Early morning physical activity is associated with healthier white matter microstructure and happier children: the ActiveBrains project.

The background of this study is to examine the associations of individual and combined early morning patterns (i.e., active commuting to school, physical activity before school, having breakfast and good sleep) with white matter microstructure (WMM) and, whether the associated white mater microstructure outcomes were related to mental health outcomes in children with overweight or obesity. 103 children with overweight or obesity (10.0 ± 1.1 years old, 42 girls) from the ActiveBrains project participated in this cross-sectional study. Early morning patterns and mental health indicators (i.e., self-esteem, optimism, positive and negative affect, stress, depression and anxiety) were self-reported by the children using validated questionnaires. WMM was assessed by magnetic resonance imaging using diffusion tensor imaging. When examined independently, early morning patterns were not related with WMM (all P > 0.05). However, the combination of early morning patterns was related with WMM (P < 0.05). Specifically, physically active early morning patterns (i.e., active commuting to school and physical activity before school) were associated with global fractional anisotropy (FA) (ß = 0.298, P = 0.013) and global radial diffusivity (RD) (ß = - 0.272, P = 0.021), as well as with tract-specific FA (ß = 0.314, P = 0.004) and RD (ß = - 0.234, P = 0.032) in the superior longitudinal fasciculus (SLF). Furthermore, combined physically active early morning pattern-associated global (i.e., FA and RD) and tract-specific (i.e., FA and RD in the SLF) WMM indicators were positively associated with happiness (ß absolute value range from 0.252 to 0.298, all P < 0.05). A combination of physically active early morning patterns may positively relate to white matter microstructure in children with overweight or obesity, and, in turn, happiness.

Subacute cutaneous lupus erythematosus following ribociclib therapy for metastatic breast cancer.

INTRODUCTION: Drug-induced subacute cutaneous lupus erythematosus (DI-SCLE) has been associated with drugs with different mechanisms of action, including anti-hypertensives, tumour necrosis factor-α inhibitors and even some chemotherapy medicines. In the last years, a few reports have been described in patients treated with cyclin-dependent kinase (CDK) 4/6 inhibitors, palbociclib and abemaciclib. CASE REPORT: Here, we describe a case of DI-SCLE in association with ribociclib and exemestane in a woman diagnosed with metastatic breast cancer. MANAGEMENT AND OUTCOME: Topical mometasone was prescribed for two weeks with complete resolution of lesions, also abemaciclib was substituted for ribociclib, and the patient had stable disease with no relapse of DI-SCLE. DISCUSSION: To our knowledge, this is the first report of ribociclib-induced SCLE but based on the DI-SCLE reported cases associated others CDK4/6 inhibitors, the role of this family of drugs in dermatopathology must be further investigated.

Development and internal validation of a multivariable prediction model for the quality of life of cervical cancer survivors.

PURPOSE: To elaborate a prediction model for quality of life of cervical cancer survivors. METHODS: We conducted a prospective cohort study on 229 cervical cancer survivors. The quality of life measures included the Functional Assessment Cancer Therapy-Cervix version 4.0 and the World Health Organization Quality of Life-brief version self-administered questionnaires. We imported the data into the statistical software program R and developed a gamma generalized linear model. RESULTS: Our internally validated predictive model for the Functional Assessment Cancer Therapy-Cervix total score was composed of the following predictors: pain, appetite, vaginal bleeding/discharge/odor, and WHOQOL-BREF social relationships domain. The Harrell's concordance index was 0.75. CONCLUSIONS: We developed a solid and internally validated predictive model in cervical cancer survivors based on predictors, such as pain, appetite, vaginal bleeding/odor/discharge, and WHOQOL-BREF social relationships subscale score that contribute significantly to quality of life as targets for potential intervention.

Volumetric study of brain MRI in a cohort of patients with neurotransmitter disorders.

PURPOSE: Inborn errors of neurotransmitters are rare monogenic diseases. In general, conventional neuroimaging is not useful for diagnosis. Nevertheless, advanced neuroimaging techniques could provide novel diagnosis and prognosis biomarkers. We aim to describe cerebral volumetric findings in a group of Spanish patients with neurotransmitter disorders. METHODS: Fifteen 3D T1-weighted brain images from the International Working Group on Neurotransmitter related Disorders Spanish cohort were assessed (eight with monoamine and seven with amino acid disorders). Volumes of cortical and subcortical brain structures were obtained for each patient and then compared with those of two healthy individuals matched by sex and age. RESULTS: Regardless of the underlying disease, patients showed a smaller total cerebral tissue volume, which was apparently associated with clinical severity. A characteristic volumetric deficit pattern, including the right Heschl gyrus and the bilateral occipital gyrus, was identified. In severe cases, a distinctive pattern comprised the middle and posterior portions of the right cingulate, the left superior motor area and the cerebellum. In succinate semialdehyde dehydrogenase deficiency, volumetric affection seems to worsen over life. CONCLUSION: Despite the heterogeneity and limited size of our cohort, we found novel and relevant data. Total volume deficit appears to be a marker of severity, regardless of the specific neurotransmitter disease and irrespective of the information obtained from conventional neuroimaging. Volumetric assessment of individual brain structures could provide a deeper knowledge about pathophysiology, disease severity and specific clinical traits.

Relevance of gastrointestinal manifestations in a large Spanish cohort of patients with systemic lupus erythematosus: what do we know?

OBJECTIVE: SLE can affect any part of the gastrointestinal (GI) tract. GI symptoms are reported to occur in >50% of SLE patients. To describe the GI manifestations of SLE in the RELESSER (Registry of SLE Patients of the Spanish Society of Rheumatology) cohort and to determine whether these are associated with a more severe disease, damage accrual and a worse prognosis. METHODS: We conducted a nationwide, retrospective, multicentre, cross-sectional cohort study of 3658 SLE patients who fulfil ≥4 ACR-97 criteria. Data on demographics, disease characteristics, activity (SLEDAI-2K or BILAG), damage (SLICC/ACR/DI) and therapies were collected. Demographic and clinical characteristics were compared between lupus patients with and without GI damage to establish whether GI damage is associated with a more severe disease. RESULTS: From 3654 lupus patients, 3.7% developed GI damage. Patients in this group (group 1) were older, they had longer disease duration, and were more likely to have vasculitis, renal disease and serositis than patients without GI damage (group 2). Hospitalizations and mortality were significantly higher in group 1. Patients in group 1 had higher modified SDI (SLICC Damage Index). The presence of oral ulcers reduced the risk of developing damage in 33% of patients. CONCLUSION: Having GI damage is associated with a worse prognosis. Patients on a high dose of glucocorticoids are at higher risk of developing GI damage which reinforces the strategy of minimizing glucocorticoids. Oral ulcers appear to decrease the risk of GI damage.

Incidence and univariate models for lymphatic drainage disorders following management for cervical cancer.

AIM: To clarify the incidence of lymphatic drainage disorders (LLD) after treatment for cervical cancer (CC) and to establish univariate models for their occurrence. METHODS: A total of 263 eligible patients with CC were identified between 2010 and 2019. We conducted a case-control study and divided the study population into two subsamples of 12 and 251 CC survivors based on the presence/absence of LLD, respectively. The cumulative incidence was evaluated using the Kaplan-Meier method. Univariate models based on Pearson correlation coefficient were used to evaluate associations between explanatory variables and LLD. RESULTS: The cumulative incidence of LLD began at 3.3% after the 7-month follow-up, reaching a plateau of 21.2% between 130 and 250 months of follow-up. We detected correlation between LLD and number of removed para-aortic lymph nodes (r = -0.39), number of pelvic lymphadenopathies (r = 0.16), pelvic lymphadenectomy (PL) (r = 0.16), age at diagnosis of CC (r = -0.1) and primary surgery (r = 0.1). CONCLUSION: We observed a cumulative incidence of LLD of 21.2%, which is in accord with other retrospective studies. Number of removed para-aortic lymph nodes, number of pelvic lymphadenopathies, PL, age at diagnosis of CC and primary surgery were the most influential clinical factors associated with the occurrence of LLD in CC survivors.

Visually guided classification trees for analyzing chronic patients.

BACKGROUND: Chronic diseases are becoming more widespread each year in developed countries, mainly due to increasing life expectancy. Among them, diabetes mellitus (DM) and essential hypertension (EH) are two of the most prevalent ones. Furthermore, they can be the onset of other chronic conditions such as kidney or obstructive pulmonary diseases. The need to comprehend the factors related to such complex diseases motivates the development of interpretative and visual analysis methods, such as classification trees, which not only provide predictive models for diagnosing patients, but can also help to discover new clinical insights. RESULTS: In this paper, we analyzed healthy and chronic (diabetic, hypertensive) patients associated with the University Hospital of Fuenlabrada in Spain. Each patient was classified into a single health status according to clinical risk groups (CRGs). The CRGs characterize a patient through features such as age, gender, diagnosis codes, and drug codes. Based on these features and the CRGs, we have designed classification trees to determine the most discriminative decision features among different health statuses. In particular, we propose to make use of statistical data visualizations to guide the selection of features in each node when constructing a tree. We created several classification trees to distinguish among patients with different health statuses. We analyzed their performance in terms of classification accuracy, and drew clinical conclusions regarding the decision features considered in each tree. As expected, healthy patients and patients with a single chronic condition were better classified than patients with comorbidities. The constructed classification trees also show that the use of antipsychotics and the diagnosis of chronic airway obstruction are relevant for classifying patients with more than one chronic condition, in conjunction with the usual DM and/or EH diagnoses. CONCLUSIONS: We propose a methodology for constructing classification trees in a visually guided manner. The approach allows clinicians to progressively select the decision features at each of the tree nodes. The process is guided by exploratory data analysis visualizations, which may provide new insights and unexpected clinical information.

Clinical and molecular diagnosis of non-phosphomannomutase 2 N-linked congenital disorders of glycosylation in Spain.

The congenital disorders of glycosylation (CDG) are defects in glycoprotein and glycolipid glycan synthesis and attachment. They affect multiple organ/systems, but non-specific symptoms render the diagnosis of the different CDG very challenging. Phosphomannomutase 2 (PMM2)-CDG is the most common CDG, but advances in genetic analysis have shown others to occur more commonly than previously thought. The present work reports the clinical and mutational spectrum of 25 non-PMM2 CDG patients. The most common clinical symptoms were hypotonia (80%), motor or psychomotor disability (80%) and craniofacial dysmorphism (76%). Based on their serum transferrin isoform profile, 18 were classified as CDG-I and 7 as CDG-II. Pathogenic variations were found in 16 genes (ALG1, ALG6, ATP6V0A2, B4GALT1, CCDC115, COG7, DOLK, DPAGT1, DPM1, GFPT1, MPI, PGM1, RFT1, SLC35A2, SRD5A3, and SSR4). Overall, 27 variants were identified, 12 of which are novel. The results highlight the importance of combining genetic and biochemical analyses for the early diagnosis of this heterogeneous group of disorders.

Biomarkers and clinical scores to identify patient populations at risk of delayed antibiotic administration or intensive care admission.

BACKGROUND: The performance of blood biomarkers (mid-regional proadrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate) and clinical scores (Sequential Organ Failure Assessment (SOFA), National Early Warning Score (NEWS), and quick SOFA) was compared to identify patient populations at risk of delayed treatment initiation and disease progression after presenting to the emergency department (ED) with a suspected infection. METHODS: A prospective observational study across three EDs. Biomarker and clinical score values were calculated upon presentation and 72 h, and logistic and Cox regression used to assess the strength of association. Primary outcomes comprised of 28-day mortality prediction and delayed antibiotic administration or intensive care (ICU) admission, whilst secondary outcomes identified subsequent disease progression. RESULTS: Six hundred eighty-four patients were enrolled with hospitalisation, ICU admission, and infection-related 28-day mortality rates of 72.8%, 3.4%, and 4.4%, respectively. MR-proADM and NEWS had the strongest association with hospitalisation and the requirement for antibiotic administration, whereas MR-proADM alone had the strongest association with ICU admission (OR [95% CI]: 5.8 [3.1 - 10.8]) and mortality (HR [95% CI]: 3.8 [2.2 - 6.5]). Patient subgroups with high MR-proADM concentrations (≥ 1.77 nmol/L) and low NEWS (< 5 points) values had significantly higher rates of ICU admission (8.1% vs 1.6%; p < 0.001), hospital readmission (18.9% vs. 5.9%; p < 0.001), infection-related mortality (13.5% vs. 0.2%; p < 0.001), and disease progression (29.7% vs. 4.9%; p < 0.001) than corresponding patients with low MR-proADM concentrations. ICU admission was delayed by 1.5 [0.25 - 5.0] days in patients with high MR-proADM and low NEWS values compared to corresponding patients with high NEWS values, despite similar 28-day mortality rates (13.5% vs. 16.5%). Antibiotics were withheld in 17.4% of patients with high MR-proADM and low NEWS values, with higher subsequent rates of ICU admission (27.3% vs. 4.8%) and infection-related hospital readmission (54.5% vs. 14.3%) compared to those administered antibiotics during ED treatment. CONCLUSIONS: Patients with low severity signs of infection but high MR-proADM concentrations had an increased likelihood of subsequent disease progression, delayed antibiotic administration or ICU admission. Appropriate triage decisions and the rapid use of antibiotics in patients with high MR-proADM concentrations may constitute initial steps in escalating or intensifying early treatment strategies.

Direct trocar insertion without previous pneumoperitoneum versus insertion after insufflation with Veress needle in laparoscopic gynecological surgery: a prospective cohort study.

The aim of this study was to determine whether direct trocar entry without prior pneumoperitoneum at umbilical level (DTI) can be a safe alternative to access the abdominal cavity in gynaecological laparoscopic surgery. We present a prospective observational analytical study of cohorts, comparing DTI with umbilical entry with trocar after previous insufflation with a Veress needle at umbilical level (V). The study period was performed from June 2013 to April 2016; data was collected on 600 patients who underwent gynaecological laparoscopic surgery. There were no significant differences in the risk of suffering a complication during the access manoeuvres between DTI (6.49%) and V (7.39%), OR 0.89 (95% CI: 0.42-1.81). The duration of the access manoeuvres was 69 s in DTI and 193 s in V (p < .001). The percentage of patients in whom two or more access attempts were performed was lower in DTI (7.8%) than in V (12.3%) (p > .05). We concluded that DTI is at least as safe as V, regarding the risk of suffering complications arising from access into the abdominal cavity. DTI has advantages with regard to V, such as: the shorter duration of access manoeuvres or the lesser number of unsuccessful entry or insufflation attempts. Impact statement What is already known on this subject? There are few international publications comparing DTI and V. When we conducted a search in PubMed for the terms 'Veress needle and direct trocar insertion', 51 publications were obtained. When we increased the restriction and added the terms 'laparoscopic entry and laparoscopy complications', 27 publications were obtained; thus, the uniqueness of our study. What do the results of this study add? We present a 3-year observational prospective study of cohorts that included 600 patients. The aim of this study was to determine that in laparoscopic gynaecological surgery, DTI is an access method to the abdominal cavity at least as safe as V, with respect to the risk of complications. On the other hand, DTI has some advantages such as the shorter duration of access manoeuvres or the lower number of failed entry attempts. What are the implications of these findings for clinical practice and/or further research? Given the limited number of publications that compared both techniques, our study indicates that DTI can be a safe alternative for access to abdominal cavity in gynaecological surgery, compared to the traditional V.

Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit.

The presence of bacteria with resistance to specific antibiotics is one of the greatest threats to the global health system. According to the World Health Organization, antimicrobial resistance has already reached alarming levels in many parts of the world, involving a social and economic burden for the patient, for the system, and for society in general. Because of the critical health status of patients in the intensive care unit (ICU), time is critical to identify bacteria and their resistance to antibiotics. Since common antibiotics resistance tests require between 24 and 48 h after the culture is collected, we propose to apply machine learning (ML) techniques to determine whether a bacterium will be resistant to different families of antimicrobials. For this purpose, clinical and demographic features from the patient, as well as data from cultures and antibiograms are considered. From a population point of view, we also show graphically the relationship between different bacteria and families of antimicrobials by performing correspondence analysis. Results of the ML techniques evidence non-linear relationships helping to identify antimicrobial resistance at the ICU, with performance dependent on the family of antimicrobials. A change in the trend of antimicrobial resistance is also evidenced.

Predicting colorectal surgical complications using heterogeneous clinical data and kernel methods.

OBJECTIVE: In this work, we have developed a learning system capable of exploiting information conveyed by longitudinal Electronic Health Records (EHRs) for the prediction of a common postoperative complication, Anastomosis Leakage (AL), in a data-driven way and by fusing temporal population data from different and heterogeneous sources in the EHRs. MATERIAL AND METHODS: We used linear and non-linear kernel methods individually for each data source, and leveraging the powerful multiple kernels for their effective combination. To validate the system, we used data from the EHR of the gastrointestinal department at a university hospital. RESULTS: We first investigated the early prediction performance from each data source separately, by computing Area Under the Curve values for processed free text (0.83), blood tests (0.74), and vital signs (0.65), respectively. When exploiting the heterogeneous data sources combined using the composite kernel framework, the prediction capabilities increased considerably (0.92). Finally, posterior probabilities were evaluated for risk assessment of patients as an aid for clinicians to raise alertness at an early stage, in order to act promptly for avoiding AL complications. DISCUSSION: Machine-learning statistical model from EHR data can be useful to predict surgical complications. The combination of EHR extracted free text, blood samples values, and patient vital signs, improves the model performance. These results can be used as a framework for preoperative clinical decision support.

The environmental quality of Doñana surrounding areas affects the immune transcriptional profile of inhabitant crayfish Procambarus clarkii.

This study aimed to identify differentially expressed genes in Procambarus clarkii crayfish collected from locations of different environmental qualities in the Doñana National Park surrounding areas. The pollution sustained by the crayfish was confirmed by their hepatopancreatic metal concentration. We generated forward and reverse libraries by suppression subtractive hybridization (SSH) to analyze the transcriptional profiles of crayfish from moderately and highly polluted zones in comparison with the control site within the Doñana Biological Reserve. Forty-three differentially expressed genes were detected, and most of them were identified as genes involved in a variety of biological functions, particularly in the innate immune response. To verify the SSH results and assess interindividual variability nine transcripts (ALP, AST, BTF3, CHIT, CTS, ferritin, HC, HC2, and SPINK4) were selected for absolute quantification by real-time qRT-PCR. The qRT-PCR data revealed substantial differences in the absolute amounts of the nine transcripts and confirmed their up- or down-regulation in the polluted sites. Additionally, a positive and significant linear correlation was found between the hepatopancreatic copper concentration and the levels of the transcripts encoding hemocyanins. Finally, the transcriptomic study was complemented with a detailed analysis of SNP profiles of the selected transcripts that revealed point mutations that might underlie adaptive response to environmental stress in P. clarkii. Overall, this work provides novel insights into the molecular pathways that could mediate the response to environmental pollutants in P. clarkii emphasizing the central role of the immune function and thus, should clearly benefit further immunotoxicological research in this organism.

Female sexual function in long-term cervical cancer survivors compared with healthy women and women affected by benign gynecological disorders.

OBJECTIVE: To compare the female sexual function between cervical cancer survivors and healthy women or with benign gynecological diseases. STUDY DESIGN: From January 1, 2010 to January 31, 2019, a case-control study was conducted to compare the female sexual function of 106 cervical cancer survivors from a tertiary hospital and 185 women admitted to a gynecological outpatient clinic from the same health area for a routine gynecological examination (n=46) or for a benign gynecological disorder (symptomatic, n=113; asymptomatic, n=26). We prospectively assessed the female sexual function using the Female Sexual Function Index (FSFI). For the contrastive analysis hypothesis, we employed R statistical software. RESULTS: Cervical cancer survivors reported lower sexual activity rates than controls, in general, did (47.12% vs. 88.65%, p=0.0001), and, particularly, compared with healthy and symptomatic controls (47.12% vs. 82.61%, p=0.003; 47.12% vs. 87.61%, p=0.0001, respectively). Sixty and fifty-eight hundredths percent of the cervical cancer survivors experienced female sexual dysfunction, mainly due to hypoactive sexual desire (93.27%). Female sexual dysfunction was diagnosed in 64.32% of the controls, with sexual arousal disorders being the most common diagnosis (44.86%). Compared with controls, cervical cancer survivors exhibited considerably lower FSFI total scores and in sexual desire and lubrication domains (p <0.000; p <0.0001; p=0.023). CONCLUSIONS: Cervical cancer survivors had worse female sexual function and less sexual activity than controls did, although scores in both groups were in range of FSD. Rates of female sexual dysfunction were similar across cervical cancer survivors and controls, with hypoactive sexual desire and sexual arousal disorders as the most common diagnoses, respectively.

Quality of life in long-term cervical cancer survivors compared with healthy women and women with benign gynecological disorders.

OBJECTIVE: The impact of cervical cancer treatment on the quality of life of long-term survivors compared with the general female population is controversial, and no studies have been conducted comparing patients with benign gynecological diseases. The aim of this study was to compare the quality of life of cervical cancer survivors with that of healthy controls. STUDY DESIGN: A case-control study was conducted to compare the quality of life of 106 cervical cancer survivors from a tertiary hospital and 185 women admitted to a gynecological outpatient clinic from the same health area for a healthy woman check-up (n 46) or for a benign gynecological disorder (symptomatic, n 113; asymptomatic, n 26). To measure quality of life, self-administered questionnaires, such as the Functional Assessment Cancer Therapy-cervix and World Health Organization quality of life-brief version, were employed. Baseline scores were collected when patients first reported, and further evaluations were completed at 0-6, 7-12, 13-24, 25-60, and more than 60 months. For the contrastive analysis hypothesis, we employed R statistical software. RESULTS: Except for the environment domain at 0-6, 7-12, and 13-24 months (51.52 vs. 60.73, p < 0.0001; 52 vs. 60.73, p < 0.0001; 49.81 vs. 60.73, p < 0.0001, respectively), we found no statistically significant differences in the quality of life between cervical cancer survivors and controls. We did find differences in the physical health domain scores at 0-6 months (60.22 vs. 72.42, p = 0.039) and the social relationships domain scores at 13-24 months (54 vs. 71.42, p = 0.017) between cases and asymptomatic controls. CONCLUSION: Except for physical well-being, environment and social relationships, which were substantially better for controls, especially in the asymptomatic, long-term cervical cancer survivorsquality of life did not vary from that of controls.

Integrated modeling of labile and glycated hemoglobin with glucose for enhanced diabetes detection and short-term monitoring.

Metabolic biomarkers, particularly glycated hemoglobin and fasting plasma glucose, are pivotal in the diagnosis and control of diabetes mellitus. Despite their importance, they exhibit limitations in assessing short-term glucose variations. In this study, we propose labile hemoglobin as an additional biomarker, providing insightful perspectives into these fluctuations. By utilizing datasets from 40,652 retrospective general participants and conducting glucose tolerance tests on 60 prospective pediatric subjects, we explored the relationship between plasma glucose and labile hemoglobin. A mathematical model was developed to encapsulate short-term glucose kinetics in the pediatric group. Applying dimensionality reduction techniques, we successfully identified participant subclusters, facilitating the differentiation between diabetic and non-diabetic individuals. Intriguingly, by integrating labile hemoglobin measurements with plasma glucose values, we were able to predict the likelihood of diabetes in pediatric subjects, underscoring the potential of labile hemoglobin as a significant glycemic biomarker for diabetes research.

MicroRNA signatures in hereditary breast cancer.

This study aims to identify signatures of miR associated with hereditary, BRCA1 or BRCA2 mutation positive breast cancer (BC), and non-hereditary BC, either sporadic (SBC) or non-informative (BRCAX). Moreover, we search for signatures associated with tumor stage, immunohistochemistry and tumor molecular profile. Twenty formalin fixed paraffin embedded (FFPE) BCs, BRCA1, BRCA2, BRCAX and SBC, five per group were studied. Affymetrix platform miRNA v.3.0 was used to perform miR expression analysis. ER, PR, HER2 and Ki67 protein expression was analyzed by immunohistochemistry. BRCA1, BRCA2 and RASSF1 methylation analysis, AURKA copy number variations, and BRCA1 and BRCA2 deletions, were studied by MLPA. We validated eight of the miR selected by the arrays in 77 BCs by qRT-PCR. The miR profiles associated with tumor features were studied applying the Sparse Partial Least Squares Discriminant Analysis. MiR discrimination capability to distinguish hereditary and non-hereditary BC was analyzed by the discriminant function. With 15 out of 1,733 hsa-miRs, it was possible to differentiate the four groups. BRCA1, BRCA2 and SBC were associated with clusters of hyper-expressed miRs, and BRCAX with hypo-expressed miRs. Hsa-miR-4417 and hsa-miR-423-3p expressions (included among the eight validated miRs) differentiated 70.1 % of hereditary and non-hereditary BCs. We found miR profiles associated with tumor features like node involvement, histological grade, ER, PR and HER2 expression. Regarding molecular parameters, we only found a weak association of miRs in BC harboring losses in AURKA. We conclude that array miR expression profiles can differentiate the four study groups using FFPE BC. However, miRs expression estimated by qRT-PCR differentiates only hereditary and non-inherited BCs. The miR expression array is a simple and rapid approach that could be useful to facilitate the identification of those SBC carrying genetic or epigenetic changes in BRCA genes responsible of BRCA-like phenotype. These patients could benefit from the treatment with PARP inhibitors.

Association between water intake, chronic kidney disease, and cardiovascular disease: a cross-sectional analysis of NHANES data.

BACKGROUND: Evidence from animal and human studies suggests a protective effect of higher water intake on kidney function and cardiovascular disease (CVD). Here the associations between water intake, chronic kidney disease (CKD) and CVD were examined in the general population. METHODS: We conducted a cross-sectional analysis of the 2005-2006 National Health and Nutrition Examination Survey. Non-pregnant adults with an estimated glomerular filtration rate (eGFR) ≥30 ml/min/1.73 m(2) who were not taking diuretics were included. Total water intake from foods and beverages was categorized as low (<2.0 l/day), moderate (2.0-4.3 l/day) and high (>4.3 l/day). We examined associations between low total water intake and CKD (eGFR 30-60 ml/min/1.73 m(2)) and self-reported CVD. RESULTS: Of 3,427 adults (mean age 46 (range 20-84); mean eGFR 95 ml/min/1.73 m(2) (range 30-161)), 13% had CKD and 18% had CVD. CKD was higher among those with the lowest (<2.0 l/day) vs. highest total water intake (>4.3 l/day) (adjusted odds ratio (OR) 2.52; 95% confidence interval (CI) 0.91-6.96). When stratified by intake of (1) plain water and (2) other beverages, CKD was associated with low intake of plain water: adjusted OR 2.36 (95% CI 1.10-5.06), but not other beverages: adjusted OR 0.87 (95% CI 0.30-2.50). There was no association between low water intake and CVD (adjusted OR 0.76; 95% CI 0.37-1.59). CONCLUSIONS: Our results provide additional evidence suggesting a potentially protective effect of higher total water intake, particularly plain water, on the kidney.

Impact of Ischemia and Preservation Times on Survival in Transplant Recipients From After Circulatory Death Donors.

BACKGROUND: The limitation of ischemia times, which damages the organs and impacts transplant outcomes, is a drawback of controlled donation after circulatory death. METHODS: The aim of the study was to analyze the influence of preservation and ischemia times on overall survival and both censured graft survival and overall graft survival. This was an observational and retrospective study of patients undergoing liver transplantation with grafts from controlled donation after circulatory death between November 2013 and November 2022. RESULTS: Sixty-five patients were included in the study. Twenty percent (12 patients) developed early graft dysfunction according to Olthoff's classification, and 7 patients (11.6%) scored ≥7 points according to the Model for Early Allograft Function Scoring scale. Five patients (7.6%) met the criteria for primary graft failure. The retransplantation rate was 9.2% (6 cases). Fifty patients (76.9%) remained alive, and 15 patients (23.1%) died. When analyzing overall survival based on the main preservation and ischemia times, we observed that the best results occurred in the group with a functional warm ischemia time <12 minutes, with a survival rate at 1, 3, and 5 years of 95.8%, 87.1%, and 87.1%, respectively (P = .043). Regarding the analysis of censured graft survival based on the main preservation and ischemia times, we found that the worst results occurred in the group with a cold ischemia time ≥6 hours, with a survival rate of around 48% at 3 and 5 years (P = .047). CONCLUSIONS: High-risk patients have lower overall and graft survival in the short and long term in grafts from controlled donation after circulatory death.

Dimensionality reduction and ensemble of LSTMs for antimicrobial resistance prediction.

Bacterial resistance to antibiotics has been rapidly increasing, resulting in low antibiotic effectiveness even treating common infections. The presence of resistant pathogens in environments such as a hospital Intensive Care Unit (ICU) exacerbates the critical admission-acquired infections. This work focuses on the prediction of antibiotic resistance in Pseudomonas aeruginosa nosocomial infections at the ICU, using Long Short-Term Memory (LSTM) artificial neural networks as the predictive method. The analyzed data were extracted from the Electronic Health Records (EHR) of patients admitted to the University Hospital of Fuenlabrada from 2004 to 2019 and were modeled as Multivariate Time Series. A data-driven dimensionality reduction method is built by adapting three feature importance techniques from the literature to the considered data and proposing an algorithm for selecting the most appropriate number of features. This is done using LSTM sequential capabilities so that the temporal aspect of features is taken into account. Furthermore, an ensemble of LSTMs is used to reduce the variance in performance. Our results indicate that the patient's admission information, the antibiotics administered during the ICU stay, and the previous antimicrobial resistance are the most important risk factors. Compared to other conventional dimensionality reduction schemes, our approach is able to improve performance while reducing the number of features for most of the experiments. In essence, the proposed framework achieve, in a computationally cost-efficient manner, promising results for supporting decisions in this clinical task, characterized by high dimensionality, data scarcity, and concept drift.