Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods. METHODS: Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by CMR investigation. 4D Flow-based E/A ratio values were computed using three different approaches; two semi-automated, assessing the E/A ratio by measuring the inflow velocity (MVvel) and the inflow volume (MVflow) at the mitral valve plane, and one fully automated, creating a full LV segmentation using a deep learning-based method with which the E/A ratio could be assessed without constraint to the mitral plane (LVvel). RESULTS: MVvel, MVflow, and LVvel E/A ratios were strongly associated with echocardiographically derived E/A ratio (R2 = 0.60, 0.58, 0.72). LVvel peak E and A showed moderate association to Echo peak E and A, while MVvel values were weakly associated. MVvel and MVflow EA ratios were very strongly associated with LVvel (R2 = 0.84, 0.86). MVvel peak E was moderately associated with LVvel, while peak A showed a strong association (R2 = 0.26, 0.57). CONCLUSION: Peak E, peak A, and E/A ratio are integral to the assessment of diastolic dysfunction and may expand the utility of CMR studies in patients with cardiovascular disease. While underestimation of absolute peak E and A velocities was noted, the E/A ratio measured with all three 4D Flow methods was strongly associated with the gold standard Doppler echocardiography. The automatic, deep learning-based method performed best, with the most favorable runtime of ∼40 seconds. As both semi-automatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of E/A ratio.

Automatic Time-Resolved Cardiovascular Segmentation of 4D Flow MRI Using Deep Learning.

BACKGROUND: Segmenting the whole heart over the cardiac cycle in 4D flow MRI is a challenging and time-consuming process, as there is considerable motion and limited contrast between blood and tissue. PURPOSE: To develop and evaluate a deep learning-based segmentation method to automatically segment the cardiac chambers and great thoracic vessels from 4D flow MRI. STUDY TYPE: Retrospective. SUBJECTS: A total of 205 subjects, including 40 healthy volunteers and 165 patients with a variety of cardiac disorders were included. Data were randomly divided into training (n = 144), validation (n = 20), and testing (n = 41) sets. FIELD STRENGTH/SEQUENCE: A 3 T/time-resolved velocity encoded 3D gradient echo sequence (4D flow MRI). ASSESSMENT: A 3D neural network based on the U-net architecture was trained to segment the four cardiac chambers, aorta, and pulmonary artery. The segmentations generated were compared to manually corrected atlas-based segmentations. End-diastolic (ED) and end-systolic (ES) volumes of the four cardiac chambers were calculated for both segmentations. STATISTICAL TESTS: Dice score, Hausdorff distance, average surface distance, sensitivity, precision, and miss rate were used to measure segmentation accuracy. Bland-Altman analysis was used to evaluate agreement between volumetric parameters. RESULTS: The following evaluation metrics were computed: mean Dice score (0.908 ± 0.023) (mean ± SD), Hausdorff distance (1.253 ± 0.293 mm), average surface distance (0.466 ± 0.136 mm), sensitivity (0.907 ± 0.032), precision (0.913 ± 0.028), and miss rate (0.093 ± 0.032). Bland-Altman analyses showed good agreement between volumetric parameters for all chambers. Limits of agreement as percentage of mean chamber volume (LoA%), left ventricular: 9.3%, 13.5%, left atrial: 12.4%, 16.9%, right ventricular: 9.9%, 15.6%, and right atrial: 18.7%, 14.4%; for ED and ES, respectively. DATA CONCLUSION: The addition of this technique to the 4D flow MRI assessment pipeline could expedite and improve the utility of this type of acquisition in the clinical setting. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 1.

Using Deep Learning to Emulate the Use of an External Contrast Agent in Cardiovascular 4D Flow MRI.

BACKGROUND: Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications. PURPOSE: To develop and evaluate a deep learning architecture to generate high blood-tissue contrast in noncontrast 4D flow MRI by emulating the use of an external contrast agent. STUDY TYPE: Retrospective. SUBJECTS: Of 222 data sets, 141 were used for neural network (NN) training (69 with and 72 without contrast agent). Evaluation was performed on the remaining 81 noncontrast data sets. FIELD STRENGTH/SEQUENCES: Gradient echo or echo-planar 4D flow MRI at 1.5 T and 3 T. ASSESSMENT: A cyclic generative adversarial NN was trained to perform image translation between noncontrast and contrast data. Evaluation was performed quantitatively using contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), structural similarity index (SSIM), mean squared error (MSE) of edges, and Dice coefficient of segmentations. Three observers performed a qualitative assessment of blood-tissue contrast, noise, presence of artifacts, and image structure visualization. STATISTICAL TESTS: The Wilcoxon rank-sum test evaluated statistical significance. Kendall's concordance coefficient assessed interobserver agreement. RESULTS: Contrast in the regions of interest (ROIs) in the NN enhanced images increased by 88%, CNR increased by 63%, and SNR improved by 48% (all P < 0.001). The SSIM was 0.82 ± 0.01, and the MSE of edges was 0.09 ± 0.01 (range [0,1]). Segmentations based on the generated images resulted in a Dice similarity increase of 15.25%. The observers managed to differentiate between contrast MR images and our results; however, they preferred the NN enhanced images in 76.7% of cases. This percentage increased to 93.3% for phase-contrast MR angiograms created from the NN enhanced data. Visual grading scores were blood-tissue contrast = 4.30 ± 0.74, noise = 3.12 ± 0.98, and presence of artifacts = 3.63 ± 0.76. Image structures within and without the ROIs resulted in scores of 3.42 ± 0.59 and 3.07 ± 0.71, respectively (P < 0.001). DATA CONCLUSION: The proposed approach improves blood-tissue contrast in MR images and could be used to improve data quality, visualization, and postprocessing of cardiovascular 4D flow data. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Automated segmentation of the individual branches of the carotid arteries in contrast-enhanced MR angiography using DeepMedic.

BACKGROUND: Non-invasive imaging is of interest for tracking the progression of atherosclerosis in the carotid bifurcation, and segmenting this region into its constituent branch arteries is necessary for analyses. The purpose of this study was to validate and demonstrate a method for segmenting the carotid bifurcation into the common, internal, and external carotid arteries (CCA, ICA, ECA) in contrast-enhanced MR angiography (CE-MRA) data. METHODS: A segmentation pipeline utilizing a convolutional neural network (DeepMedic) was tailored and trained for multi-class segmentation of the carotid arteries in CE-MRA data from the Swedish CardioPulmonsary bioImage Study (SCAPIS). Segmentation quality was quantitatively assessed using the Dice similarity coefficient (DSC), Matthews Correlation Coefficient (MCC), F2, F0.5, and True Positive Ratio (TPR). Segmentations were also assessed qualitatively, by three observers using visual inspection. Finally, geometric descriptions of the carotid bifurcations were generated for each subject to demonstrate the utility of the proposed segmentation method. RESULTS: Branch-level segmentations scored DSC = 0.80 ± 0.13, MCC = 0.80 ± 0.12, F2 = 0.82 ± 0.14, F0.5 = 0.78 ± 0.13, and TPR = 0.84 ± 0.16, on average in a testing cohort of 46 carotid bifurcations. Qualitatively, 61% of segmentations were judged to be usable for analyses without adjustments in a cohort of 336 carotid bifurcations without ground-truth. Carotid artery geometry showed wide variation within the whole cohort, with CCA diameter 8.6 ± 1.1 mm, ICA 7.5 ± 1.4 mm, ECA 5.7 ± 1.0 mm and bifurcation angle 41 ± 21°. CONCLUSION: The proposed segmentation method automatically generates branch-level segmentations of the carotid arteries that are suitable for use in further analyses and help enable large-cohort investigations.

Changes in PPAR-γ Expression Are Associated with microRNA Profiles during Fetal Programming due to Maternal Overweight and Obesity.

BACKGROUND: There has been a global increase in the prevalence of obesity in pregnant women in recent years. Animal studies have shown that intrauterine environment associated with maternal obesity leads to epigenetic changes. However, the effects of epigenetic changes occurring before birth in response to maternal conditions have not been clearly characterized in humans. OBJECTIVE: The aim of the study was to analyze peroxisome proliferator-activated receptor (PPAR)-γ expression in cell cultures from newborns from mothers with overweight and obesity, in response to in vitro metabolic challenges and their relationship with microRNA profile and cytokine expression. Methods/Study design: The profile of circulating microRNAs from 72 mother-child pairs (including healthy infants born to normal weight [n = 35], overweight [n = 25], and obese [n = 12] mothers) was determined through real-time PCR, and the PPAR-γ expression in peripheral blood mononuclear cell cultures from offspring was analyzed after in vitro challenges. RESULTS: miR-146a, miR-155, and miR-378a were upregulated in overweight mothers, while miR-378a was upregulated in obese mothers compared to normal weight mothers. In children from overweight mothers, miR-155 and miR-221 were downregulated and miR-146a was upregulated, while offspring of mothers with obesity showed downregulation of miR-155, miR-221, and miR-1301. These microRNAs have direct or indirect relation with PPAR-γ expression. In vitro exposure to high triglyceride and exposure to miR-378a induced a higher expression of PPAR-γ in cells from offspring of mothers with overweight and obesity. In contrast, cells from offspring of mothers with obesity cultured with high glucose concentrations showed PPAR-γ downregulation. IL-1ß, IL-6, and TNF-α expression in cells of offspring of overweight and obese mothers differed from that of offspring of normal weight mothers. Limitation of our study is the small sample size. CONCLUSION: The blood microRNA profile, and in vitro PPAR-γ and inflammatory cytokine expression in cells of newborn infants are associated with maternal obesity indicating that epigenetic marks may be established during intrauterine development. Key Message: Neonatal microRNA profile is associated with maternal weight. Neonatal microRNA profile is independent of maternal microRNA profile. PPAR-γ expression in newborn cell cultures is affected by maternal weight.

Urinary Metabolites Altered during the Third Trimester in Pregnancies Complicated by Gestational Diabetes Mellitus: Relationship with Potential Upcoming Metabolic Disorders.

Gestational diabetes mellitus (GDM) is a disorder in pregnancy with highest impact in the future life of both mother and newborn. Increasing incidence, economic impact, and potential for severe GDM-related pregnancy complications are some factors that have motivated the deep study of physiopathology, risk factors for developing GDM, and potential biomarkers for its diagnosis. In the present pilot study, we analyzed the urinary metabolome profile of GDM patients in the 3rd trimester of pregnancy, when GDM is already established and the patients are under dietary and pharmacological control. An untargeted metabolomics method based on liquid chromatography⁻mass spectrometry analysis was developed to identify differentially expressed metabolites in the GDM group. We identified 14 metabolites that are significantly upregulated in the urine of GDM patients, and, more importantly, we identified those related with the steroid hormone biosynthesis and tryptophan (TRP) metabolism pathways, which are associated with GDM pathophysiology. Thus, these metabolites could be screened as potential prognostic biomarkers of type two diabetes mellitus, coronary artery disease and chronic renal failure in future follow-up studies with GDM patients.

Improving left ventricular segmentation in four-dimensional flow MRI using intramodality image registration for cardiac blood flow analysis.

PURPOSE: Assessment of blood flow in the left ventricle using four-dimensional flow MRI requires accurate left ventricle segmentation that is often hampered by the low contrast between blood and the myocardium. The purpose of this work is to improve left-ventricular segmentation in four-dimensional flow MRI for reliable blood flow analysis. METHOD: The left ventricle segmentations are first obtained using morphological cine-MRI with better in-plane resolution and contrast, and then aligned to four-dimensional flow MRI data. This alignment is, however, not trivial due to inter-slice misalignment errors caused by patient motion and respiratory drift during breath-hold based cine-MRI acquisition. A robust image registration based framework is proposed to mitigate such errors automatically. Data from 20 subjects, including healthy volunteers and patients, was used to evaluate its geometric accuracy and impact on blood flow analysis. RESULTS: High spatial correspondence was observed between manually and automatically aligned segmentations, and the improvements in alignment compared to uncorrected segmentations were significant (P < 0.01). Blood flow analysis from manual and automatically corrected segmentations did not differ significantly (P > 0.05). CONCLUSION: Our results demonstrate the efficacy of the proposed approach in improving left-ventricular segmentation in four-dimensional flow MRI, and its potential for reliable blood flow analysis. Magn Reson Med 79:554-560, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Effect of cytomegalovirus infection and leukocyte immunoglobulin like receptor B1 polymorphisms on receptor expression in peripheral blood mononuclear cells.

Leukocyte immunoglobulin like receptor B1 (LILRB1) plays a significant role in a number of infectious, autoimmune, cardiovascular, and oncologic disorders. LILRB1 expression varies between individuals and may be associated with polymorphisms on the regulatory region of the LILRB1 gene, as well as to previous cytomegalovirus infection. In this study, the contribution of these two factors to LILRB1 expression in peripheral blood mononuclear cells of healthy young adults was analyzed. LILRB1 expression in NK cells, T cells, B cells and monocytes was significantly stronger in individuals who had had cytomegalovirus infection than in those who had not (P < 0.001, P < 0.001, P < 0.01, and P < 0.001, respectively). Overall, no differences in LILRB1 expression were observed between individuals with and without GAA haplotypes of the LILRB1 regulatory region. However, when analyzed according to cytomegalovirus infection status, significant differences in LILRB1+ NK cells were observed. A higher proportion of LILRB1+ cells was found in GAA+ than in GAA- individuals who had not been infected (P < 0.01), whereas GAA- individuals had a larger proportion of LILRB1+ cells than GAA+ individuals who were cytomegalovirus positive (P < 0.01). In conclusion, cytomegalovirus infection has a major effect on LILRB1 expression in NK and other mononuclear cells and polymorphisms in the LILRB1 regulatory region appear to have a modulatory influence over this effect.

Creating hemodynamic atlases of cardiac 4D flow MRI.

PURPOSE: Hemodynamic atlases can add to the pathophysiological understanding of cardiac diseases. This study proposes a method to create hemodynamic atlases using 4D Flow magnetic resonance imaging (MRI). The method is demonstrated for kinetic energy (KE) and helicity density (Hd ). MATERIALS AND METHODS: Thirteen healthy subjects underwent 4D Flow MRI at 3T. Phase-contrast magnetic resonance cardioangiographies (PC-MRCAs) and an average heart were created and segmented. The PC-MRCAs, KE, and Hd were nonrigidly registered to the average heart to create atlases. The method was compared with 1) rigid, 2) affine registration of the PC-MRCAs, and 3) affine registration of segmentations. The peak and mean KE and Hd before and after registration were calculated to evaluate interpolation error due to nonrigid registration. RESULTS: The segmentations deformed using nonrigid registration overlapped (median: 92.3%) more than rigid (23.1%, P < 0.001), and affine registration of PC-MRCAs (38.5%, P < 0.001) and affine registration of segmentations (61.5%, P < 0.001). The peak KE was 4.9 mJ using the proposed method and affine registration of segmentations (P = 0.91), 3.5 mJ using rigid registration (P < 0.001), and 4.2 mJ using affine registration of the PC-MRCAs (P < 0.001). The mean KE was 1.1 mJ using the proposed method, 0.8 mJ using rigid registration (P < 0.001), 0.9 mJ using affine registration of the PC-MRCAs (P < 0.001), and 1.0 mJ using affine registration of segmentations (P = 0.028). The interpolation error was 5.2 ± 2.6% at mid-systole, 2.8 ± 3.8% at early diastole for peak KE; 9.6 ± 9.3% at mid-systole, 4.0 ± 4.6% at early diastole, and 4.9 ± 4.6% at late diastole for peak Hd . The mean KE and Hd were not affected by interpolation. CONCLUSION: Hemodynamic atlases can be obtained with minimal user interaction using nonrigid registration of 4D Flow MRI. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1389-1399.

Improving visualization of 4D flow cardiovascular magnetic resonance with four-dimensional angiographic data: generation of a 4D phase-contrast magnetic resonance CardioAngiography (4D PC-MRCA).

Magnetic Resonance Angiography (MRA) and Phase-Contrast MRA (PC-MRA) approaches used for assessment of cardiovascular morphology typically result in data containing information from the entire cardiac cycle combined into one 2D or 3D image. Information specific to each timeframe of the cardiac cycle is, however, lost in this process. This study proposes a novel technique, called Phase-Contrast Magnetic Resonance CardioAngiography (4D PC-MRCA), that utilizes the full potential of 4D Flow CMR when generating temporally resolved PC-MRA data to improve visualization of the heart and major vessels throughout the cardiac cycle. Using non-rigid registration between the timeframes of the 4D Flow CMR acquisition, the technique concentrates information from the entire cardiac cycle into an angiographic dataset at one specific timeframe, taking movement over the cardiac cycle into account. Registration between the timeframes is used once more to generate a time-resolved angiography. The method was evaluated in ten healthy volunteers. Visual comparison of the 4D PC-MRCAs versus PC-MRAs generated from 4D Flow CMR using the traditional approach was performed by two observers using Maximum Intensity Projections (MIPs). The 4D PC-MRCAs resulted in better visibility of the main anatomical regions of the cardiovascular system, especially where cardiac or vessel motion was present. The proposed method represents an improvement over previous PC-MRA generation techniques that rely on 4D Flow CMR, as it effectively utilizes all the information available in the acquisition. The 4D PC-MRCA can be used to visualize the motion of the heart and major vessels throughout the entire cardiac cycle.

Genome-wide analyses for dissecting gene regulatory networks in the shoot apical meristem.

Shoot apical meristem activity is controlled by complex regulatory networks in which components such as transcription factors, miRNAs, small peptides, hormones, enzymes and epigenetic marks all participate. Many key genes that determine the inherent characteristics of the shoot apical meristem have been identified through genetic approaches. Recent advances in genome-wide studies generating extensive transcriptomic and DNA-binding datasets have increased our understanding of the interactions within the regulatory networks that control the activity of the meristem, identifying new regulators and uncovering connections between previously unlinked network components. In this review, we focus on recent studies that illustrate the contribution of whole genome analyses to understand meristem function.

Atlas-based analysis of 4D flow CMR: automated vessel segmentation and flow quantification.

BACKGROUND: Flow volume quantification in the great thoracic vessels is used in the assessment of several cardiovascular diseases. Clinically, it is often based on semi-automatic segmentation of a vessel throughout the cardiac cycle in 2D cine phase-contrast Cardiovascular Magnetic Resonance (CMR) images. Three-dimensional (3D), time-resolved phase-contrast CMR with three-directional velocity encoding (4D flow CMR) permits assessment of net flow volumes and flow patterns retrospectively at any location in a time-resolved 3D volume. However, analysis of these datasets can be demanding. The aim of this study is to develop and evaluate a fully automatic method for segmentation and analysis of 4D flow CMR data of the great thoracic vessels. METHODS: The proposed method utilizes atlas-based segmentation to segment the great thoracic vessels in systole, and registration between different time frames of the cardiac cycle in order to segment these vessels over time. Additionally, net flow volumes are calculated automatically at locations of interest. The method was applied on 4D flow CMR datasets obtained from 11 healthy volunteers and 10 patients with heart failure. Evaluation of the method was performed visually, and by comparison of net flow volumes in the ascending aorta obtained automatically (using the proposed method), and semi-automatically. Further evaluation was done by comparison of net flow volumes obtained automatically at different locations in the aorta, pulmonary artery, and caval veins. RESULTS: Visual evaluation of the generated segmentations resulted in good outcomes for all the major vessels in all but one dataset. The comparison between automatically and semi-automatically obtained net flow volumes in the ascending aorta resulted in very high correlation (r (2)=0.926). Moreover, comparison of the net flow volumes obtained automatically in other vessel locations also produced high correlations where expected: pulmonary trunk vs. proximal ascending aorta (r (2)=0.955), pulmonary trunk vs. pulmonary branches (r (2)=0.808), and pulmonary trunk vs. caval veins (r (2)=0.906). CONCLUSIONS: The proposed method allows for automatic analysis of 4D flow CMR data, including vessel segmentation, assessment of flow volumes at locations of interest, and 4D flow visualization. This constitutes an important step towards facilitating the clinical utility of 4D flow CMR.

Eco-epidemiological study of seropositivity against Rickettsia and Leptospira agents in rural areas of Urabá, Colombia.

Rickettsioses and leptospirosis are infectious diseases that are often underdiagnosed due to a lack of knowledge about their epidemiology, pathophysiology, diagnosis, management, among others. Objetive: to characterize the seroprevalence and seroincidence of both Rickettsia and Leptospira agents and determine the risk factors for these outcomes in rural areas of Urabá, Antioquia. Methods: a secondary data analysis using information on Rickettsia and Leptospira exposure from a prior prospective study that explored sociocultural and ecological aspects of Rickettsia infection in rural Urabá, Colombia. A multinomial mixed logistic regression model was employed to analyze factors linked to seroprevalent cases of Rickettsia, Leptospira and both, along with descriptive analyses of seroincident cases. Results: the concomitant seroprevalence against Rickettsiaand Leptospira was 9.38% [95%CI 6.08%-13.37%] (56/597). The factors associated with this seroprevalence were age (ORa= 1.02 [95%CI 1.007-1.03]), male gender (ORa= 3.06 [95%CI 1.75-5.37]), fever history (ORa= 1.71 [95%CI 1.06-2.77]) the presence of breeding pigs (ORa= 2.29 [95%CI 1.36-3.88]), peridomicile yucca crops(ORa= 2.5 [95%CI 1.1-5.62]), and deforestation practices(ORa= 1.74 [95%CI 1.06-2.87]). The concomitant seroincidence against Rickettsia and Leptospira was 1.09% (3/274) [95%CI 0.29%-4.05%], three cases were female, with a median age of 31.83 years-old (IQR 8.69-56.99). At the household level, all the seroincident cases had households built partially or totally with soil floors, wooden walls, and zinc roofs. Two seroincident cases described the presence of equines, canines, and domestic chickens in intra or peri-domicile. Finally, two cases were exposed to synanthropic rodents, and one case to tick infestation. Conclusion: there is evidence of seroprevalent and seroincident cases of seropositivity against both Rickettsia and Leptospira in rural areas of Urabá, Colombia. These findings can help improve public health surveillance systems in preventing, detecting, and attending to the different clinical cases caused by these pathogens.

Association Between Pro-inflammatory Cytokine Levels (IL-1ß, IL-6, and TNF-α) in Human Colostrum and Maternal Body Composition Components.

Background: Obesity is characterized as a low-grade chronic inflammatory state, marked by elevated inflammatory biomarkers. Breast milk (BM) is rich in nutritional elements, vitamins, minerals, immunological factors, and bioactive components. These bioactive components, capable of influencing biological processes, may vary in concentration based on maternal body composition. Research Aim/Question(s): This study aimed to explore the association between pro-inflammatory cytokine levels (interleukin-1 beta [IL-1ß], interleukin-6 [IL-6], and tumor necrosis factor-alpha [TNF-α]) in human colostrum and maternal body composition, as analyzed through bioelectrical impedance vector analysis (BIVA). Method: In this cross-sectional study, 117 healthy postpartum participants were included, with each group (normal weight, overweight, and obese) comprising 39 individuals, as classified by BIVA. Colostrum samples were collected within the first 24 hours postpartum. Results: IL-1ß levels did not significantly differ across the groups, with concentrations of 69.5 ± 103 pg/mL in normal-weight, 79.7 ± 97.9 pg/mL in overweight, and 68.7 ± 108 pg/mL in obese women. IL-6 levels were significantly higher in the overweight group (55 ± 72.4 pg/mL) than in the normal-weight (48.1 ± 74.1 pg/mL) and obese groups (28.9 ± 36.2 pg/mL) (p = 0.02). Similarly, TNF-α levels were higher in the overweight group, with concentrations of 58.7 ± 74.9 pg/mL, than in the normal-weight group, with concentrations of 38.6 ± 95.4 pg/mL, and 52.6 ± 115 pg/mL in obese women (p = 0.02). Conclusion: This study shows that IL-6 and TNF-α concentrations were statistically higher in the colostrum of overweight women, suggesting that maternal body composition may influence the inflammatory profile of BM.

Inhaled nitric oxide in moderate-to-severe COVID-19 acute respiratory distress syndrome: a retrospective cohort study.

OBJECTIVE: In this study, we present the findings from a cohort of patients with COVID-19 with acute respiratory distress syndrome who underwent standard therapy, including prone positioning, with or without adjunctive inhalation of nitric oxide. Our investigation sought to determine whether inhaled nitric oxide administration yielded clinical enhancement in this population. Remarkably, nitric oxide administration elevated the PaO2/FiO2 ratio, which is indicative of improved oxygenation. Despite this improvement, discernible mortality benefits did not emerge in association with the inhaled nitric oxide treatment. To evaluate the responsiveness of COVID-19 acute respiratory distress syndrome patients to inhaled nitric oxide as part of their standard therapy. METHODS: This retrospective cohort study included critically ill adult patients with confirmed COVID-19 treated between March 2020 and May 2021. Eligible patients with moderate-to-severe acute respiratory distress syndrome due to COVID-19 were subsequently categorized into two groups based on inhaled nitric oxide use throughout their stay in the intensive care unit. The primary endpoints were overall mortality and improvement in oxygenation parameters 6 hours after inhaled nitric oxide use. RESULTS: A total of 481 patients admitted to the intensive care unit due to COVID-19 acute respiratory distress syndrome were screened, 105 of which were included. Among the 105 patients, inhaled nitric oxide therapy was used in 33 patients, will 72 did not undergo inhaled nitric oxide therapy. No significant difference in mortality was observed between the groups (67% for the treatment and 82% for the no-treatment groups respectively, p=0.173). Among the patients who used inhaled nitric oxide, 17 (51%) were considered responsive to therapy. There was no significant difference in the length of stay in the intensive care unit (p=0.324) or total hospitalization time (p=0.344). CONCLUSION: Inhaled nitric oxide rescue therapy improved oxygenation in patients with COVID-19 with moderate-to-severe acute respiratory distress syndrome but did not affect mortality.

Epileptic encephalopathies secondary to hypothalamic hamartomas treated with radiosurgery: A case series.

OBJECTIVE: Hypothalamic hamartomas are congenital lesions that typically present with gelastic seizures, refractory epilepsy, neurodevelopmental delay, and severe cognitive impairment. Surgical procedures have been reported to be effective in removing the hamartomas, however, they are associated with significant morbidity. Therefore, it is not considered a safe therapeutic modality. Image-guided robotic radiosurgery (CyberKnife® Radiosurgery System) has been shown to provide good outcomes without lasting complications. METHODS: This series of cases describes the clinical, radiological, radiotherapeutic, and postsurgical outcomes of five patients with epileptic encephalopathies secondary to hypothalamic hamartomas who were treated with CyberKnife®. RESULTS: All patients exhibited refractory epilepsy with gelastic seizures and were unsuitable candidates for surgical resection The prescribed dose ranged between 16 and 25 Gy, delivered in a single fraction for four patients and five fractions for one patient while adhering strictly to visual pathway constraints. After radiosurgery, four patients maintained seizure control (one with an Engel class Ia, three with an Engel class 1d), and another presented sporadic, nondisabling gelastic seizures (with an Engel class IIa). After 24-26 months of follow-up, in three patients, their intelligence quotient scores increased. No complications were reported. SIGNIFICANCE: This report suggests that Cyberknife may be a good option for treating hypothalamic hamartoma, particularly in cases where other noninvasive alternatives are unavailable. Nevertheless, additional studies are essential in order to evaluate the effectiveness of the technique in these cases.

Neurologic manifestations of Long COVID in Colombia: a comparative analysis of post-hospitalization vs. non-hospitalized patients.

Objective: To analyze patient-reported outcomes, cognitive function, and persistent symptoms in patients with neurologic post-acute sequelae of SARS-CoV-2 infection (Neuro-PASC) in Colombia. Methods: We recruited patients with laboratory-confirmed COVID-19 and PASC symptoms lasting more than 6 weeks at the CES University and CES Clinic (Medellín, Colombia). We included 50 post-hospitalization Neuro-PASC (PNP) and 50 non-hospitalized Neuro-PASC (NNP) patients. Long-COVID symptoms, cognitive (NIH Toolbox v2.1-Spanish for 18+), patient-reported (PROMIS) outcomes, and relevant medical history were evaluated. Statistical analyses were performed via generalized linear models. Results: Overall, brain fog (60%), myalgia (42%), and numbness or tingling (41%) were the most common neurological symptoms, while fatigue (74%), sleep problems (46%), and anxiety (44%) were the most common non-neurological symptoms. Compared to NNP, PNP patients showed a higher frequency of abnormal neurological exam findings (64% vs. 42%, p = 0.028). Both groups had impaired quality of life (QoL) in domains of cognition, fatigue, anxiety depression and sleep disturbance, and performed worse on processing speed and attention than a normative population. In addition, NNP patients performed worse on executive function than PNP patients (T-score 42.6 vs. 48.5, p = 0.012). PASC symptoms of anxiety and depression were associated with worse QoL and cognitive outcomes. Brain fog and fatigue remained persistent symptoms across all durations of Long COVID. Conclusion: Our findings highlight the high incidence and heterogeneity of the neurologic symptoms and impacts of Long COVID even more than 2 years from disease onset. Early detection, emotional support and targeted management of Neuro-PASC patients are warranted.

Genome-Wide Association Study of Accessory Atrioventricular Pathways.

Importance: Understanding of the genetics of accessory atrioventricular pathways (APs) and affiliated arrhythmias is limited. Objective: To investigate the genetics of APs and affiliated arrhythmias. Design, Setting, and Participants: This was a genome-wide association study (GWAS) of APs, defined by International Classification of Diseases (ICD) codes and/or confirmed by electrophysiology (EP) study. Genome-wide significant AP variants were tested for association with AP-affiliated arrhythmias: paroxysmal supraventricular tachycardia (PSVT), atrial fibrillation (AF), ventricular tachycardia, and cardiac arrest. AP variants were also tested in data on other heart diseases and measures of cardiac physiology. Individuals with APs and control individuals from Iceland (deCODE Genetics), Denmark (Copenhagen Hospital Biobank, Danish Blood Donor Study, and SupraGen/the Danish General Suburban Population Study [GESUS]), the US (Intermountain Healthcare), and the United Kingdom (UK Biobank) were included. Time of phenotype data collection ranged from January 1983 to December 2022. Data were analyzed from August 2022 to January 2024. Exposures: Sequence variants. Main Outcomes and Measures: Genome-wide significant association of sequence variants with APs. Results: The GWAS included 2310 individuals with APs (median [IQR] age, 43 [28-57] years; 1252 [54.2%] male and 1058 [45.8%] female) and 1 206 977 control individuals (median [IQR] year of birth, 1955 [1945-1970]; 632 888 [52.4%] female and 574 089 [47.6%] male). Of the individuals with APs, 909 had been confirmed in EP study. Three common missense variants were associated with APs, in the genes CCDC141 (p.Arg935Trp: adjusted odds ratio [aOR], 1.37; 95% CI, 1.24-1.52, and p.Ala141Val: aOR, 1.55; 95% CI 1.34-1.80) and SCN10A (p.Ala1073Val: OR, 1.22; 95% CI, 1.15-1.30). The 3 variants associated with PSVT and the SCN10A variant associated with AF, supporting an effect on AP-affiliated arrhythmias. All 3 AP risk alleles were associated with higher heart rate and shorter PR interval, and have reported associations with chronotropic response. Conclusions and Relevance: Associations were found between sequence variants and APs that were also associated with risk of PSVT, and thus likely atrioventricular reentrant tachycardia, but had allele-specific associations with AF and conduction disorders. Genetic variation in the modulation of heart rate, chronotropic response, and atrial or atrioventricular node conduction velocity may play a role in the risk of AP-affiliated arrhythmias. Further research into CCDC141 could provide insights for antiarrhythmic therapeutic targeting in the presence of an AP.

Gene Expression Analysis by Quantitative Real-Time PCR for Floral Tissues.

Real-time, or quantitative, reverse transcription polymerase chain reaction (qRT-PCR) is a powerful method for rapid and reliable quantification of mRNA abundance. Although it has not featured prominently in flower development research in the past, the availability of novel techniques for the synchronized induction of flower development, or for the isolation of cell-specific mRNA populations, suggests that detailed quantitative analyses of gene expression over time and in specific tissues and cell types by qRT-PCR will become more widely used. In this chapter, we discuss specific considerations for studying gene expression by using qRT-PCR, such as the identification of suitable reference genes for the experimental set-up used. In addition, we provide protocols for performing qRT-PCR experiments in a multiwell plate format (with the LightCycler® 480 system, Roche) and with nanofluidic arrays (BioMark™ system, Fluidigm), which allow the automatic combination of sets of samples with sets of assays, and significantly reduce reaction volume and the number of liquid-handling steps performed during the experiment.

[Impact of acute lymphoblastic leukemia on the microbiome and oral lesions: scoping review]. / Impacto de la leucemia linfoblástica aguda en el microbioma y lesiones bucales: revisión de alcance.

Objective: To describe the existing knowledge about the alterations of the MBO oral microbiome and the presence of OL Oral Lesions in patients with Acute Lymphoblastic Leukemia ALL. Materials and Methods: An electronic search was carried out in the PubMed, SciELO, and academic Google databases, and descriptive, analytical, observational articles on MBO, OL, and ALL were included, following the PRISMA criteria. 642 were evaluated, duplicate articles, case reports, and those where only changes were reported during or after chemotherapy treatment were eliminated. Results: 10 articles were evaluated, published between 1997 and 2021, 4 articles agreed that the MBO of patients with ALL is in dysbiosis showing a significant increase in firmicutes 0.1%, bacillus 0.05%, and opportunistic bacteria such as Moraxella spp, Klebsiella spp 5.66%, Pseudomonas spp 3.77%, Enterobacter spp 1.88%, Acinetobacter spp 1.88% and E. coli 1.08%, the most frequent OL reported in 5 articles were spontaneous gingival bleeding 3.5%, gingivitis 25% and ulcers 9.4%. Conclusions: The oral cavity of patients with ALL is in dysbiosis and associated OL is identified. It is necessary to establish preventive strategies with a niche-ecological approach to restore the MBO, to reduce the risk of opportunistic infections and other OL during chemotherapy treatment.