Pembrolizumab for advanced urothelial carcinoma: exploratory ctDNA biomarker analyses of the KEYNOTE-361 phase 3 trial.

Circulating tumor DNA (ctDNA) is emerging as a potential biomarker in early-stage urothelial cancer but its utility in metastatic disease remains unknown. In the phase 3 KEYNOTE-361 study, pembrolizumab with and without chemotherapy was compared with chemotherapy alone in patients with metastatic urothelial cancer. The study did not meet prespecified efficacy thresholds for statistical significance. To identify potential biomarkers of response, we retrospectively evaluated association of pre- and post-treatment ctDNA with clinical outcomes in a subset of patients who received pembrolizumab (n = 130) or chemotherapy (n = 130) in KEYNOTE-361. Baseline ctDNA were associated with best overall response (BOR;P = 0.009), progression-free survival (PFS;P < 0.001), and overall survival (OS;P < 0.001) for pembrolizumab, but not chemotherapy (all, P > 0.05). Chemotherapy induced larger ctDNA decreases from baseline to treatment cycle 2 than pembrolizumab; however, change with pembrolizumab (n = 87) were more associated with BOR (P = 4.39 × 10-5) and OS (P = 7.07 × 10-5) versus chemotherapy (n = 102; BOR: P = 1.01 × 10-4; OS: P = 0.018). Tumor tissue-informed versions of ctDNA change metrics were most associated with clinical outcomes but did not show statistically significant independent value for explaining OS beyond radiographic change by RECIST v1.1 when jointly modeled (pembrolizumab P = 0.364; chemotherapy P = 0.823). These results suggest distinct patterns in early ctDNA changes with immunotherapy and chemotherapy and differences in their association with long-term outcomes, which provide preliminary insights on the utility of liquid biopsies for treatment monitoring in metastatic urothelial cancer. Clinical trial registration: NCT02853305.

Eosinophil-derived extracellular vesicles: isolation and classification techniques and implications for disease pathophysiology.

Eosinophils are leukocytes characterized by their ability to release granule content that is highly rich in enzymes and proteins. Besides the anti-helminthic, bactericidal, and antiviral properties of eosinophils and their secretory granules, these also play a prominent role in the pathophysiology of diseases like asthma, eosinophilic esophagitis, and other hypereosinophilic conditions by causing tissue damage and airway hyperresponsiveness. Although this cell was first recognized mainly for its capacity to release granule content, nowadays other capabilities such as cytokine secretion have been linked to its physiology, and research has found that eosinophils are not only involved in innate immunity, but also as orchestrators of immune responses. Nearly 10 years ago, eosinophil-derived extracellular vesicles (EVs) were first described; since then, the EV field has grown exponentially, revealing their vital roles in intracellular communication. In this review, we synthesize current knowledge on eosinophil-derived EVs, beginning with a description of what they are and what makes them important regulators of disease, followed by an account of the methodologies used to isolate and characterize EVs. We also summarize current understanding of eosinophil-derived vesicles functionality, especially in asthma, the disease in which eosinophil-derived EVs have been most widely studied, describing how they modulate the role of eosinophils themselves (through autocrine signaling) and the way they affect airway structural cells and airway remodeling. Deeper understanding of this cell type could lead to novel research in eosinophil biology, its role in other diseases, and possible use of eosinophil-derived EVs as therapeutic targets.

Maternal Education and Children Home Alone in 63 Low- and Middle-Income Countries.

Background. Maternal education may influence child supervision practices in low-and middle-income countries (LMIC). However, little is known about the maternal factors that can improve child supervision in LMIC with scarce childcare facilities. Objective. To investigate the prevalence of children under 5 years home alone and examine the association between mother's formal education and children home alone across 63 LMIC. Methods. The study used data from 50 Multiple Indicator Cluster Surveys and 13 Demographic and Health Surveys with a sample of 501 769 children. We estimated Prevalence Ratios (PRs) for the association between maternal education and children home alone using multivariable Poisson regression, adjusting for covariates such as child's age and sex, mother's age and marital status, number of adults inhabiting the households, and urbanicity. Results. Prevalence of children home alone across 63 LMIC ranged from 1.1% to 50.1%. A significant negative association between mothers with more years of formal education and children home alone was found across 16 LMIC. However, the opposite trend was observed in Nigeria, Senegal, and Côte d'Ivoire. Null association was found across 44 LMIC. Conclusions. The varied pattern of the associations observed across LMIC underscores the importance of regional and local factors when developing policies and interventions to ensure safety and adequate care for children aged under 5 years in LMIC.

Gut microbiota composition in travellers is associated with faecal lipocalin-2, a mediator of gut inflammation.

Introduction: We examined the gut microbiota of travellers returning from tropical areas with and without traveller's diarrhoea (TD) and its association with faecal lipocalin-2 (LCN2) levels. Methods: Participants were recruited at the Hospital Clinic of Barcelona, Spain, and a single stool sample was collected from each individual to perform the diagnostic of the etiological agent causing gastrointestinal symptoms as well as to measure levels of faecal LCN2 as a biomarker of gut inflammation. We also characterised the composition of the gut microbiota by sequencing the region V3-V4 from the 16S rRNA gene, and assessed its relation with the clinical presentation of TD and LCN2 levels using a combination of conventional statistical tests and unsupervised machine learning approaches. Results: Among 61 participants, 45 had TD, with 40% having identifiable etiological agents. Surprisingly, LCN2 levels were similar across groups, suggesting gut inflammation occurs without clinical TD symptoms. Differential abundance (DA) testing highlighted a microbial profile tied to high LCN2 levels, marked by increased Proteobacteria and Escherichia-Shigella, and decreased Firmicutes, notably Oscillospiraceae. UMAP analysis confirmed this profile's association, revealing distinct clusters based on LCN2 levels. The study underscores the discriminatory power of UMAP in capturing meaningful microbial patterns related to clinical variables. No relevant differences in the gut microbiota composition were found between travellers with or without TD. Discussion: The findings suggest a correlation between gut microbiome and LCN2 levels during travel, emphasising the need for further research to discern the nature of this relationship.

Two extracellular α-arabinofuranosidases are required for cereal-derived arabinoxylan metabolism by Bifidobacterium longum subsp. longum.

Members of the genus Bifidobacterium are commonly found in the human gut and are known to utilize complex carbohydrates that are indigestible by the human host. Members of the Bifidobacterium longum subsp. longum taxon can metabolize various plant-derived carbohydrates common to the human diet. To metabolize such polysaccharides, which include arabinoxylan, bifidobacteria need to encode appropriate carbohydrate-active enzymes in their genome. In the current study, we describe two GH43 family enzymes, denoted here as AxuA and AxuB, which are encoded by B. longum subsp. longum NCIMB 8809 and are shown to be required for cereal-derived arabinoxylan metabolism by this strain. Based on the observed hydrolytic activity of AxuA and AxuB, assessed by employing various synthetic and natural substrates, and based on in silico analyses, it is proposed that both AxuA and AxuB represent extracellular α-L-arabinofuranosidases with distinct substrate preferences. The variable presence of the axuA and axuB genes and other genes previously described to be involved in the metabolism of arabinose-containing glycans can in the majority cases explain the (in)ability of individual B. longum subsp. longum strains to grow on cereal-derived arabinoxylans and arabinan.

Different Diagnostic Criteria for Determining the Prevalence of Sarcopenia in Older Adults: A Systematic Review.

Background: Sarcopenia is defined as a loss of muscle mass, strength, and physical function associated with aging. It is due to a combination of genetic, environmental, and physiological factors. It is also associated with an increased risk of health problems. Since there are many different researchers in the field, with their own algorithms and cut-off points, there is no single criterion for diagnosis. This review aims to compare the prevalence of sarcopenia according to these different diagnostic criteria in older adult populations by age group and sex. Methods: Different databases were searched: Web of Science, Pubmed, Dialnet, Scopus, and Cochrane. The keywords used were "sarcopenia", "diagnosis", "prevalence", "assessment", "aged", "aging" and "older". Studies conducted in a population aged ≥65 assessing the prevalence of sarcopenia were selected. Results: Nineteen articles met the inclusion criteria, with a total of 33,515 subjects, 38.08% female and 61.42% male, at a mean age of 74.52. The diagnostic algorithms used were 52.63% AWGS2, 21.05% EWGSOP2, 10.53% AWGS1 and EWGS1, and 5.26% FNIH. Prevalence ranged from 1.7% to 37.47%, but was higher in males and increased with age. Conclusions: The prevalence of sarcopenia varies depending on the diagnostic algorithm used, but it increases with age and is higher in men. The EWGSOP2 and AWGS2 are the most used diagnostic criteria and measure the same variables but have different cut-off points. Of these two diagnostic algorithms, the one with the highest prevalence of sarcopenia and severe sarcopenia is the AWGS2. These differences may be due to the use of different tools and cut-off points. Therefore, a universal diagnostic criterion should be developed to allow early diagnosis of sarcopenia.

Supplementing infant milk formula with a multi-strain synbiotic and osteopontin enhances colonic microbial colonization and modifies jejunal gene expression in lactating piglets.

A total of ninety-six weaned piglets were assigned to four dietary treatments in a 2 × 2 design. The treatments included: a standard milk formula (CTR); CTR + probiotics (6.4 × 108 cfu L-1Bifidobacterium longum subsp. infantis CECT 7210 and 1.1 × 108 cfu L-1Lactobacillus rhamnosus NH001) + prebiotics (galacto-oligosaccharides 4.36 g L-1 and human-milk-oligosaccharide 0.54 g L-1) (SYN); CTR + osteopontin (0.43 g L-1) (OPN); and CTR + SYN + OPN (CON). Daily records including feed intake, body weight, and clinical signs, were maintained throughout the 15-day trial. At the end of the study samples from blood, digestive content, and gut tissues were collected to determine serum TNF-α, intestinal fermentative activity (SCFA and ammonia), colonic microbiota (16S rRNA Illumina-MiSeq), histomorphology, and jejunal gene expression (Open-Array). No statistical differences were found in weight gain; however, the animals supplemented with osteopontin exhibited higher feed intake. In terms of clinical signs, synbiotic supplementation led to a shorter duration of diarrhoea episodes. Regarding gut health, the sequenced faecal microbiota revealed better control of potentially dysbiotic bacteria with the CON diet at day 15. In the colon compartment, a significant increase in SCFA concentration, a decrease in ammonia concentration, and a significant decrease in intraepithelial lymphocyte counts were particularly observed in CON animals. The supplemented diets were also associated with modified jejunal gene expression. The synbiotic combination was characterized by the upregulation of genes related to intestinal maturation (ALPI, SI) and nutrient transport (SLC13A1, SLC15A1, SLC5A1, SLC7A8), and the downregulation of genes related to the response to pathogens (GBP1, IDO, TLR4) or the inflammatory response (IDO, IL-1ß, TGF-ß1). Osteopontin promoted the upregulation of a digestive function gene (GCG). Correlational analysis between the microbiota population and various intestinal environmental factors (SCFA concentration, histology, and gene expression) proposes mechanisms of communication between the gut microbiota and the host. In summary, these results suggest an improvement in the colonic colonization process and a better modulation of the immune response when milk formula is supplemented with the tested synbiotic combined with osteopontin, benefiting from a synergistic effect.

Advancements in dementia research, diagnostics, and care in Latin America: Highlights from the 2023 Alzheimer's Association International conference satellite symposium in Mexico City.

INTRODUCTION: While Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care. METHODS: In 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm. RESULTS: Significant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted. DISCUSSION: The myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.

Tobacco policies and changes in the tendency of smoking cessation in cigarette users in Chile: a longitudinal cross-sectional study.

OBJECTIVE: To assess the impact of tobacco control regulations and policy implementation on smoking cessation tendencies in cigarette users born between 1982 and 1991 in Chile. DESIGN: Longitudinal cross-sectional study. SETTING: National level. PARTICIPANTS: Data from the National Survey of Drug Consumption (Service of Prevention and Rehabilitation for Drug and Alcohol Consumption). A pseudo-cohort of smokers born between 1982 and 1991 (N=17 905) was tracked from 2002 to 2016. PRIMARY AND SECONDARY OUTCOMES MEASURES: Primary outcome was the tendency to cease smoking conceptualised as the report of using cigarettes 1 month or more ago relative to using cigarettes in the last 30 days. The main exposure variable was the Tobacco Policy Index-tracking tobacco policy changes over time. Logistic regression, controlling for various factors, was applied. RESULTS: Models suggested a 14% increase in the smoking cessation tendency of individuals using cigarettes 1 month or more ago relative to those using cigarettes in the last 30 days (OR 1.14, CI 95% CI 1.10 to 1.19) for each point increment in the Tobacco Policy index. CONCLUSIONS: Our study contributes to documenting a positive impact of the implementation of interventions considered in the MPOWER strategy in the progression of smoking cessation tendencies in smokers born between 1982 and 1991 in Chile.

Reactivation of Trypanosoma cruzi infection in immunosuppressed patients: a systematic review and meta-analysis.

BACKGROUND: The risk of Trypanosoma cruzi reactivation is poorly understood. Previous studies evaluating the risk of reactivation report imprecise findings, and recommendations for monitoring and management from clinical guidelines rely on consensus opinion. OBJECTIVES: We conducted a systematic review and meta-analysis to estimate the cumulative T. cruzi reactivation incidence in immunosuppressed adults, summarize the available evidence on prognostic factors for reactivation, and examine its prognostic effect on mortality. DATA SOURCES: MEDLINE, Embase, LILACS, Clinical Trials, and CENTRAL from inception to 4 July 2022. STUDY ELIGIBILITY CRITERIA: Studies reporting the incidence of T. cruzi reactivation. PARTICIPANTS: Immunosuppressed adults chronically infected by T. cruzi. METHODS: Two authors independently extracted data (including, but not limited to, incidence data, reactivation definition, follow-up, treatment, monitoring schedule, examined prognostic factors) and evaluated the risk of bias. We pooled cumulative incidence using a random-effects model. RESULTS: Twenty-two studies (806 participants) were included. The overall pooled incidence of T. cruzi reactivation was 27% (95% CI, 19-36), with the highest pooled proportion in the sub-group of transplant recipients (36%; 95% CI, 25-48). The highest risk period was in the first 6 months after transplant (32%; 95% CI, 17-58), decreasing drastically the number of new cases later. People living with HIV and patients with autoimmune diseases experienced significantly lower cumulative reactivation incidences (17%; 95% CI, 8-29 and 18%; 95% CI, 9-29, respectively). A single study explored the independent effect of benznidazole and found benefits for preventing reactivations. No studies evaluated the independent association between reactivation and mortality, while sensitivity analysis results using unadjusted estimates were inconclusive. The heterogeneity of diagnostic algorithms was substantial. CONCLUSIONS: Reactivation occurs in three out of ten T. cruzi-seropositive immunosuppressed adults. These findings can assist clinicians and panel guidelines in tailoring monitoring schedules. There is a great need for an accurate definition of reactivation and targeted monitoring.

A Principled Approach to Characterize and Analyze Partially Observed Confounder Data from Electronic Health Records.

Objective: Partially observed confounder data pose challenges to the statistical analysis of electronic health records (EHR) and systematic assessments of potentially underlying missingness mechanisms are lacking. We aimed to provide a principled approach to empirically characterize missing data processes and investigate performance of analytic methods. Methods: Three empirical sub-cohorts of diabetic SGLT2 or DPP4-inhibitor initiators with complete information on HbA1c, BMI and smoking as confounders of interest (COI) formed the basis of data simulation under a plasmode framework. A true null treatment effect, including the COI in the outcome generation model, and four missingness mechanisms for the COI were simulated: completely at random (MCAR), at random (MAR), and two not at random (MNAR) mechanisms, where missingness was dependent on an unmeasured confounder and on the value of the COI itself. We evaluated the ability of three groups of diagnostics to differentiate between mechanisms: 1)-differences in characteristics between patients with or without the observed COI (using averaged standardized mean differences [ASMD]), 2)-predictive ability of the missingness indicator based on observed covariates, and 3)-association of the missingness indicator with the outcome. We then compared analytic methods including "complete case", inverse probability weighting, single and multiple imputation in their ability to recover true treatment effects. Results: The diagnostics successfully identified characteristic patterns of simulated missingness mechanisms. For MAR, but not MCAR, the patient characteristics showed substantial differences (median ASMD 0.20 vs 0.05) and consequently, discrimination of the prediction models for missingness was also higher (0.59 vs 0.50). For MNAR, but not MAR or MCAR, missingness was significantly associated with the outcome even in models adjusting for other observed covariates. Comparing analytic methods, multiple imputation using a random forest algorithm resulted in the lowest root-mean-squared-error. Conclusion: Principled diagnostics provided reliable insights into missingness mechanisms. When assumptions allow, multiple imputation with nonparametric models could help reduce bias.

Machine learning approach to identify malaria risk in travelers using real-world evidence.

Background: Pre-travel consultation and chemoprophylaxis measures for malaria are a key component in the prevention of imported malaria in travelers. In this study we report a predictive tool for assessing personalized malaria risk in travelers based on the analysis of electronic medical records from travel consultations. The tool aims to guide physicians in the recommendation of appropriate prophylaxis prior to their trip. We also provide best-practice recommendations for pre-processing noisy and highly sparse real world evidence data. Methods: We leveraged a large EMR dataset, containing demographic information about travelers and their destination. The data has been previously preprocessed using various strategies to handle missing and unbalanced data. We compared multiple machine learning approaches to assess the risk of malaria acquisition in travelers during their travels. Additionally, a feature importance analysis was performed using SHAP (SHapley Additive Explanations) values to identify patterns associated with malaria risk. Results: Our study revealed that our XGB models achieved high predictive capacity (AUC >0.80). The most significant features predicting malaria infection during travel included travel destinations with low malaria risk, vaccination history, number of countries visited, age, and trip duration. Remarkably, we were able to obtain a reduced model with only five features. When comparing this model with a population of travelers recommended for malaria chemoprophylaxis, we observed that it was deemed necessary in only 40% of these travelers. This suggests that 60% received chemoprophylaxis despite having a low personalized risk of malaria. Conclusion: We have developed an algorithmic tool that utilizes a concise survey to generate a personalized travel risk assessment, effectively minimizing the prescription of unnecessary malaria chemoprophylaxis. Through the identification of patterns linked to predictions, our model significantly enhances the efficacy of pre-travel consultations.

Prevalence of diagnosed and undiagnosed osteoarthrosis and associated factors in the adult general Spanish population.

OBJECTIVE: To determine the prevalence and related factors of diagnosed osteoarthrosis (DO) and undiagnosed osteoarthrosis (UO) in the general Spanish adult population. SETTING: Cross-sectional study with data from the Spanish National Health Survey 2017. PARTICIPANTS: N=23,089 adults. Three groups of people were defined: DO, UO, and no osteoarthrosis (NO). MAIN MEASUREMENTS: Sociodemographic information, lifestyle (tobacco, alcohol, physical activity, body mass index) and health factors (intensity of pain, pain drug consumption, mental health, self-perceived health status, pain involvement in daily living) were collected. Descriptive and bivariate analyses were performed, and a multinomial logistic regression model for the factors associated with each group. RESULTS: The prevalence of DO was 22.4% (95%CI=21.8;22.9) and 0.9% (95%CI=0.8;1) of UO. With respect to NO, risk factors for DO and UO included higher pain levels and pain drug consumption. Better self-perceived health status was inversely related with both. More pain involvement in daily living was associated with increased risk of DO, but reduced risk of UO. CONCLUSIONS: The prevalence of DO and UO was similar to that reported in Europe, but slightly higher than in low/middle-income countries. It was more prevalent in females, older people, people with worse perceived health status and worse mental health. Higher pain levels and pain drug consumption were risk factors for DO and UO. Better self-perceived health status was protective. Pain involvement in daily living was a risk factor for DO, but protective for UO. Different public health strategies should be considered in view of this.

Gene expression alterations of purinergic signaling components in obesity-associated intestinal low-grade inflammation in type 2 diabetes.

Intestinal low-grade inflammation induced by a high-fat diet has been found to detonate chronic systemic inflammation, which is a hallmark of obesity, and precede the apparition of insulin resistance, a key factor for developing type 2 diabetes (T2D). Aberrant purinergic signaling pathways have been implicated in the pathogenesis of inflammatory bowel disease and other gastrointestinal diseases. However, their role in the gut inflammation associated with obesity and T2D remains unexplored. C57BL/6 J mice were fed a cafeteria diet for 21 weeks and received one injection of streptozotocin in their sixth week into the diet. The gene expression profile of purinergic signaling components in colon tissue was assessed by RT-qPCR. Compared to control mice, the treated group had a significant reduction in colonic length and mucosal and muscular layer thickness accompanied by increased NF-κB and IL-1ß mRNA expression. Furthermore, colonic P2X2, P2X7, and A3R gene expression levels were lower, while the P2Y2, NT5E, and ADA expression levels increased. In conclusion, these data suggest that these purinergic signaling components possibly play a role in intestinal low-grade inflammation associated with obesity and T2D and thus could represent a novel therapeutic target for the treatment of the metabolic complications related to these diseases.

A case of possible transfusion-acquired malaria in Zaragoza, Spain.

We present the case of a 75-year-old patient diagnosed with malaria, a native of Zaragoza, Spain, despite having no travel history to malaria-endemic regions. Following an extensive investigation, transfusion emerged as the most probable mode of transmission.

MALrisk: a machne-learning based tool to predict imported malaria in returned travellers with fever.

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence could improve the management of febrile travellers. METHODS: Data from a multicentric prospective study of febrile travellers was obtained to build a machine-learning model to predict malaria cases among travellers presenting with fever. Demographic characteristics, clinical and laboratory variables were leveraged as features. Eleven machine-learning classification models were evaluated by 50-fold cross-validation in a Training set. Then, the model with the best performance, defined by the Area Under the Curve (AUC), was chosen for parameter optimization and evaluation in the Test set. Finally, a reduced model was elaborated with those features that contributed most to the model. RESULTS: Out of eleven machine-learning models, XGBoost presented the best performance (mean AUC of 0.98 and a mean F1 score of 0.78). A reduced model (MALrisk) was developed using only six features: Africa as a travel destination, platelet count, rash, respiratory symptoms, hyperbilirubinemia and chemoprophylaxis intake. MALrisk predicted malaria cases with 100% (95%CI 96-100) sensitivity and 72% (95%CI 68-75) specificity. CONCLUSIONS: The MALrisk can aid in the timely identification of malaria in non-endemic settings, allowing the initiation of empiric antimalarials and reinforcing the need for urgent transfer in healthcare facilities with no access to malaria diagnostic tests. This resource could be easily scalable to a digital application and could reduce the morbidity associated with late diagnosis.

Structural characterization of two nanobodies targeting the ligand-binding pocket of human Arc.

The activity-regulated cytoskeleton-associated protein (Arc) is a complex regulator of synaptic plasticity in glutamatergic neurons. Understanding its molecular function is key to elucidate the neurobiology of memory and learning, stress regulation, and multiple neurological and psychiatric diseases. The recent development of anti-Arc nanobodies has promoted the characterization of the molecular structure and function of Arc. This study aimed to validate two anti-Arc nanobodies, E5 and H11, as selective modulators of the human Arc N-lobe (Arc-NL), a domain that mediates several molecular functions of Arc through its peptide ligand binding site. The structural characteristics of recombinant Arc-NL-nanobody complexes were solved at atomic resolution using X-ray crystallography. Both anti-Arc nanobodies bind specifically to the multi-peptide binding site of Arc-NL. Isothermal titration calorimetry showed that the Arc-NL-nanobody interactions occur at nanomolar affinity, and that the nanobodies can displace a TARPγ2-derived peptide from the binding site. Thus, both anti-Arc-NL nanobodies could be used as competitive inhibitors of endogenous Arc ligands. Differences in the CDR3 loops between the two nanobodies indicate that the spectrum of short linear motifs recognized by the Arc-NL should be expanded. We provide a robust biochemical background to support the use of anti-Arc nanobodies in attempts to target Arc-dependent synaptic plasticity. Function-blocking anti-Arc nanobodies could eventually help unravel the complex neurobiology of synaptic plasticity and allow to develop diagnostic and treatment tools.

Considerations about the inhibition of monophenolase and diphenolase activities of tyrosinase. Characterization of the inhibitor concentration which generates 50 % of inhibition, type and inhibition constants. A review.

Tyrosinase is a copper oxidase enzyme which catalyzes the first two steps in the melanogenesis pathway, L-tyrosine to L-dopa conversion and, then, to o-dopaquinone and dopachrome. Hypopigmentation and, above all, hyperpigmentation issues can be originated depending on their activity. This enzyme also promotes the browning of fruits and vegetables. Therefore, control of their activity by regulators is research topic of great relevance. In this work, we consider the use of inhibitors of monophenolase and diphenolase activities of the enzyme in order to accomplish such control. An experimental design and data analysis which allow the accurate calculation of the degree of inhibition of monophenolase activity (iM) and diphenolase activity (iD) are proposed. The IC50 values (amount of inhibitor that causes 50 % inhibition at a fixed substrate concentration) can be calculated for the two activities and from the values of IC50M (monophenolase) and IC50D(diphenolase). Additionally, the strength and type of inhibition can be deduced from these values. The data analysis from these IC50D values allows to obtain the values of [Formula: see text] or [Formula: see text] , or and [Formula: see text] from the values of IC50M. In all cases, the values of the different must satisfy their relationship with IC50M and IC50D.