Correct Nucleotide Selection Is Confined at the Binding Site of Polymerase Enzymes.

DNA polymerases (Pols) add incoming nucleotides (deoxyribonucleoside triphosphate (dNTPs)) to growing DNA strands, a crucial step for DNA synthesis. The insertion of correct (vs incorrect) nucleotides relates to Pols' fidelity, which defines Pols' ability to faithfully replicate DNA strands in a template-dependent manner. We and others have demonstrated that reactant alignment and correct base pairing at the Pols catalytic site are crucial structural features to fidelity. Here, we first used equilibrium molecular simulations to demonstrate that the local dynamics at the protein-DNA interface in the proximity of the catalytic site is different when correct vs incorrect dNTPs are bound to polymerase ß (Pol ß). Formation and dynamic stability of specific interatomic interactions around the incoming nucleotide influence the overall binding site architecture. This explains why certain Pols' mutants can affect the local catalytic environment and influence the selection of correct vs incorrect nucleotides. In particular, this is here demonstrated by analyzing the interaction network formed by the residue R283, whose mutant R283A has an experimentally measured lower capacity of differentiating correct (G:dCTP) vs incorrect (G:dATP) base pairing in Pol ß. We also used alchemical free-energy calculations to quantify the G:dCTP →G:dATP transformation in Pol ß wild-type and mutant R283A. These results correlate well with the experimental trend, thus corroborating our mechanistic insights. Sequence and structural comparisons with other Pols from the same family suggest that these findings may also be valid in similar enzymes.

How do sports injury epidemiological outcomes vary depending on athletes' response rates to a weekly online questionnaire? An analysis of 39-week follow-up from 391 athletics (track and field) athletes.

OBJECTIVE: To explore how sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) vary depending on the response rates to a weekly online self-reported questionnaire for athletes. METHODS: Weekly information on athletics injuries and exposure from 391 athletics (track and field) athletes was prospectively collected over 39 weeks (control group of the PREVATHLE randomized controlled trial) using an online self-reported questionnaire. The data were used to calculate sports injury epidemiological outcomes (i.e., prevalence, average prevalence, incidence, burden, and time to first injury) for sub-groups with different minimum individual athletes' response rates (i.e., from at least 100%, at least 97%, at least 95%, … to at least 0% response rate). We then calculated the relative variation between each sub-group and the sub-group with a 100% response rate as a reference. A substantial variation was considered when the relative variation was greater than one SD or 95% CI of the respective epidemiological outcome calculated in the sub-group with a 100% response rate. RESULTS: Of 15 249 expected weekly questionnaires, 7209 were completed and returned, resulting in an overall response rate of 47.3%. The individual athletes' response rates ranged from 0% (n = 51) to 100% (n = 100). The prevalence, average weekly prevalence, and time to first injury only varied substantially for the sub-groups below a 5%, 10% and 18% minimum individual response rate, respectively. The incidence and injury burden showed substantial variations for all sub-groups with a response rate below 100%. CONCLUSIONS: Epidemiological outcomes varied depending on the minimum individual athletes' response rate, with injury prevalence, average weekly prevalence, and time to first injury varying less than injury incidence and injury burden. This highlights the need to take into account the individual response rate when calculating epidemiological outcomes, and determining the optimal study-specific cut-offs of the minimum individual response rate needed.

On-Machine LTS Integration for Layer-Wise Surface Quality Characterization in MEX/P.

Material Extrusion (MEX) currently stands as the most widespread Additive Manufacturing (AM) process, but part quality deficiencies remain a barrier to its generalized industrial adoption. Quality control in MEX is a complex task as extrusion performance impacts the consistency of mechanical properties and the surface finish, dimensional accuracy, and geometric precision of manufactured parts. Recognizing the need for early-stage process monitoring, this study explores the potential of integrating Laser Triangulation Sensors (LTS) into MEX/P manufacturing equipment for layer-wise 3D inspections. Using a double-bridge architecture, an LTS-based sub-micrometric inspection system operates independently from the manufacturing process, enabling comprehensive digitization and autonomous reconstruction of the target layer's topography. Surface texture is then computed using standardized indicators and a new approach that provides insight into layer quality uniformity. A case study evaluating two alternative extruder head designs demonstrates the efficacy of this integrated approach for layer quality characterization. Implementing a generalized layer-wise procedure based on this integration can significantly mitigate quality issues in MEX manufacturing and optimize process parameter configurations for enhanced performance.

Comparison of Refractive Index Matching Techniques and PLIF40 Measurements in Annular Flow.

This paper investigates non-invasive techniques for annular two-phase flow analysis, focusing on liquid film characterization to understand the interfacial phenomena that are crucial for heat and mass transfer. Limited methods allow the study of the temporal and spatial evolution of liquid film, such as Planar Laser-Induced Fluorescence (PLIF). However, this method possesses optical challenges, leading to the need for improved techniques to mitigate refraction and reflection, such as Refractive Index Matching (RIM). This study utilizes an experimental annular flow facility to analyze both RIM and non-RIM PLIF over a range of liquid Reynolds numbers from 4200 to 10,400. Three configurations-PLIF RIM90, PLIF RIM40, and PLIF nRIM40-are compared from both qualitative and quantitative perspectives. In the quantitative analysis, key variables of the liquid film are measured, namely mean film thickness, disturbance wave height, and frequency. Variations in the analyzed variables indicate minor deviations, which are not likely to be caused by the technique used. However, all three methodologies exhibited errors that are estimated to be within a maximum of 10%, with a mean value of approximately 8%.

A Novel Traffic Prediction Method Using Machine Learning for Energy Efficiency in Service Provider Networks.

This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including recurrent neural networks (RNNs), long short-term memory (LSTM), gated recurrent units (GRUs), and online sequential extreme learning machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results show that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems.

Speaker Counting Based on a Novel Hive Shaped Nested Microphone Array by WPT and 2D Adaptive SRP Algorithms in Near-Field Scenarios.

Speech processing algorithms, especially sound source localization (SSL), speech enhancement, and speaker tracking are considered to be the main fields in this application. Most speech processing algorithms require knowing the number of speakers for real implementation. In this article, a novel method for estimating the number of speakers is proposed based on the hive shaped nested microphone array (HNMA) by wavelet packet transform (WPT) and 2D sub-band adaptive steered response power (SB-2DASRP) with phase transform (PHAT) and maximum likelihood (ML) filters, and, finally, the agglomerative classification and elbow criteria for obtaining the number of speakers in near-field scenarios. The proposed HNMA is presented for aliasing and imaging elimination and preparing the proper signals for the speaker counting method. In the following, the Blackman-Tukey spectral estimation method is selected for detecting the proper frequency components of the recorded signal. The WPT is considered for smart sub-band processing by focusing on the frequency bins of the speech signal. In addition, the SRP method is implemented in 2D format and adaptively by ML and PHAT filters on the sub-band signals. The SB-2DASRP peak positions are extracted on various time frames based on the standard deviation (SD) criteria, and the final number of speakers is estimated by unsupervised agglomerative clustering and elbow criteria. The proposed HNMA-SB-2DASRP method is compared with the frequency-domain magnitude squared coherence (FD-MSC), i-vector probabilistic linear discriminant analysis (i-vector PLDA), ambisonics features of the correlational recurrent neural network (AF-CRNN), and speaker counting by density-based classification and clustering decision (SC-DCCD) algorithms on noisy and reverberant environments, which represents the superiority of the proposed method for real implementation.

A New COVID-19 Detection Method Based on CSK/QAM Visible Light Communication and Machine Learning.

This article proposes a novel method for detecting coronavirus disease 2019 (COVID-19) in an underground channel using visible light communication (VLC) and machine learning (ML). We present mathematical models of COVID-19 Deoxyribose Nucleic Acid (DNA) gene transfer in regular square constellations using a CSK/QAM-based VLC system. ML algorithms are used to classify the bands present in each electrophoresis sample according to whether the band corresponds to a positive, negative, or ladder sample during the search for the optimal model. Complexity studies reveal that the square constellation N=22i×22i,(i=3) yields a greater profit. Performance studies indicate that, for BER = 10-3, there are gains of -10 [dB], -3 [dB], 3 [dB], and 5 [dB] for N=22i×22i,(i=0,1,2,3), respectively. Based on a total of 630 COVID-19 samples, the best model is shown to be XGBoots, which demonstrated an accuracy of 96.03%, greater than that of the other models, and a recall of 99% for positive values.

A New Internet of Things Hybrid VLC/RF System for m-Health in an Underground Mining Industry.

This paper proposes a new system based on the Industrial Internet of Things (IIoT) for the monitoring of Mobile Health (m-Health) of workers in the underground mining industry. The proposed architecture uses a hybrid model in data transmission. Visible Light Communication (VLC) is used for downlink because of its narrow coverage, which aids in worker positioning. Radio frequency (RF) communication technology is used to send data for primary vital signs in the uplink, which is more efficient in transmission and is a viable solution according to the problem raised. The results obtained in terms of coverage and transmission for the downlink and uplink links show the feasibility of implementing the proposed system.

Telomeres in ecology and evolution: A review and classification of hypotheses.

Research on telomeres in the fields of ecology and evolution has been rapidly expanding over the last two decades. This has resulted in the formulation of a multitude of, often name-given, hypotheses related to the associations between telomeres and life-history traits or fitness-facilitating processes (and the mechanisms underlying them). However, the differences (or similarities) between the various hypotheses, which can originate from different research fields, are often not obvious. Our aim here is therefore to give an overview of the hypotheses that are of interest in ecology and evolution and to provide two frameworks that help discriminate among them. We group the hypotheses (i) based on their association with different research questions, and (ii) using a hierarchical approach that builds on the assumptions they make, such as about causality of telomere length/shortening and/or the proposed functional consequences of telomere shortening on organism performance. Both our frameworks show that there exist parallel lines of thoughts in different research fields. Moreover, they also clearly illustrate that there are in many cases competing hypotheses within clusters, and that some of these even have contradictory assumptions and/or predictions. We also touch upon two topics in telomere research that would benefit from further conceptualization. This review should help researchers, both those familiar with and those new to the subject, to identify future avenues of research.

Quaternary E-W Extension Uplifts Kythira Island and Segments the Hellenic Arc.

Several crustal and lithospheric mechanisms lead to deformation and vertical motion of the upper plate during subduction, but their relative contribution is often enigmatic. Multiple areas of the Hellenic Forearc have been uplifting since Plio-Quaternary times, yet spatiotemporal characteristics and sources of this uplift are poorly resolved. The remarkable geology and geomorphology of Kythira Island, in the southwestern Hellenic forearc, allow for a detailed tectonic reconstruction since the Late Miocene. We present a morphotectonic map of the island, together with new biostratigraphic dating and detailed analyses of active fault strikes and marine terraces. We find that the Tortonian-Pliocene stratigraphy in Kythira records ∼100 m of subsidence, and a wide coastal rasa marks the ∼2.8-2.4 Ma maximum transgression. Subsequent marine regression of ∼300-400 m and minor E-W tilt are recorded in ∼12 marine terrace levels for which we estimate uplift rates of ∼0.2-0.4 mm/yr. Guided by simple landscape evolution models, we interpret the coastal morphology as the result of initial stability or of slow, gradual sea-level drop since ∼2.8-2.4 Ma, followed by faster uplift since ∼1.5-0.7 Ma. Our findings on- and offshore suggest that E-W extension is the dominant mode of regional active upper crustal deformation, and N-S normal faults accommodate most, if not all of the uplift on Kythira. We interpret the initiation of E-W extension as the result of a change in plate boundary conditions, in response to either propagation of the North Anatolian Fault, incipient collision with the African plate, mantle dynamics or a combination thereof.

3D Multiple Sound Source Localization by Proposed T-Shaped Circular Distributed Microphone Arrays in Combination with GEVD and Adaptive GCC-PHAT/ML Algorithms.

Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article, a combination of one-step-based method based on the generalized eigenvalue decomposition (GEVD), and a two-step-based method based on the adaptive generalized cross-correlation (GCC) by using the phase transform/maximum likelihood (PHAT/ML) filters along with a novel T-shaped circular distributed microphone array (TCDMA) is proposed for 3D multiple simultaneous SSL. In addition, the low computational complexity advantage of the GCC algorithm is considered in combination with the high accuracy of the GEVD method by using the distributed microphone array to eliminate spatial aliasing and thus obtain more appropriate information. The proposed T-shaped circular distributed microphone array-based adaptive GEVD and GCC-PHAT/ML algorithms (TCDMA-AGGPM) is compared with hierarchical grid refinement (HiGRID), temporal extension of multiple response model of sparse Bayesian learning with spherical harmonic (SH) extension (SH-TMSBL), sound field morphological component analysis (SF-MCA), and time-frequency mixture weight Bayesian nonparametric acoustical holography beamforming (TF-MW-BNP-AHB) methods based on the mean absolute estimation error (MAEE) criteria in noisy and reverberant environments on simulated and real data. The superiority of the proposed method is presented by showing the high accuracy and low computational complexity for 3D multiple simultaneous SSL.

An Enhanced VLC Channel Model for Underground Mining Environments Considering a 3D Dust Particle Distribution Model.

Underground Mining (UM) is a hostile industry that generally requires a wireless communication system as a cross-cutting axis for its optimal operation. Therefore, in the last five years, it has been shown that, in addition to radio-frequency-based communication links, wireless optical communications, such as Visible Light Communication (VLC), can be applied to UM environments. The application of VLC systems in underground mines, known as UM-VLC, must take into account the unique physical features of underground mines. Among the physical phenomena found in underground mines, the most important ones are the positioning of optical transmitters and receivers, irregular walls, shadowing, and a typical phenomenon found in tunnels known as scattering, which is caused by the atmosphere and dust particles. Consequently, it is necessary to use proper dust particle distribution models consistent with these scenarios to describe the scattering phenomenon in a coherent way in order to design realistic UM-VLC systems with better performance. Therefore, in this article, we present an in-depth study of the interaction of optical links with dust particles suspended in the UM environment and the atmosphere. In addition, we analytically derived a hemispherical 3D dust particle distribution model, along with its main statistical parameters. This analysis allows to develop a more realistic scattering channel component and presents an enhanced UM-VLC channel model. The performance of the proposed UM-VLC system is evaluated using computational numerical simulations following the IEEE 802.1.5.7 standard in terms of Channel Impulse Response (CIR), received power, Signal-to-Noise-Ratio (SNR), Root Mean Square (RMS) delay spread, and Bit Error Rate (BER). The results demonstrate that the hemispherical dust particle distribution model is more accurate and realistic in terms of the metrics evaluated compared to other models found in the literature. Furthermore, the performance of the UM-VLC system is negatively affected when the number of dust particles suspended in the environment increases.

A Novel and Adaptive Angle Diversity-Based Receiver for 6G Underground Mining VLC Systems.

Visible light communication (VLC) is considered an enabling technology for future 6G wireless systems. Among the many applications in which VLC systems are used, one of them is harsh environments such as Underground Mining (UM) tunnels. However, these environments are subject to degrading environmental and intrinsic challenges for optical links. Therefore, current research should focus on solutions to mitigate these problems and improve the performance of Underground Mining Visible Light Communication (UM-VLC) systems. In this context, this article presents a novel solution that involves an improvement to the Angle Diversity Receivers (ADRs) based on the adaptive orientation of the Photo-Diodes (PDs) in terms of the Received Signal Strength Ratio (RSSR) scheme. Specifically, this methodology is implemented in a hemidodecahedral ADR and evaluated in a simulated UM-VLC scenario. The performance of the proposed design is evaluated using metrics such as received power, user data rate, and bit error rate (BER). Furthermore, our approach is compared with state-of-the-art ADRs implemented with fixed PDs and with the Time of Arrival (ToA) reception method. An improvement of at least 60% in terms of the analyzed metrics compared to state-of-the-art solutions is obtained. Therefore, the numerical results demonstrate that the hemidodecahedral ADR, with adaptive orientation PDs, enhances the received optical signal. Furthermore, the proposed scheme improves the performance of the UM-VLC system due to its optimum adaptive angular positioning, which is completed according to the strongest optical received signal power. By improving the performance of the UM-VLC system, this novel method contributes to further consideration of VLC systems as potential and enabling technologies for future 6G deployments.

Effect of intravenous iron on functional outcomes in hip fracture: a randomised controlled trial.

OBJECTIVES: to determine the safety and effect of intravenous iron sucrose on functional outcomes, delirium, nosocomial infections and transfusion requirements in older patients with hip fracture. DESIGN: single-centre randomised, double-blind, placebo-controlled clinical trial. SETTING AND PARTICIPANTS: orthogeriatric share care service at an academic tertiary care hospital. A total of 253 patients were recruited: 126 patients were assigned to intravenous iron and 127 to placebo. METHODS: on days 1, 3 and 5 after admission, the iron group received 200 mg Venofer® (iron sucrose) in 100 ml saline and the placebo group 100 ml saline. The primary outcome was absolute functional gain, considered as Barthel index (BI) at discharge minus BI on admission. Secondary outcomes included incidence of postoperative delirium according to the confusion assessment method, proportion of patients recovering prior functional status at 3 months, postoperative transfusion requirements, haemoglobin at 3 months, incidence of nosocomial infections and safety. RESULTS: the median participant age was 87 (interquartile range, 82.5-91.5) years. Most patients were female (72.7%), and the median previous BI was 81(59-95). No significant effect of intravenous iron was observed for the primary outcome: the median AFG score was 17.1 points (4.8-23.3) in the intravenous iron group and 16 points (6-26) in the placebo group (P = 0.369). No significant treatment effects were observed for other functional outcomes or secondary end points. CONCLUSION: while we found no impact of intravenous iron sucrose on functional recovery, incidence of postoperative delirium, transfusion requirements, haemoglobin at 3 months, mortality and nosocomial infections rates in older patients with hip fracture, we did find that the intervention was safe.

Training strategies to minimize interchannel interference effects using supervised learning in gridless Nyquist-WDM systems.

The dynamism envisioned in future high-capacity gridless optical networks requires facing several challenges in distortion mitigation, such as the mitigation of interchannel interference (ICI) effects in any optical channel without information of their adjacent channels. Machine learning (ML)-based techniques have been proposed in recent works to estimate and mitigate different optical impairments with promising results. We propose and evaluate two training strategies for supervised learning algorithms with the aim to minimize ICI effects in a gridless 3×16-Gbaud 16-quadrature amplitude modulation (QAM) Nyquist-wavelength-division multiplexing (WDM) system. One strategy, called updating strategy, is based on symbol training sequence, and the other one, called characterization strategy, is based on an offline training using a previous system characterization. Artificial neural networks (ANN), support vector machine (SVM), K-nearest neighbors (KNN), and extreme learning machine (ELM) algorithms are explored for both training strategies. Experimental results showed a bit error rate (BER) improvement at low training lengths for both training strategies, for instance, gains up to ∼4dB in terms of optical signal-to-noise ratio were achieved in a back-to-back scenario. Besides, the KNN and ELM algorithms showed significant BER reduction in transmission over 250 km optical fiber. Additionally, we carried out a brief computational complexity analysis where ELM presented only 1.9% of ANN processing time. Hence, the use of ML-based techniques could enhance the optical gridless networks performance and consequently fulfill future traffic demands.

Pulmonary Function Testing in Patients with Tracheostomies: Feasibility and Technical Considerations.

PURPOSE: Pulmonary function testing (PFT) in patients with tracheostomies has been perceived as difficult to perform and clinically unreliable. We studied the feasibility, quality, repeatability and clinical significance of PFT. METHODS: Patients with tracheostomies that underwent PFT from January 1, 2010 to February 29, 2012 were identified. Clinical history and PFT data were reviewed retrospectively. RESULTS: Fifty patients (88% men) were identified. Forty-seven (94%) patients were able to perform PFT. Acceptable repeatability was obtained for FVC in 39 (83%) and for FEV1 in 41 (87%). Patients with tracheostomies showed difficulty in meeting ATS end-of-test criteria; only 9 (19%) met plateau criteria and 25 (53%) had exhalation times of greater than 6 s. Obstructive pattern was observed in 30 (64%) and restrictive pattern in 9 (19%). DLCO measurements were attempted in 43 patients and satisfactorily obtained in 34 (79%). CONCLUSIONS: PFT can be performed with reliability in patients with tracheostomies, and they are useful for detecting and classifying types of lung dysfunction.

Neuroevolution-Based Adaptive Antenna Array Beamforming Scheme to Improve the V2V Communication Performance at Intersections.

The opportunistic exchange of information between vehicles can significantly contribute to reducing the occurrence of accidents and mitigating their damages. However, in urban environments, especially at intersection scenarios, obstacles such as buildings and walls block the line of sight between the transmitter and receiver, reducing the vehicular communication range and thus harming the performance of road safety applications. Furthermore, the sizes of the surrounding vehicles and weather conditions may affect the communication. This makes communications in urban V2V communication scenarios extremely difficult. Since the late notification of vehicles or incidents can lead to the loss of human lives, this paper focuses on improving urban vehicle-to-vehicle (V2V) communications at intersections by using a transmission scheme able of adapting to the surrounding environment. Therefore, we proposed a neuroevolution of augmenting topologies-based adaptive beamforming scheme to control the radiation pattern of an antenna array and thus mitigate the effects generated by shadowing in urban V2V communication at intersection scenarios. This work considered the IEEE 802.11p standard for the physical layer of the vehicular communication link. The results show that our proposal outperformed the isotropic antenna in terms of the communication range and response time, as well as other traditional machine learning approaches, such as genetic algorithms and mutation strategy-based particle swarm optimization.

Development of Ferromagnetic Materials Containing Co2P, Fe2P Phases from Organometallic Dendrimers Precursors.

The development of synthesis methods to access advanced materials, such as magnetic materials that combine multimetallic phosphide phases, remains a worthy research challenge. The most widely used strategies for the synthesis of magnetic transition metal phosphides (TMPs) are organometallic approaches. In this study, Fe-containing homometallic dendrimers and Fe/Co-containing heterometallic dendrimers were used to synthesize magnetic materials containing multimetallic phosphide phases. The crystalline nature of the nearly aggregated particles was indicated for both designed magnetic samples. In contrast to heterometallic samples, homometallic samples showed dendritic effects on their magnetic properties. Specifically, saturation magnetization (Ms) and coercivity (Hc) decrease as dendritic generation increases. Incorporating cobalt into the homometallic dendrimers to prepare the heterometallic dendrimers markedly increases the magnetic properties of the magnetic materials from 60 to 75 emu/g. Ferromagnetism in homometallic and heterometallic particles shows different responses to temperature changes. For example, heterometallic samples were less sensitive to temperature changes due to the presence of Co2P in contrast to the homometallic ones, which show an abrupt change in their slopes at a temperature close to 209 K, which appears to be related to the Fe2P ratios. This study presents dendrimers as a new type of precursor for the assembly of magnetic materials containing a mixture of iron- and cobalt-phosphides phases with tunable magnetism, and provides an opportunity to understand magnetism in such materials.

Lens differentiation is characterized by stage-specific changes in chromatin accessibility correlating with differentiation state-specific gene expression.

Changes in chromatin accessibility regulate the expression of multiple genes by controlling transcription factor access to key gene regulatory sequences. Here, we sought to establish a potential function for altered chromatin accessibility in control of key gene expression events during lens cell differentiation by establishing genome-wide chromatin accessibility maps specific for four distinct stages of lens cell differentiation and correlating specific changes in chromatin accessibility with genome-wide changes in gene expression. ATAC sequencing was employed to generate chromatin accessibility profiles that were correlated with the expression profiles of over 10,000 lens genes obtained by high-throughput RNA sequencing at the same stages of lens cell differentiation. Approximately 90,000 regions of the lens genome exhibited distinct changes in chromatin accessibility at one or more stages of lens differentiation. Over 1000 genes exhibited high Pearson correlation coefficients (r â€‹> â€‹0.7) between altered expression levels at specific stages of lens cell differentiation and changes in chromatin accessibility in potential promoter (-7.5kbp/+2.5kbp of the transcriptional start site) and/or other potential cis-regulatory regions ( ±10 â€‹kb of the gene body). Analysis of these regions identified consensus binding sequences for multiple transcription factors including members of the TEAD, FOX, and NFAT families of transcription factors as well as HIF1a, RBPJ and IRF1. Functional mapping of genes with high correlations between altered chromatin accessibility and differentiation state-specific gene expression changes identified multiple families of proteins whose expression could be regulated through changes in chromatin accessibility including those governing lens structure (BFSP1,BFSP2), gene expression (Pax-6, Sox 2), translation (TDRD7), cell-cell communication (GJA1), autophagy (FYCO1), signal transduction (SMAD3, EPHA2), and lens transparency (CRYBB1, CRYBA4). These data provide a novel relationship between altered chromatin accessibility and lens differentiation and they identify a wide-variety of lens genes and functions that could be regulated through altered chromatin accessibility. The data also point to a large number of potential DNA regulatory sequences and transcription factors whose functional analysis is likely to provide insight into novel regulatory mechanisms governing the lens differentiation program.

Impact of rapid weight loss after bariatric surgery on the prevalence of arterial hypertension in severely obese patients with chronic kidney disease.

BACKGROUND: Arterial hypertension (HTN) is one of the most important risk factors for the development and progression of chronic kidney disease (CKD). Rapid weight loss after bariatric interventions has a positive impact on blood pressure levels of hypertensive patients. The aim of our study is to assess the prevalence of HTN in patients with CKD after bariatric surgery (BS). METHODS: We retrospectively reviewed severely obese patients who underwent BS from 2010 to 2017. We used guidelines of the American College of Cardiology to define HTN. Only patients meeting ACC criteria and the calculation of estimated glomerular filtration rate (eGFR) using CKD epidemiology collaboration study equation preoperatively and at 12-month follow-up were included in the analysis. RESULTS: From a total of 2900 patients, 29.13% (845) met the required criteria and had variables for the calculation of eGFR recorded preoperatively. 36.92% (312) had preoperative HTN and s classified as CKD stage ≥ 2. We observed a predominantly female population 63.83% (203) with mean age of 54.10 ± 11.58. Patients preoperatively classified in CKD 2, 3a, and 3b exhibited the greatest prevalence reduction of HTN at 12-month follow-up (68.59%, n = 214 vs. 36.59%, n = 114; 16.67%, n = 52 vs. 6.41%, n = 20; 7.69%, n = 24 vs. 1.28%, n = 4; p < 0.0001). A marked improvement in CKD was also observed along with improvement in HTN. The greatest benefit corresponded to patients classified preoperatively in CKD 2, 3a and 3b. A total of n = 70 (62.5%) patients with HTN were classified as CKD 2 preoperatively compared to n = 55 (49.11%) at 12-month follow-up (p = 0.0436). Similarly, n = 22 (19.64%) patients with HTN were classified preoperatively as CKD 3a compared to n = 7 (6.25%) and n = 12 (10.71%) patients as CKD 3b compared to n = 4 (3.57%) during the same time period (p = 0.0028, p = 0.0379, respectively). CONCLUSIONS: Rapid weight loss after BS significantly reduces prevalence of HTN in all stages of CKD at 12-month follow-up. Additionally, there was a positive impact on classification of CKD at 12-month follow-up.