knowledge can also help cocoa producers improve cocoa processing management and obtain a better chocolate. Several recent studies have been conducted to dissect cocoa processing via omics analysis. A vast amount of data has been produced regarding omics studies of cocoa processing performed worldwide. This review systematically analyzes the current data on cocoa omics using data mining techniques and discusses opportunities and gaps for cocoa processing standardization from this data. First, we observed a recurrent report in metagenomics studies of species of the fungi genus Candida and Pichia as well as bacteria from the genus Lactobacillus, Acetobacter, and Bacillus. Second, our analyzes of the available metabolomics data showed clear differences in the identified metabolites in cocoa and chocolate from different geographical origin, cocoa type, and processing stage. Finally, our analysis of peptidomics data revealed characteristic patterns in the gathered data including higher diversity and lower size distribution of peptides in fine-flavor cocoa. In addition, we discuss the current challenges in cocoa omics research. More research is still required to fill gaps in central matter in chocolate production as starter cultures for cocoa fermentation, flavor evolution of cocoa, and the role of peptides in the development of specific flavor notes. We also offer the most comprehensive collection of multi-omics data in cocoa processing gathered from different research articles.

Genotype and Phenotype Characterization of Patients with Mucopolysaccharidosis IV-A in Chile.

Introduction: Morquio syndrome or mucopolysaccharidosis type IV-A (MPS IV-A) is an autosomal recessive disease caused by biallelic variants in the GALNS gene, encoding the lysosomal enzyme GalN6S, responsible for glycosaminoglycan keratan sulfate and chondroitin-6-sulfate degradation. Studies have shown that the degree of evolutionary and chemical divergence of missense variants in GalN6S when compared to ancestral amino acids is associated with the severity of the syndrome, suggesting a genotype-phenotype correlation. There is little information on Latin American patients with MPS IV-A that replicate these findings. This study aimed to characterize the phenotype and genotype from patients with MPS IV-A, who are under Enzyme Replacement Therapy at the Children's Neuropsychiatry Service of the Hospital Clínico San Borja Arriarán, Santiago, Chile, and to determine if there is any association between genotype and phenotype with those findings. Methods: Information was collected from medical charts, all patients went through a GalN6S enzymatic activity measurement in leukocytes from peripheral blood, and the GALNS gene was sequenced for all cases. Results: 12 patients with MPS IV-A were recruited, all patients presented multisystem involvement, mostly skeletal, and 75% of cases underwent surgical interventions, and cervical arthrodesis was the most frequent procedure. In regards of the genotype, the two most frequent variants were c.319+2T>C (n = 10, 41.66%) and p.(Arg386Cys) (n = 8, 33.33%), the first one was previously described in 2018 in a patient from Chile [Bochernitsan et al., 2018]. Conclusion: This is the first time that a genotype-phenotype correlation has been studied by analyzing the variants effect on the molecular structure of human GalN6S and the evolutionary conservation degree of affected residues in a cohort of patients in Chile. Albeit our work could not find statistically significant associations, we may infer that the evolutionary conservations of affected amino acids and the effect of variants on enzyme structure may play a main role. Further analyzes should consider a meta-analysis of published cases with genotype data and larger samples and include other variables that could provide more information. Finally, our data strongly suggest that variant c.319+2T>C could have a founder effect in Chilean patients with MPS IV-A.

Exploring the Spectrum of RHOBTB2 Variants Associated with Developmental Encephalopathy 64: A Case Series and Literature Review.

Background: Rho-related BTB domain-containing protein 2 (RHOBTB2) is a protein that interacts with cullin-3, a crucial E3 ubiquitin ligase for mitotic cell division. RHOBTB2 has been linked to early infantile epileptic encephalopathy, autosomal dominant type 64 (OMIM618004), in 34 reported patients. Methods: We present a case series of seven patients with RHOBTB2-related disorders (RHOBTB2-RD), including a description of a novel heterozygous variant. We also reviewed previously published cases of RHOBTB2-RD. Results: The seven patients had ages ranging from 2 years and 8 months to 26 years, and all had experienced seizures before the age of one (onset, 4-12 months, median, 4 months), including various types of seizures. All patients in this cohort also had a movement disorder (onset, 0.3-14 years, median, 1.5 years). Six of seven had a baseline movement disorder, and one of seven only had paroxysmal dystonia. Stereotypies were noted in four of six, choreodystonia in three of six, and ataxia in one case with multiple movement phenotypes at baseline. Paroxysmal movement disorders were observed in six of seven patients for whom carbamazepine or oxcarbazepine treatment was effective in controlling acute or paroxysmal movement disorders. Four patients had acute encephalopathic episodes at ages 4 (one patient) and 6 (three patients), which improved following treatment with methylprednisolone. Magnetic resonance imaging scans revealed transient fluid-attenuated inversion recovery abnormalities during these episodes, as well as myelination delay, thin corpus callosum, and brain atrophy. One patient had a novel RHOBTB2 variant (c.359G>A/p.Gly120Glu). Conclusion: RHOBTB2-RD is characterized by developmental delay or intellectual disability, early-onset seizures, baseline movement disorders, acute or paroxysmal motor phenomena, acquired microcephaly, and episodes of acute encephalopathy. Early onsets of focal dystonia, acute encephalopathic episodes, episodes of tongue protrusion, or peripheral vasomotor disturbances are important diagnostic clues. Treatment with carbamazepine or oxcarbazepine was found to be effective in controlling acute or paroxysmal movement disorders. Our study highlights the clinical features and treatment response of RHOBTB2-RD.

Multifunctional magnetoliposomes as drug delivery vehicles for the potential treatment of Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Therefore, development of novel technologies and strategies to treat PD is a global health priority. Current treatments include administration of Levodopa, monoamine oxidase inhibitors, catechol-O-methyltransferase inhibitors, and anticholinergic drugs. However, the effective release of these molecules, due to the limited bioavailability, is a major challenge for the treatment of PD. As a strategy to solve this challenge, in this study we developed a novel multifunctional magnetic and redox-stimuli responsive drug delivery system, based on the magnetite nanoparticles functionalized with the high-performance translocating protein OmpA and encapsulated into soy lecithin liposomes. The obtained multifunctional magnetoliposomes (MLPs) were tested in neuroblastoma, glioblastoma, primary human and rat astrocytes, blood brain barrier rat endothelial cells, primary mouse microvascular endothelial cells, and in a PD-induced cellular model. MLPs demonstrated excellent performance in biocompatibility assays, including hemocompatibility (hemolysis percentages below 1%), platelet aggregation, cytocompatibility (cell viability above 80% in all tested cell lines), mitochondrial membrane potential (non-observed alterations) and intracellular ROS production (negligible impact compared to controls). Additionally, the nanovehicles showed acceptable cell internalization (covered area close to 100% at 30 min and 4 h) and endosomal escape abilities (significant decrease in lysosomal colocalization after 4 h of exposure). Moreover, molecular dynamics simulations were employed to better understand the underlying translocating mechanism of the OmpA protein, showing key findings regarding specific interactions with phospholipids. Overall, the versatility and the notable in vitro performance of this novel nanovehicle make it a suitable and promising drug delivery technology for the potential treatment of PD.

Design and Assembly of a Biofactory for (2S)-Naringenin Production in Escherichia coli: Effects of Oxygen Transfer on Yield and Gene Expression.

The molecule (2S)-naringenin is a scaffold molecule with several nutraceutical properties. Currently, (2S)-naringenin is obtained through chemical synthesis and plant isolation. However, these methods have several drawbacks. Thus, heterologous biosynthesis has emerged as a viable alternative to its production. Recently, (2S)-naringenin production studies in Escherichia coli have used different tools to increase its yield up to 588 mg/L. In this study, we designed and assembled a bio-factory for (2S)-naringenin production. Firstly, we used several parametrized algorithms to identify the shortest pathway for producing (2S)-naringenin in E. coli, selecting the genes phenylalanine ammonia lipase (pal), 4-coumarate: CoA ligase (4cl), chalcone synthase (chs), and chalcone isomerase (chi) for the biosynthetic pathway. Then, we evaluated the effect of oxygen transfer on the production of (2S)-naringenin at flask (50 mL) and bench (4 L culture) scales. At the flask scale, the agitation rate varied between 50 rpm and 250 rpm. At the bench scale, the dissolved oxygen was kept constant at 5% DO (dissolved oxygen) and 40% DO, obtaining the highest (2S)-naringenin titer (3.11 ± 0.14 g/L). Using genome-scale modeling, gene expression analysis (RT-qPCR) of oxygen-sensitive genes was obtained.

Enhancing Wound Healing: A Novel Topical Emulsion Combining CW49 Peptide and Lavender Essential Oil for Accelerated Regeneration and Antibacterial Protection.

Wound healing is a complex process involving blood cells, extracellular matrix, and parenchymal cells. Research on biomimetics in amphibian skin has identified the CW49 peptide from Odorrana grahami, which has been demonstrated to promote wound regeneration. Additionally, lavender essential oil exhibits anti-inflammatory and antibacterial activities. Given these considerations, we propose an innovative emulsion that combines the CW49 peptide with lavender oil. This novel formulation could serve as a potent topical treatment, potentially fostering the regeneration of damaged tissues and providing robust antibacterial protection for skin wounds. This study investigates the physicochemical properties, biocompatibility, and in vitro regenerative capacity of the active components and the emulsion. The results show that the emulsion possesses appropriate rheological characteristics for topical application. Both the CW49 peptide and lavender oil exhibit high viability in human keratinocytes, indicating their biocompatibility. The emulsion induces hemolysis and platelet aggregation, an expected behavior for such topical treatments. Furthermore, the lavender-oil emulsion demonstrates antibacterial activity against both Gram-positive and Gram-negative bacterial strains. Finally, the regenerative potential of the emulsion and its active components is confirmed in a 2D wound model using human keratinocytes. In conclusion, the formulated emulsion, which combines the CW49 peptide and lavender oil, shows great promise as a topical treatment for wound healing. Further research is needed to validate these findings in more advanced in vitro models and in vivo settings, potentially leading to improved wound-care management and novel therapeutic options for patients with skin injuries.

Genome-Scale Metabolic Reconstruction, Non-Targeted LC-QTOF-MS Based Metabolomics Data, and Evaluation of Anticancer Activity of Cannabis sativa Leaf Extracts.

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.

Teleworking and technostress: early consequences of a COVID-19 lockdown.

This paper analyzes teleworkers' technostress evolution over time, as well as its effects on these individuals' work-related well-being over time. The proposed research model was tested using a survey-based longitudinal study with individuals that forcibly moved to teleworking in the context of a COVID-19 lockdown at two points in time (T0 and T1). Results indicate that two techno-stressors (work-home conflict and work overload) generated strain in teleworkers, which in turn decreased their satisfaction with telework and perceived job performance. In addition, teleworkers experienced two types of enduring technostress: synchronous effect (i.e., stressors generating strain at T1), and a cumulative reverse causation effect (i.e., strain at T0 has an effect on stressors at T1). These findings contribute to cognition, work, and technology literature by providing a more complete understanding of teleworkers' technostress and its possible cumulative effects over time. Practical insights for managing technostress when moving to and remaining in teleworking are provided.