Exhaled Nitric Oxide fraction in asthma and obstructive sleep apnea among children at high altitudes. A cross-sectional study.

INTRODUCTION: Exhaled nitric oxide fraction (FeNO) is employed for the diagnosis and phenotyping of asthma as an inflammatory biomarker of the airway. Limited evidence exists regarding its behavior in the presence of asthma and obstructive sleep apnea (OSA). Our objective was to determine whether FeNO levels are associated with the severity of OSA or the coexistence of asthma and OSA in residents at high altitudes. MATERIALS AND METHODS: Observational, analytical, cross-sectional study in children aged 5-16 years residing at 2600 m above sea level treated at a Sleep Study Center between 2019 and 2021. We conducted a medical history, polysomnogram, and measurement of FeNO levels. The children were categorized into four groups: OSA, asthma, asthma with OSA, and controls (without asthma or OSA). FeNO levels among the groups were compared using the Kruskal-Wallis test, and correlations were explored using the Spearman correlation coefficient. Analyses considered statistical significance at a two-tailed p-value <0.05. RESULTS: Among the 261 included children, 68 (26.1 %) had OSA, 42 (16.1 %) were diagnosed with asthma, 109 (41.8 %) had both asthma and OSA, and 42 (16.1 %) were controls. Their FeNO medians were 10 ppb, 18.5 ppb, 15 ppb, and 14 ppb, respectively, with no significant differences between the evaluated groups (p = 0.263). We found no correlation between FeNO and apnea-hypopnea index and obstructive apnea index even for the groups of patients with FeNO >20 ppb and FeNO >35 ppb (>75th percentile). In the adjusted model, a significant association was observed between asthma and FeNO levels. CONCLUSIONS: Our findings suggest that FeNO measurements in children would not allow establishing this biomarker as part of the diagnosis of OSA. However, these findings may be related to high altitude.

Clinical Practice Guidelines of the Latin American Federation of Endocrinology for the use of vitamin D in the maintenance of bone health: recommendations for the Latin American context.

INTRODUCTION: These guidelines aim to provide evidence-based recommendations for the supplementation of Vitamin D in maintaining bone health. An unmet need persists in Latin American regarding the availability of clinical and real-world data for rationalizing the use of vitamin D supplementation. The objective of these guidelines is to establish clear and practical recommendations for healthcare practitioners from Latin American countries to address Vitamin D insufficiency in clinical practice. METHODS: The guidelines were developed according to the GRADE-ADOLOPMENT methodology for the adaptation or adoption of CPGs or evidence-based recommendations. A search for high quality CPGs was complemented through a comprehensive review of recent literature, including randomized controlled trials, observational studies, and systematic reviews evaluating the effects of Vitamin D supplementation on bone health. The evidence to decision framework proposed by the GRADE Working Group was implemented by a panel of experts in endocrinology, bone health, and clinical research. RESULTS: The guidelines recommend Vitamin D supplementation for individuals aged 18 and above, considering various populations, including healthy adults, individuals with osteopenia, osteoporosis patients, and institutionalized older adults. These recommendations offer dosing regimens depending on an individualized treatment plan, and monitoring intervals of serum 25-hydroxyvitamin D levels and adjustments based on individual results. DISCUSSION: The guidelines highlight the role of Vitamin D in bone health and propose a standardized approach for healthcare practitioners to address Vitamin D insufficiency across Latin America. The panel underscored the necessity for generating local data and stressed the importance of considering regional geography, social dynamics, and cultural specificities when implementing these guidelines.

Central leptin signaling deficiency induced by leptin receptor antagonist leads to hypothalamic proteomic remodeling.

AIMS: Leptin irresponsiveness, which is often associated with obesity, can have significant impacts on the hypothalamic proteome of individuals, including those who are lean. While mounting evidence on leptin irresponsiveness has focused on obese individuals, understanding the early molecular and proteomic changes associated with deficient hypothalamic leptin signaling in lean individuals is essential for early intervention and prevention of metabolic disorders. Leptin receptor antagonists block the binding of leptin to its receptors, potentially reducing its effects and used in cases where excessive leptin activity might be harmful. MATERIALS AND METHODS: In this work, we blocked the central actions of leptin in lean male adult Wistar rat by chronically administering intracerebroventricularly the superactive leptin receptor antagonist (SLA) (D23L/L39A/D40A/F41A) and investigated its impact on the hypothalamic proteome using label-free sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) for quantitative proteomics. KEY FINDINGS: Our results show an accumulation of proteins involved in mRNA processing, mRNA stability, and translation in the hypothalamus of SLA-treated rats. Conversely, hypothalamic leptin signaling deficiency reduces the representation of proteins implicated in energy metabolism, neural circuitry, and neurotransmitter release. SIGNIFICANCE: The alterations in the adult rat hypothalamic proteome contribute to dysregulate appetite, metabolism, and energy balance, which are key factors in the development and progression of obesity and related metabolic disorders. Additionally, using bioinformatic analysis, we identified a series of transcription factors that are potentially involved in the upstream regulatory mechanisms responsible for the observed signature.

Quality of life of patients with thyroid cancer in Colombia.

INTRODUCTION: Quality of life (QoL) in thyroid cancer patients is comparable to patients with other tumours with worse prognosis. The aim was to evaluate QoL in Colombian patients with thyroid carcinoma and to explore the association of QoL scores with patient features. METHODS: This is a cross-sectional study. The present research was carried out from data obtained for the validation study of the Spanish version of the THYCA-QoL. Adult patients with thyroid carcinoma who underwent total or partial thyroidectomy were included and asked to complete the Spanish-validated versions of the THYCA-QoL and EORTC QLQ-C30 questionnaires. The scores of each domain and single items underwent linear transformation to values of 0-100. Comparisons of scale scores with clinical variables were performed. RESULTS: We included 293 patients. The global EORTC QLQ-C30 score was 73.2±22.1 and the domains with poorer values were emotional and cognitive and the symptoms with poorer values were insomnia and fatigue. The global THYCA-QOL score was 28.4±17.8. The domains with poorer values were neuromuscular and psychological and the single items with poorer values were headaches and tingling hands/feet. CONCLUSION: Colombian patients with thyroid cancer have a good prognosis, but they experience important problems related to QoL. QoL was influenced by demographic and clinical factors such as age, sex functional status and clinical stage.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers.

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20 + chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was > 99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Structural trends in antibody-antigen binding interfaces: a computational analysis of 1833 experimentally determined 3D structures.

Antibodies are attractive therapeutic candidates due to their ability to bind cognate antigens with high affinity and specificity. Still, the underlying molecular rules governing the antibody-antigen interface remain poorly understood, making in silico antibody design inherently difficult and keeping the discovery and design of novel antibodies a costly and laborious process. This study investigates the characteristics of antibody-antigen binding interfaces through a computational analysis of more than 850,000 atom-atom contacts from the largest reported set of antibody-antigen complexes with 1833 nonredundant, experimentally determined structures. The analysis compares binding characteristics of conventional antibodies and single-domain antibodies (sdAbs) targeting both protein- and peptide antigens. We find clear patterns in the number antibody-antigen contacts and amino acid frequencies in the paratope. The direct comparison of sdAbs and conventional antibodies helps elucidate the mechanisms employed by sdAbs to compensate for their smaller size and the fact that they harbor only half the number of complementarity-determining regions compared to conventional antibodies. Furthermore, we pinpoint antibody interface hotspot residues that are often found at the binding interface and the amino acid frequencies at these positions. These findings have direct potential applications in antibody engineering and the design of improved antibody libraries.

Evaluating artificial intelligence for comparative radiography.

INTRODUCTION: Comparative radiography is a forensic identification and shortlisting technique based on the comparison of skeletal structures in ante-mortem and post-mortem images. The images (e.g., 2D radiographs or 3D computed tomographies) are manually superimposed and visually compared by a forensic practitioner. It requires a significant amount of time per comparison, limiting its utility in large comparison scenarios. METHODS: We propose and validate a novel framework for automating the shortlisting of candidates using artificial intelligence. It is composed of (1) a segmentation method to delimit skeletal structures' silhouettes in radiographs, (2) a superposition method to generate the best simulated "radiographs" from 3D images according to the segmented radiographs, and (3) a decision-making method for shortlisting all candidates ranked according to a similarity metric. MATERIAL: The dataset is composed of 180 computed tomographies and 180 radiographs where the frontal sinuses are visible. Frontal sinuses are the skeletal structure analyzed due to their high individualization capability. RESULTS: Firstly, we validate two deep learning-based techniques for segmenting the frontal sinuses in radiographs, obtaining high-quality results. Secondly, we study the framework's shortlisting capability using both automatic segmentations and superimpositions. The obtained superimpositions, based only on the superimposition metric, allowed us to filter out 40% of the possible candidates in a completely automatic manner. Thirdly, we perform a reliability study by comparing 180 radiographs against 180 computed tomographies using manual segmentations. The results allowed us to filter out 73% of the possible candidates. Furthermore, the results are robust to inter- and intra-expert-related errors.

Insulin resistance is a cardiovascular risk factor in hypertensive adults without type 2 diabetes mellitus.

BACKGROUND: Metabolic syndrome refers to the association among several cardiovascular risk factors: obesity, dyslipidemia, hyperglycemia, and hypertension. It is associated with increased cardiovascular risk and the development of type 2 diabetes mellitus. Insulin resistance is the underlying mechanism of metabolic syndrome, although its role in increased cardiovascular risk has not been directly identified. OBJECTIVE: We investigated the association between insulin resistance and increased cardiovascular risk in hypertensive adults without diabetes mellitus. DESIGN AND PARTICIPANTS: We enrolled participants without diabetes from an outpatient setting in a retrospective, longitudinal study. Several demographic, clinical, and laboratory parameters were recorded during the observation period. Plasma insulin and homeostatic model assessment for insulin resistance (HOMA-IR) were used to determine insulin resistance and four cardiovascular events (acute coronary disease, acute cerebrovascular disease, incident heart failure, and cardiovascular mortality) were combined into a single outcome. Logistic regression and Cox proportional hazards models were fitted to evaluate the association between covariates and outcomes. RESULTS: We included 1899 hypertensive adults without diabetes with an average age of 53 years (51.3% women, 23% had prediabetes, and 64.2% had metabolic syndrome). In a logistic regression analysis, male sex (odds ratio, OR = 1.66) having high levels of low-density lipoprotein (LDL, OR = 1.01), kidney function (OR = 0.97), and HOMA-IR (OR = 1.06) were associated with the incidence of cardiovascular events; however, in a survival multivariate analysis, only HOMA-IR (hazard ratio, HR 1.4, 95% confidence interval, CI: 1.05-1.87, p = 0.02) and body mass index (HR 1.05, 95% CI: 1.02-1.08, p = 0.002) were considered independent prognostic variables for the development of incident cardiovascular events. CONCLUSION: Insulin resistance and obesity are useful for assessing cardiovascular risk in hypertensive people without diabetes but with preserved kidney function. This work demonstrates the predictive value of the measurement of insulin, and therefore of insulin resistance, in an outpatient setting and attending to high-risk patients.

Immune and oxidative stress biomarkers in pediatric psychosis and psychosis-risk: Meta-analyses and systematic review.

OBJECTIVE: While genetic and cohort studies suggest immune and reduction/oxidation (redox) alterations occur in psychosis, less is known about potential alterations in children and adolescents. METHODS: We conducted a systematic review to identify immune and redox biomarker studies in children and adolescents (mean age ≤ 18 years old) across the psychosis spectrum: from psychotic like experiences, which are common in children, to threshold psychotic disorders like schizophrenia. We conducted meta-analyses when at least three studies measured the same biomarker. RESULTS: The systematic review includes 38 pediatric psychosis studies. The meta-analyses found that youth with threshold psychotic disorders had higher neutrophil/lymphocyte ratio (Hedge's g = 0.40, 95 % CI 0.17 - 0.64), tumor necrosis factor (Hedge's g = 0.38, 95 % CI 0.06 - 0.69), C-reactive protein (Hedge's g = 0.38, 95 % CI 0.05 - 0.70), interleukin-6 (Hedge's g = 0.35; 95 % CI 0.11 - 0.64), and total white blood cell count (Hedge's g = 0.29, 95 % CI 0.12 - 0.46) compared to youth without psychosis. Other immune and oxidative stress meta-analytic findings were very heterogeneous. CONCLUSION: Results from several studies are consistent with the hypothesis that signals often classified as "proinflammatory" are elevated in threshold pediatric psychotic disorders. Data are less clear for immune markers in subthreshold psychosis and redox markers across the subthreshold and threshold psychosis spectrum. Immune and redox biomarker intervention studies are lacking, and research investigating interventions targeting the immune system in threshold pediatric psychosis is especially warranted.

A window into the human immune system: comprehensive characterization of the complexity of antibody complementary-determining regions in functional antibodies.

The human immune system uses antibodies to neutralize foreign antigens. They are composed of heavy and light chains, both with constant and variable regions. The variable region has six hypervariable loops, also known as complementary-determining regions (CDRs) that determine antibody diversity and antigen specificity. Knowledge of their significance, and certain residues present in these areas, is vital for antibody therapeutics development. This study includes an analysis of more than 11,000 human antibody sequences from the International Immunogenetics information system (IMGT). The analysis included parameters such as length distribution, overall amino acid diversity, amino acid frequency per CDR and residue position within antibody chains. Overall, our findings confirm existing knowledge, such as CDRH3's high length diversity and amino acid variability, increased aromatic residue usage, particularly tyrosine, charged and polar residues like aspartic acid, serine, and the flexible residue glycine. Specific residue positions within each CDR influence these occurrences, implying a unique amino acid type distribution pattern. We compared amino acid type usage in CDRs and non-CDR regions, both in globular and transmembrane proteins, which revealed distinguishing features, such as increased frequency of tyrosine, serine, aspartic acid, and arginine. These findings should prove useful for future optimization, improvement of affinity, synthetic antibody library design, or the creation of antibodies de-novo in silico.

Insulin Resistance and Metabolic Syndrome as Risk Factors for Hospitalization in Patients with COVID-19: Pilot Study on the Use of Machine Learning.

Aim: Conditions linked to metabolic syndrome, such as obesity, hypertension, insulin resistance, and dyslipidemia, are common in patients with severe coronavirus disease 2019 (COVID-19). These conditions can act synergistically to contribute to negative outcomes. We describe and analyze the relationship between metabolic syndrome and COVID-19 severity in terms of risk of hospitalization. Methods: We designed a retrospective, cross-sectional study, including patients with confirmed COVID-19 diagnosis. Clinical and laboratory parameters regarding metabolic syndrome were collected. The Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was used to assess insulin resistance. The outcome was needed for hospitalization. Logistic regression was used to calculate odds ratios, and to determine the association between variables and risk of hospitalization. Advanced approaches using machine learning were also used to identify and interpret the effects of predictors on the proposed outcome. Results: We included 2716 COVID-19 patients with a mean age of 61.8 years. Of these, 48.9% were women, 28.9% had diabetes, and 50.6% were diagnosed with metabolic syndrome. Overall, 212 patients required hospitalization. Patients with metabolic syndrome had a 58% greater chance of hospitalization if they were men, 32% if they had metabolic syndrome, and 23% if they were obese. Machine learning methods identified body mass index, metabolic syndrome, systolic blood pressure, and HOMA-IR as the most relevant features for our predictive model. Conclusion: Metabolic syndrome and its related biomarkers increase the odds for a severe clinical course of COVID-19 and the need for hospitalization. Machine learning methods can aid understanding of the effects of single features when assessing risks for a given outcome.

Hospitalization burden and epidemiology of the COVID-19 pandemic in Spain (2020-2021).

BACKGROUND: Spain had some of Europe's highest incidence and mortality rates for coronavirus disease 2019 (COVID-19). Here we describe the epidemiology and trends in hospitalizations, the number of critical patients, and deaths in Spain in 2020 and 2021. METHODS: We performed a descriptive, retrospective, nationwide study using an administrative database, the Minimum Basic Data Set at Hospitalization, which includes 95-97% of discharge reports for patients hospitalized in Spain in 2020 and 2021. We analyzed the number of hospitalizations, admissions to intensive care units, and deaths and their geographic distribution across regions of Spain. RESULTS: As of December 31, 2021, a total of 498,789 patients (1.04% of the entire Spanish population) had needed hospitalization. At least six waves of illness were identified. Men were more prone to hospitalization than women. The median age was 66. A total of 54,340 patients (10.9% of all hospitalizations) had been admitted to the intensive care unit. We identified 71,437 deaths (mortality rate of 14.3% among hospitalized patients). We also observed important differences among regions, with Madrid being the epicenter of hospitalizations and mortality. CONCLUSIONS: We analyzed Spain's response to COVID-19 and describe here its experiences during the pandemic in terms of hospitalizations, critical illness, and deaths. This research highlights changes over several months and waves and the importance of factors such as vaccination, the predominant variant of the virus, and public health interventions in the rise and fall of the outbreaks.

Differences in Trends in Admissions and Outcomes among Patients from a Secondary Hospital in Madrid during the COVID-19 Pandemic: A Hospital-Based Epidemiological Analysis (2020-2022).

Spain had some of Europe's highest incidence and mortality rates for coronavirus disease 2019 (COVID-19). This study highlights the impact of the COVID-19 pandemic on daily health care in terms of incidence, critical patients, and mortality. We describe the characteristics and clinical outcomes of patients, comparing variables over the different waves. We performed a descriptive, retrospective study using the historical records of patients hospitalized with COVID-19. We describe demographic characteristics, admissions, and occupancy. Time series allowed us to visualize and analyze trends and patterns, and identify several waves during the 27-month period. A total of 3315 patients had been hospitalized with confirmed COVID-19. One-third of these patients were hospitalized during the first weeks of the pandemic. We observed that 4.6% of all hospitalizations had been admitted to the intensive care unit, and we identified a mortality rate of 9.4% among hospitalized patients. Arithmetic- and semi-logarithmic-scale charts showed how admissions and deaths rose sharply during the first weeks, increasing by 10 every few days. We described a single hospital's response and experiences during the pandemic. This research highlights certain demographic profiles in a population and emphasizes the importance of identifying waves when performing research on COVID-19. Our results can extend the analysis of the impact of COVID-19 and can be applied in other contexts, and can be considered when further analyzing the clinical, epidemiological, or demographic characteristics of populations with COVID-19. Our findings suggest that the pandemic should be analyzed not as a whole but rather in different waves.

Value of Prostate-Specific Antigen Kinetics in Patients with Low-Risk Prostate Cancer under Active Surveillance.

INTRODUCTION: This study analyzes the value of PSA kinetics, PSA speed (vPSA), and PSA doubling time (PSAdt), in patients with low-risk prostate cancer who are in an active surveillance (AS) program. METHODS: An observational, retrospective, and longitudinal study of a sample of 86 patients included in AS program between January 2014 and October 2021 was conducted. A review of their medical records was performed, and PSA kinetics were calculated, analyzing the causes of discontinuation of the AS program and its relationship with PSA kinetics. RESULTS: The mean age was 63.39 years, and the median follow-up was 62.55 months. The mean PSA at diagnosis was 8.27 ng/mL. A median of PSAdt of 62.55 months and 1.3 ng/mL/year for vPSA was obtained. 35 patients left the program, with a higher percentage of patients leaving with a PSAdt less than 36 months (73.7 vs. 31.1%) and a vPSA greater than 2 ng/mL/year (68.2 vs. 31.3%). The probability of permanence and the time of permanence in AS were statistically significantly higher for those patients with favorable kinetic parameters. CONCLUSION: PSA kinetics is a parameter to take into account when making decisions to keep patients in an AS program.

A Multi-institution Study on the Association of Virtual Reality Skills with Continence Recovery after Robot-assisted Radical Prostatectomy.

BACKGROUND: Virtual reality (VR) simulators are increasingly being used for surgical skills training. It is unclear what skills are best improved via VR, translate to live surgical skills, and influence patient outcomes. OBJECTIVE: To assess surgeons in VR and live surgery using a suturing assessment tool and evaluate the association between technical skills and a clinical outcome. DESIGN, SETTING, AND PARTICIPANTS: This prospective five-center study enrolled participants who completed VR suturing exercises and provided live surgical video. Graders provided skill assessments using the validated End-To-End Assessment of Suturing Expertise (EASE) suturing evaluation tool. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: A hierarchical Poisson model was used to compare skill scores among cohorts and evaluate the association of scores with clinical outcomes. Spearman's method was used to assess correlation between VR and live skills. RESULTS AND LIMITATIONS: Ten novices, ten surgeons with intermediate expertise (median 64 cases, interquartile range [IQR] 6-80), and 26 expert surgeons (median 850 cases, IQR 375-3000) participated in this study. Intermediate and expert surgeons were significantly more likely to have ideal scores in comparison to novices for the subskills needle hold angle, wrist rotation, and wrist rotation needle withdrawal (p < 0.01). For both intermediate and expert surgeons, there was positive correlation between VR and live skills for needle hold angle (p < 0.05). For expert surgeons, there was a positive association between ideal scores for VR needle hold angle and driving smoothness subskills and 3-mo continence recovery (p < 0.05). Limitations include the size of the intermediate surgeon sample and clinical data limited to expert surgeons. CONCLUSIONS: EASE can be used in VR to identify skills to improve for trainee surgeons. Technical skills that influence postoperative outcomes may be assessable in VR. PATIENT SUMMARY: This study provides insights into surgical skills that translate from virtual simulation to live surgery and that have an impact on urinary continence after robot-assisted removal of the prostate. We also highlight the usefulness of virtual reality in surgical education.

Network structure of avian mixed-species flocks decays with elevation and latitude across the Andes.

Birds in mixed-species flocks benefit from greater foraging efficiency and reduced predation, but also face costs related to competition and activity matching. Because this cost-benefit trade-off is context-dependent (e.g. abiotic conditions and habitat quality), the structure of flocks is expected to vary along elevational, latitudinal and disturbance gradients. Specifically, we predicted that the connectivity and cohesion of flocking networks would (i) decline towards tropical latitudes and lower elevations, where competition and activity matching costs are higher, and (ii) increase with lower forest cover and greater human disturbance. We analysed the structure of 84 flock networks across the Andes and assessed the effect of elevation, latitude, forest cover and human disturbance on network characteristics. We found that Andean flocks are overall open-membership systems (unstructured), though the extent of network structure varied across gradients. Elevation was the main predictor of structure, with more connected and less modular flocks upslope. As expected, flocks in areas with higher forest cover were less cohesive, with better defined flock subtypes. Flocks also varied across latitude and disturbance gradients as predicted, but effect sizes were small. Our findings indicate that the unstructured nature of Andean flocks might arise as a strategy to cope with harsh environmental conditions. This article is part of the theme issue 'Mixed-species groups and aggregations: shaping ecological and behavioural patterns and processes'.

Protective Effect of the Phycobiliproteins from Arthrospira maxima on Indomethacin-Induced Gastric Ulcer in a Rat Model.

Gastric ulcers (GU) constitute a disease with a global prevalence ≈ 8.09 million. Of their causes, non-steroidal anti-inflammatory drugs (NSAIDs) such as indomethacin (IND) rank as the second most frequent etiologic agent. The pathogenic process of gastric lesions is given by the overproduction of oxidative stress, promotion of inflammatory processes, and inhibition of prostaglandin synthesis. Spirulina Arthrospira maxima (SP) is a cyanobacterium with a wide variety of substances with high nutritional and health values such as phycobiliproteins (PBPs) that have outstanding antioxidant activity, anti-inflammatories effects, and accelerate the wound healing process. This study aimed to determine the protective effect of PBPs in GU induced by IND 40 mg/kg. Our results show that the PBPs protected against IND-induced damage with a dose-dependent effect. At a dose of 400 mg/kg, a marked decrease in the number of lesions is observed, as well as the recovery of the main markers of oxidative stress damage (MDA) and antioxidant species (SOD, CAT, GPx) at close to baseline levels. The evidence derived from the present investigation suggests that the antioxidant effect of PBPs, together with their reported anti-inflammatory effects to accelerate the wound healing process, is the most reliable cause of their antiulcerogenic activity in this GU model.

Case report: Accelerated regression of giant cardiac rhabdomyomas in neonates with low dose everolimus.

Cardiac rhabdomyoma (CRHM) is the principal cardiac tumor in children and is most often associated with tuberous sclerosis complex (TSC). Mutations in the TSC1 and TSC2 genes cause the overactivation of the mammalian Target of Rapamycin (mTOR). This protein family is responsible for abnormal cell proliferation leading to the formation of CRHMs and hamartomas in other organs. Despite the tendency for spontaneous regression, some CRHMs can cause heart failure and intractable arrhythmias, requiring surgical resection. In recent years, the use of everolimus and sirolimus (mTOR inhibitors) in the treatment of CRHMs has been reported. We report two cases of neonates with giant rhabdomyomas, with hemodynamic repercussions treated with low-dose everolimus (4.5 mg/m2/week). In both cases, we obtained an approximate decrease of 50% in the total area of the mass after three weeks of treatment. Despite rebound growth after stopping the drug, we were able to evidence that the use of low doses of everolimus immediately after birth is effective and safe in the treatment of giant CRHMs, avoiding surgical resection of the tumor and associated morbidity and mortality.

Eliminating OFF-frame clones in randomized gene libraries: An improved split ß-lactamase enrichment system.

Large, randomized libraries are a key technology for many biotechnological applications. While genetic diversity is the main parameter most libraries direct their resources on, less focus is devoted to ensuring functional IN-frame expression. This study describes a faster and more efficient system based on a split ß-lactamase complementation for removal of OFF-frame clones and increase of functional diversity, suitable for construction of randomized libraries. The gene of interest is inserted between two fragments of the ß-lactamase gene, conferring resistance to ß-lactam drugs only upon expression of an inserted IN-frame gene without stop codons or frameshifts. The preinduction-free system was capable of eliminating OFF-frame clones in starting mixtures of as little as 1% IN-frame clones and enriching to about 70% IN-frame clones, even when their starting rate was as low as 0.001%. The curation system was verified by constructing a single-domain antibody phage display library using trinucleotide phosphoramidites for randomizing a complementary determining region, while eliminating OFF-frame clones and maximizing functional diversity.

Related factors to non-adherence to antiretroviral therapy in HIV/AIDS patients.

OBJECTIVE: To identify sociodemographic, clinical, and pharmacological factors  associated with nonadherence to antiretroviral treatment in patients with  human immunodeficiency virus/acquired immunodeficiency syndrome treated  between 2017 and 2020 in four cities in Colombia. METHOD: An observational, cross-sectional, retrospective study was conducted of a population of patients with human immunodeficiency virus/acquired immunodeficiency syndrome treated between 2017 and 2020. The Morisky-Green scale, the simplified medication adherence  questionnaire, and the simplified scale to detect adherence problems to  antiretroviral treatment were applied to determine patient adherence. A  binomial multiple logistic regression was performed to evaluate the factors that  best explain nonadherence. RESULTS: A total of 9,835 patients were evaluated, of whom 74.4% were men,  71.1% were aged between 18 and 44 years, 76.0% had attended at most  secondary school, 78.1% were single, and 97.6% resided in an urban area.  After applying three different scales to each patient, 10% of the study  population were identified as nonadherent to treatment. The risk of  nonadherence was significantly higher in patients who presented any drug- related problem or had an adverse reaction to antiretroviral drugs. CONCLUSIONS: The variables most strongly associated with nonadherence to  antiretroviral treatment were drug-related problems, adverse drug reactions, a  history of nonadherence to treatment, and psychoactive substance use.

OBJETIVO: Identificar los factores sociodemográficos, clínicos y farmacológicos asociados a la no adherencia al tratamiento antirretroviral en pacientes con infección por virus de la inmunodeficiencia humana/sida atendidos entre 2017 y 2020 en diferentes ciudades de Colombia.Método: Se realizó un estudio observacional, de corte transversal y retrospectivo, con una población de pacientes con infección por virus de la  inmunodeficiencia humana/sida atendidos entre 2017 a 2020. Se aplicaron las  escalas Morisky-Green, el cuestionario simplificado de adherencia a la  medicación y la escala simplificada para detectar problemas de adherencia al  tratamiento antirretroviral, para determinar la adherencia de los pacientes. Se  realizó una regresión logística múltiple para evaluar los factores que mejor  explican la no adherencia. RESULTADOS: Se evaluaron 9.835 pacientes, de los cuales el 74,4% eran hombres, el 71,1% tenían una edad entre 18 a 44 años, el 76,0% cursó como máximo hasta secundaria, el 78,1% eran solteros y el 97,6%  residían en zona urbana. Se encontró una proporción de no adherencia al  tratamiento del 10% después de aplicar tres escalas diferentes a cada paciente. Las personas que presentaron algún problema relacionado con los medicamentos tuvieron un riesgo significativamente mayor de no ser adherentes, al igual que aquellos que tuvieron alguna reacción adversa a los medicamentos antirretrovirales. CONCLUSIONES: Los problemas relacionados con el uso de medicamentos, las  reacciones adversas a medicamentos, los antecedentes de no adherencia al  tratamiento y el consumo de sustancias psicoactivas fueron las variables que  más se asociaron con la no adherencia al tratamiento antirretroviral.