Radio-miRs: a comprehensive view of radioresistance-related microRNAs.

Radiotherapy is a key treatment option for a wide variety of human tumors, employed either alone or alongside with other therapeutic interventions. Radiotherapy uses high-energy particles to destroy tumor cells, blocking their ability to divide and proliferate. The effectiveness of radiotherapy is due to genetic and epigenetic factors that determine how tumor cells respond to ionizing radiation. These factors contribute to the establishment of resistance to radiotherapy, which increases the risk of poor clinical prognosis of patients. Although the mechanisms by which tumor cells induce radioresistance are unclear, evidence points out several contributing factors including the overexpression of DNA repair systems, increased levels of reactive oxygen species, alterations in the tumor microenvironment, and enrichment of cancer stem cell populations. In this context, dysregulation of microRNAs or miRNAs, critical regulators of gene expression, may influence how tumors respond to radiation. There is increasing evidence that miRNAs may act as sensitizers or enhancers of radioresistance, regulating key processes such as the DNA damage response and the cell death signaling pathway. Furthermore, expression and activity of miRNAs have shown informative value in overcoming radiotherapy and long-term radiotoxicity, revealing their potential as biomarkers. In this review, we will discuss the molecular mechanisms associated with the response to radiotherapy and highlight the central role of miRNAs in regulating the molecular mechanisms responsible for cellular radioresistance. We will also review radio-miRs, radiotherapy-related miRNAs, either as sensitizers or enhancers of radioresistance that hold promise as biomarkers or pharmacological targets to sensitize radioresistant cells.

Exploring the Structurally Conserved Regions and Functional Significance in Bacterial N-Terminal Nucleophile (Ntn) Amide-Hydrolases.

The initial adoption of penicillin as an antibiotic marked the start of exploring other compounds essential for pharmaceuticals, yet resistance to penicillins and their side effects has compromised their efficacy. The N-terminal nucleophile (Ntn) amide-hydrolases S45 family plays a key role in catalyzing amide bond hydrolysis in various compounds, including antibiotics like penicillin and cephalosporin. This study comprehensively analyzes the structural and functional traits of the bacterial N-terminal nucleophile (Ntn) amide-hydrolases S45 family, covering penicillin G acylases, cephalosporin acylases, and D-succinylase. Utilizing structural bioinformatics tools and sequence analysis, the investigation delineates structurally conserved regions (SCRs) and substrate binding site variations among these enzymes. Notably, sixteen SCRs crucial for substrate interaction are identified solely through sequence analysis, emphasizing the significance of sequence data in characterizing functionally relevant regions. These findings introduce a novel approach for identifying targets to enhance the biocatalytic properties of N-terminal nucleophile (Ntn) amide-hydrolases, while facilitating the development of more accurate three-dimensional models, particularly for enzymes lacking structural data. Overall, this research advances our understanding of structure-function relationships in bacterial N-terminal nucleophile (Ntn) amide-hydrolases, providing insights into strategies for optimizing their enzymatic capabilities.

Correlation Between Tacrolimus Levels in Blood Samples Obtained from Central Catheter and Peripheral Venipuncture in Lung Transplant Patients (Ven-Cat Study).

BACKGROUND: Following lung transplantation (LT), receiving immunosuppressive therapy is crucial. Tacrolimus is considered a drug with a narrow therapeutic range and its use requires constant monitoring. This study aimed to evaluate the correlation between tacrolimus levels obtained from central venous catheter and direct venipuncture in adult patients undergoing LT. METHODS: This prospective study included LT patients hospitalized in conventional ward carrying a central catheter through which no intravenous tacrolimus was administered. Trough samples were obtained through direct puncture and from the central catheter. Pearson correlation coefficient was calculated to quantify the mean difference between the 2 measures. RESULTS: A total of 54 sample pairs from 16 LT patients were obtained, mostly male (81.3%) and bilateral transplant recipients (93.8%); the transplant procedure was the primary reason for admission (81.3%). The difference in tacrolimus levels between both samples was 0.3 (0.1-0.6) mcg/L, with the measurement for the samples obtained through venipuncture being mostly higher than that for those obtained from the catheter. A strong correlation was observed between the tacrolimus levels in the samples obtained from the catheter and through venipuncture (Pearson correlation coefficient, 0.991; P < 0.001; R2 = 0.982). CONCLUSIONS: There is an excellent correlation between tacrolimus levels obtained from venipuncture and those obtained from central venous catheter in LT patients undergoing oral tacrolimus therapy.

Temporal trends on the prevalence of renal disease and outcomes among patients with diabetes mellitus hospitalized by heart failure: findings from INCAex.

BACKGROUND: To assess 20-year time trends in the prevalence of diabetes mellitus (DM) among inpatients with heart failure (HF) and the influence of coexisting DM and kidney disease (KD) on outcomes. RESEARCH DESIGN AND METHODS: A retrospective study of patients was admitted due to HF, during the period 2000/2019. The period of follow-up was divided into three intervals according to the European Medical Agency approval of newer hypoglycemic drugs. We analyzed in-hospital mortality and outcomes during the follow-up period. RESULTS: A total of 4959 patients were included. Over time, prevalence of DM was significantly raising among women with HF (50 to 53.2%) and descending among men (50% to 46.8%, p = 0.02). Total mortality and readmissions were higher in patients with DM during the and second periods. However, no significant differences were found in the third-one (HR 1.14, 95% CI 0.94-1.39, p = 0.181). A protector role of oral hypoglycemic medications was observed in this last period. According to the presence of KD, the patients with both DM and KD were who presented most of the events. CONCLUSIONS: Over the time analyzed, the prevalence of DM raised among women and decreased among men. DM influenced the prognosis of HF except in the third period when more protective hypoglycemic drugs started to be used.

Development, synthesis, and application of magnetic layered double hydroxides (Fe3O4@SiO-LDH/DS-) as an efficient adsorbent for the removal of tetracyclines from milk samples.

This work presents the development, synthesis, and application of a layered double hydroxide (LDH) coupled to magnetic particles for the removal of antibiotics as tetracyclines (TC´s): tetracycline (TC), chlortetracycline (CT), oxytetracycline (OT), and doxycycline (DT) from milk samples. The LDH synthesis conditions, reaction time (30-90 min), molar ratios Mg2+/Al3+ (7:1-1:7), interlayer anion (NO3-, Cl-, CO32-, and dodecyl sulphate (DS-)) were evaluated. Under synthesis conditions (reaction time of 30 min, Mg2+/Al3+ molar ratio of 7:1, and DS- as interlayer anion), the LDH was coupled in a magnetic solid phase microextraction (MSPµE) methodology. At the optimal extraction conditions (pH 6, 5 min of contact time, 10 mg of adsorbent), a removal percentage of 99.0 % was obtained for each tetracycline. FTIR, TGA, SEM, and adsorption isotherms were employed to characterize the optimal adsorbent. Each experiment was corroborated by large-volume sample stacking capillary electrophoresis (LVSS-CE). The adsorbent was applied directly to positive milk samples (previously tested) for TC´s removal.

Function and expression of N-acetyltransferases 1 and 2 are altered in lymphocytes in type 2 diabetes and obesity.

The cytosolic enzymes N-Acetyl Transferases 1 and 2 (NATs) transfer an acetyl group from acetyl-CoA to a xenobiotic substrate. NATs are regulated at the genetic and epigenetic levels by deacetylase enzymes such as sirtuins. The enzymatic expression of NAT1, NAT2, and SIRT1 was evaluated by flow cytometry, as well as the enzymatic activity of NATs by cell culture and HPLC analysis. Six SNPs were determined through genotyping. T2D patients (n = 29) and healthy subjects (n = 25) with a median age of 57 and 50, respectively, were recruited. An increased enzyme expression and a diminished NAT2 enzymatic activity were found in cells of T2D patients compared to the control group, while NAT1 was negatively correlated with body fat percentage and BMI. In contrast, Sirtuin inhibition increased NAT2 activity, while Sirtuin agonism decreased its activity in both groups. The analysis of NAT2 SNPs showed a higher frequency of rapid acetylation haplotypes in T2D patients compared to the control group, possibly associated as a risk factor for diabetes. The enzymatic expression of CD3+NAT2+ cells was higher in the rapid acetylators group compared to the slow acetylators group. The levels and activity of NAT1 were associated with total cholesterol and triglycerides. Meanwhile, CD3+NAT2+ cells and NAT2 activity levels were associated with HbA1c and glucose levels. The results indicate that NAT2 could be involved in metabolic processes related to the development of T2D, due to its association with glucose levels, HbA1c, and the altered SIRT-NAT axis. NAT1 may be involved with dyslipidaemias in people who are overweight or obese.

Beyond A and B Compartments: how major nuclear locales define nuclear genome organization and function.

Models of nuclear genome organization often propose a binary division into active versus inactive compartments, yet they overlook nuclear bodies. Here we integrated analysis of sequencing and image-based data to compare genome organization in four human cell types relative to three different nuclear locales: the nuclear lamina, nuclear speckles, and nucleoli. Whereas gene expression correlates mostly with nuclear speckle proximity, DNA replication timing correlates with proximity to multiple nuclear locales. Speckle attachment regions emerge as DNA replication initiation zones whose replication timing and gene composition vary with their attachment frequency. Most facultative LADs retain a partially repressed state as iLADs, despite their positioning in the nuclear interior. Knock out of two lamina proteins, Lamin A and LBR, causes a shift of H3K9me3-enriched LADs from lamina to nucleolus, and a reciprocal relocation of H3K27me3-enriched partially repressed iLADs from nucleolus to lamina. Thus, these partially repressed iLADs appear to compete with LADs for nuclear lamina attachment with consequences for replication timing. The nuclear organization in adherent cells is polarized with nuclear bodies and genomic regions segregating both radially and relative to the equatorial plane. Together, our results underscore the importance of considering genome organization relative to nuclear locales for a more complete understanding of the spatial and functional organization of the human genome.

Targeting Neutrophil Extracellular Trap Formation: Exploring Promising Pharmacological Strategies for the Treatment of Preeclampsia.

Neutrophils, which constitute the most abundant leukocytes in human blood, emerge as crucial players in the induction of endothelial cell death and the modulation of endothelial cell responses under both physiological and pathological conditions. The hallmark of preeclampsia is endothelial dysfunction induced by systemic inflammation, in which neutrophils, particularly through the formation of neutrophil extracellular traps (NETs), play a pivotal role in the development and perpetuation of endothelial dysfunction and the hypertensive state. Considering the potential of numerous pharmaceutical agents to attenuate NET formation (NETosis) in preeclampsia, a comprehensive assessment of the extensively studied candidates becomes imperative. This review aims to identify mechanisms associated with the induction and negative regulation of NETs in the context of preeclampsia. We discuss potential drugs to modulate NETosis, such as NF-κß inhibitors, vitamin D, and aspirin, and their association with mutagenicity and genotoxicity. Strong evidence supports the notion that molecules involved in the activation of NETs could serve as promising targets for the treatment of preeclampsia.

Pentoxifylline and Norcantharidin Modify p62 Expression in 2D and 3D Cultures of B16F1 Cells.

Three-dimensional cell cultures have improved the evaluation of drugs for cancer therapy, due to their high similarity to solid tumors. In melanoma, autophagy appears to show a dual role depending on the progression of the disease. p62 protein has been proposed for the evaluation of autophagic flux since its expression is an indicator of the state of autophagy. Pentoxifylline (PTX) and Norcantharidin (NCTD) are drugs that have been shown to possess anticancer effects. In this work, we used B16F1 mouse melanoma cells in two-dimensional (2D) monolayer cultures and three-dimensional (3D) spheroids to test the effect of PTX and NCTD over the p62 expression. We analyzed the effect on p62 expression through Western blot and immunofluorescence assays. Our results indicate that PTX decreases p62 expression in both cell culture models, while Norcantharidin increases its expression in 3D cultures at 24 h. Therefore, these drugs could have a potential therapeutic use for the regulation of autophagy in melanoma, depending on the state of evolution of the disease.

Observer-based control for plasma glucose regulation in type 1 diabetes mellitus patients with unknown input delay.

This article introduces an observer-based control strategy tailored for regulating plasma glucose in type 1 diabetes mellitus patients, addressing challenges like unknown time-varying delays and meal disturbances. This control strategy is based on an extended Bergman minimal model, a nonlinear glucose-insulin model to encompass unknown inputs, such as unplanned meals, exercise disturbances, or delays. The primary contribution lies in the design of an observer-based state feedback control in the presence of unknown long delays, which seeks to support and enhance the performance of the traditional artificial pancreas by considering realistic scenarios. The observer and control gains for the observer-based control are computed through linear matrix inequalities formulated from Lyapunov conditions that guarantee closed-loop stability. This design deploys a soft and gentle dynamic response, similar to a natural pancreas, despite meal disturbances and input delays. Numerical tests demonstrate the scheme's effectiveness in glycemic level regulation and hypoglycemic episode avoidance.

Diabetes and the fabkin complex: A dual-edged sword.

The Fabkin complex, composed of FABP4, ADK, and NDPKs, emerges as a novel regulator of insulin-producing beta cells, offering promising prospects for diabetes treatment. Our approach, which combines literature review and database analysis, sets the stage for future research. These findings hold significant implications for both diabetes treatment and research, as they present potential therapeutic targets for personalized treatment, leading to enhanced patient outcomes and a deeper comprehension of the disease. The multifaceted role of the Fabkin complex in glucose metabolism, insulin resistance, anti-inflammation, beta cell proliferation, and vascular function underscores its therapeutic potential, reshaping diabetes management and propelling advancements in the field.

Impact of dementia on 30-, 180-, and 365-day mortality during the first pandemic wave in older adults seen in spanish emergency departments diagnosed with or without COVID-19.

OBJECTIVES: To assess whether dementia is an independent predictor of death after a hospital emergency department (ED) visit by older adults with or without a COVID-19 diagnosis during the first pandemic wave. METHOD: We used data from the EDEN-Covid (Emergency Department and Elderly Needs during Covid) cohort formed by all patients ≥65 years seen in 52 Spanish EDs from March 30 to April 5, 2020. The association of prior history of dementia with mortality at 30, 180 and 365 d was evaluated in the overall sample and according to a COVID-19 or non COVID diagnosis. RESULTS: We included 9,770 patients aged 78.7 ± 8.3 years, 51.1% men, 1513 (15.5%) subjects with prior history of dementia and 3055 (31.3%) with COVID-19 diagnosis. 1399 patients (14.3%) died at 30 d, 2008 (20.6%) at 180 days and 2456 (25.1%) at 365 d. The adjusted Hazard Ratio (aHR) for age, sex, comorbidity, disability and diagnosis for death associated with dementia were 1.16 (95% CI 1.01-1.34) at 30 d; 1.15 at 180 d (95% CI 1.03-1.30) and 1.19 at 365 d (95% CI 1.07-1.32), p < .001. In patients with COVID-19, the aHR were 1.26 (95% CI: 1.04-1.52) at 30 days; 1.29 at 180 d (95% CI: 1.09-1.53) and 1.35 at 365 d (95% CI: 1.15-1.58). CONCLUSION: Dementia in older adults attending Spanish EDs during the first pandemic wave was independently associated with 30-, 180- and 365-day mortality. This impact was lower when adjusted for age, sex, comorbidity and disability, and was greater in patients diagnosed with COVID-19.

Connecting Clinical Capacity and Intervention Sustainability in Resource-Variable Pediatric Oncology Centers in Latin America.

Clinical capacity for sustainability, or the clinical resources needed to sustain an evidence-based practice, represent proximal determinants that contribute to intervention sustainment. We examine the relationship between clinical capacity for sustainability and sustainment of PEWS, an evidence-based intervention to improve outcomes for pediatric oncology patients in resource-variable hospitals. We conducted a cross-sectional survey among Latin American pediatric oncology centers participating in Proyecto Escala de Valoración de Alerta Temprana (EVAT), an improvement collaborative to implement Pediatric Early Warning Systems (PEWS). Hospitals were eligible if they had completed PEWS implementation. Clinicians were eligible to participate if they were involved in PEWS implementation or used PEWS in clinical work. The Spanish language survey consisted of 56 close and open-ended questions about the respondent, hospital, participants' assessment of clinical capacity to sustain PEWS using the clinical sustainability assessment tool (CSAT), and perceptions about PEWS and its use as an intervention. Results were analyzed using a multi-level modeling approach to examine the relationship between individual, hospital, intervention, and clinical capacity determinants to PEWS sustainment. A total of 797 responses from 37 centers in 13 countries were included in the analysis. Eighty-seven percent of participants reported PEWS sustainment. After controlling for individual, hospital, and intervention factors, clinical capacity was significantly associated with PEWS sustainment (OR 3.27, p < .01). Marginal effects from the final model indicate that an increasing capacity score has a positive influence (11% for every additional CSAT point) of predicting PEWS sustainment. PEWS is a sustainable intervention and clinical capacity to sustain PEWS contributes meaningfully to PEWS sustainment.

Fairness and bias correction in machine learning for depression prediction across four study populations.

A significant level of stigma and inequality exists in mental healthcare, especially in under-served populations. Inequalities are reflected in the data collected for scientific purposes. When not properly accounted for, machine learning (ML) models learned from data can reinforce these structural inequalities or biases. Here, we present a systematic study of bias in ML models designed to predict depression in four different case studies covering different countries and populations. We find that standard ML approaches regularly present biased behaviors. We also show that mitigation techniques, both standard and our own post-hoc method, can be effective in reducing the level of unfair bias. There is no one best ML model for depression prediction that provides equality of outcomes. This emphasizes the importance of analyzing fairness during model selection and transparent reporting about the impact of debiasing interventions. Finally, we also identify positive habits and open challenges that practitioners could follow to enhance fairness in their models.

Significance of clinical-immunological patterns and diagnostic yield of biopsies in microscopic polyangiitis and granulomatosis with polyangiitis.

BACKGROUND: Microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) are the two major antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). OBJECTIVES: To characterize a homogenous AAV cohort and to assess the impact of clinicopathological profiles and ANCA serotypes on clinical presentation and prognosis. Clinical differences in GPA patients according to ANCA serotype and the diagnostic yield for vasculitis of biopsies in different territories were also investigated. RESULTS: This retrospective study (2000-2021) included 152 patients with AAV (77 MPA/75 GPA). MPA patients (96.1% myeloperoxidase [MPO]-ANCA and 2.6% proteinase 3 [PR3]-ANCA) presented more often with weight loss, myalgia, renal involvement, interstitial lung disease (ILD), cutaneous purpura, and peripheral nerve involvement. Patients with GPA (44% PR3-ANCA, 33.3% MPO, and 22.7% negative/atypical ANCA) presented more commonly with ear, nose, and throat and eye/orbital manifestations, more relapses, and higher survival than patients with MPA. GPA was the only independent risk factor for relapse. Poor survival predictors were older age at diagnosis and peripheral nerve involvement. ANCA serotypes differentiated clinical features in a lesser degree than clinical phenotypes. A mean of 1.5 biopsies were performed in 93.4% of patients in different territories. Overall, vasculitis was identified in 80.3% (97.3% in MPA and 61.8% in GPA) of patients. CONCLUSIONS: The identification of GPA presentations associated with MPO-ANCA and awareness of risk factors for relapse and mortality are important to guide proper therapeutic strategies in AAV patients. Biopsies of different affected territories should be pursued in difficult-to-diagnose patients based on their significant diagnostic yield.

An Edge Computing Application of Fundamental Frequency Extraction for Ocean Currents and Waves.

This paper describes the design and optimization of a smart algorithm based on artificial intelligence to increase the accuracy of an ocean water current meter. The main purpose of water current meters is to obtain the fundamental frequency of the ocean waves and currents. The limiting factor in those underwater applications is power consumption and that is the reason to use only ultra-low power microcontrollers. On the other hand, nowadays extraction algorithms assume that the processed signal is defined in a fixed bandwidth. In our approach, belonging to the edge computing research area, we use a deep neural network to determine the narrow bandwidth for filtering the fundamental frequency of the ocean waves and currents on board instruments. The proposed solution is implemented on an 8 MHz ARM Cortex-M0+ microcontroller without a floating point unit requiring only 9.54 ms in the worst case based on a deep neural network solution. Compared to a greedy algorithm in terms of computational effort, our worst-case approach is 1.81 times faster than a fast Fourier transform with a length of 32 samples. The proposed solution is 2.33 times better when an artificial neural network approach is adopted.

Sociodemographic and clinical predictors of adherence to antidepressants in depressive disorders: a systematic review with a meta-analysis.

Introduction: Current evidence reveals concerning rates of non-adherence to antidepressant treatment, possibly influenced by various relevant determinants such as sociodemographic factors or those related to the health system and their professionals. The aim of this paper is to review the scientific evidence on sociodemographic and clinical predictors of adherence to pharmacological treatment in patients diagnosed with a depressive disorder. Methods: a systematic review (SR) was conducted. The search for a previous SR was updated and de novo searches were performed in Medline, EMBASE, Web of Science (WoS) and PsycInfo (last 10 years). The risk of bias was assessed using the Cochrane tool for non-randomized studies-of Exposure (ROBINS-E). Meta-analyses were conducted. Results: Thirty-nine studies (n = 2,778,313) were included, 24 of them in the meta-analyses. In the initiation phase, no association of adherence was found with any of the predictors studied. In the implementation and discontinuation phases, middle-aged and older patients had better adherence rates and lower discontinuation rates than younger ones. White patients adhered to treatment better than African-American patients. Discussion: Age and ethnicity are presented as the predictive factors of pharmacological adherence. However, more research is needed in this field to obtain more conclusive results on other possible factors. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023414059], identifier [CRD42023414059].

High-Dimensional Feature Selection for Automatic Classification of Coronary Stenosis Using an Evolutionary Algorithm.

In this paper, a novel strategy to perform high-dimensional feature selection using an evolutionary algorithm for the automatic classification of coronary stenosis is introduced. The method involves a feature extraction stage to form a bank of 473 features considering different types such as intensity, texture and shape. The feature selection task is carried out on a high-dimensional feature bank, where the search space is denoted by O(2n) and n=473. The proposed evolutionary search strategy was compared in terms of the Jaccard coefficient and accuracy classification with different state-of-the-art methods. The highest feature selection rate, along with the best classification performance, was obtained with a subset of four features, representing a 99% discrimination rate. In the last stage, the feature subset was used as input to train a support vector machine using an independent testing set. The classification of coronary stenosis cases involves a binary classification type by considering positive and negative classes. The highest classification performance was obtained with the four-feature subset in terms of accuracy (0.86) and Jaccard coefficient (0.75) metrics. In addition, a second dataset containing 2788 instances was formed from a public image database, obtaining an accuracy of 0.89 and a Jaccard Coefficient of 0.80. Finally, based on the performance achieved with the four-feature subset, they can be suitable for use in a clinical decision support system.