Serial Data Research Articles

Impact of cardiac resynchronisation therapy in patients with cardiac sarcoidosis

Abstract Background Implantation of a device is usually required in cardiac sarcoidosis (CS) patients presenting with advanced conduction abnormalities or ventricular arrhythmias. A cardiac resynchronisation therapy (CRT) device is often chosen in patients with concomitant left ventricular systolic impairment. The role of CRT in CS is not well established. Purpose To describe the cohort of CS patients with CRT device in situ in our hospital focusing on the short-term effect in serial echocardiography and long-term outcomes on morbidity and mortality. Methods All consecutive CS patients with a CRT device in situ were identified in our CS database (2005–2022). A confident CS diagnosis was provided after review of all relevant clinical and imaging baseline data in our CS multi-disciplinary meeting and a consensus decision for CRT-D implantation was made based on international guidelines. All patients were followed up for at least 6 months with serial echocardiography. Serial data regarding symptoms, rhythm disturbance and echocardiographic parameters were obtained and comparisons were performed using Wilcoxon signed rank test. Results A total of 51 CS patients with CRT-D were identified (mean age: 57±10 years old). Patients were male predominant (64.7%) and Caucasian in origin (86.2%). Extra-cardiac sarcoidosis was confirmed histologically in 33 (64.7%) patients. The prevalence of smoking, diabetes, hypertension and ischaemic heart disease was 27.5%, 21.6%, 49.0% and 7.8% respectively. At the time of device implantation or during follow-up, 43 (84.3%) patients were found to have active cardiac sarcoidosis on cardiac PET. Post CRT implantation there was a significant difference in LV ejection fraction (35.9±15.0% vs 42.2±14.1%, p<0.001), LV end-systolic diameter (4.90±1.46 cm vs 4.62±1.32 cm, p=0.012) and LV end-diastolic diameter (5.99±1.18 cm vs 5.66±1.06 cm, p<0.001). No significant changes were observed in the right ventricular function (p=0.09) and severity of mitral regurgitation (p=0.40). There was one patient who experienced acute heart failure decompensation admission within six months of CRT-D implantation. The New York Heart Association (NYHA) class improved in 26 patients (51.0%), worsened in 4 (7.8%) patients and remained the same in 21 (41.2%) patients at 6 months post CRT-implantation. During the mean follow up of 47.6 months, the composite end-point of death and cardiac transplantation was reached in 9 (17.6%) patients (8 deaths and 1 cardiac transplantation). 5 patients had major complications including a large haematoma, a small atrio-septal defect, haemothorax, device associated endocarditis and lead fracture. Minor wound infections were seen in 3 patients and 4 patients received inappropriate shock or anti-tachycardia pacing. Conclusions CRT in cardiac sarcoidosis patients is associated with short-term improvement in LV remodelling and functional status but over a four year follow up, morbidity and mortality are common. Funding Acknowledgement Type of funding sources: None.

State-of-Health Prediction of Lithium-Ion Batteries Based on CNN-BiLSTM-AM

State-of-Health (SOH) prediction of lithium-ion batteries is crucial in battery management systems. In order to guarantee the safe operation of lithium-ion batteries, a hybrid model based on convolutional neural network (CNN)-bidirectional long short-term memory (BiLSTM) and attention mechanism (AM) is developed to predict the SOH of lithium-ion batteries. By analyzing the charging and discharging process of batteries, the indirect health indicator (HI), which is highly correlated with capacity, is extracted in this paper. HI is taken as the input of CNN, and the convolution and pooling operations of CNN layers are used to extract the features of battery time series data. On this basis, a BiLSTM depth model is built in this paper to collect the data coming from CNN forward and reverse dependencies and further emphasize the correlation between the serial data by AM to obtain an accurate SOH estimate. Experimental results based on NASA PCoE lithium-ion battery data demonstrate that the proposed hybrid model outperforms other single models, with the root mean square error (RMSE) of SOH prediction results all less than 0.01, and can accurately predict the SOH of lithium-ion batteries.

Pregnancy outcomes in women with Ebstein's anomaly: data from the EORP Registry of Pregnancy and Cardiac Disease (ROPAC)

Abstract Background Ebstein's anomaly is a rare congenital cardiac condition characterized by displacement of the posterior and septal leaflets of the tricuspid valve towards the apex of the right ventricle. The ESC Guidelines for the management of cardiovascular diseases during pregnancy categorize women with uncomplicated Ebstein's anomaly as modified World Health Organization (mWHO) risk class II. However, data regarding pregnancy outcomes in women with Ebstein's anomaly are scarce. Purpose To evaluate the maternal and perinatal risks of pregnancy in women with Ebstein's anomaly. Methods All patients with Ebstein's anomaly who had been included in the Registry of Pregnancy and Cardiac Disease (ROPAC), which is an international, prospective, observational registry of pregnant women with underlying cardiac disease (n=5739), were evaluated. The primary outcome was the occurrence of a major adverse cardiac event, defined as maternal mortality, heart failure, arrhythmia, thromboembolic events or endocarditis. The secondary outcomes were obstetric and perinatal outcomes and the influence of pregnancy on tricuspid valve regurgitation. Results Thirty-six hospitals in 22 countries enrolled 81 women with Ebstein's anomaly (mean age 29.7 years, 46.9% nulliparous). Seven (8.6%) women had a history of tricuspid valve repair and a further eight (9.9%) of tricuspid replacement. Most women (67.9%) were in NYHA class I. At least one major adverse cardiac event occurred in 8 (9.9%) pregnancies, including heart failure (n=6), supraventricular arrhythmia (n=3) and thromboembolic events (n=2). There was no maternal death. Almost half of the women underwent a Caesarean section (49%) and preterm delivery occurred in 24.7%. Neonatal mortality was 2.5% and four (4.9%) infants had neonatal congenital heart disease. Serial echocardiographic data pre- and postpregnancy were available in 14 women. There was no clear deterioration in tricuspid regurgitation (see Picture 1). Conclusion Although mortality was zero, in 10% of the pregnant women with Ebstein's anomaly a major adverse cardiac event occurred, most frequently heart failure or arrhythmia. Therefore, women with Ebstein's anomaly should be categorized as mWHO risk class II at least, but perhaps more correctly as II–III. Preconception counseling is crucial, so that women are aware of the potential risks of maternal morbidity, preterm delivery and congenital heart disease and the need for careful monitoring during pregnancy. Funding Acknowledgement Type of funding sources: None.

Systematic Design of Loop Circuit Topologies Using C/I DS Methodology

Herein, a systematic approach for designing loop topology circuits, such as ring oscillators (ROs), latches, and frequency dividers, is proposed. The design flow is devised to implement the target circuits with minimum power dissipation at the desired operating frequency. Using a modified <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C/I_{\text {DS}}$ </tex-math></inline-formula> methodology, several design examples in different technology nodes are provided showing less than ±5% error in the estimated circuit performance, confirmed by experimental data in 0.18 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\mu }\text{m}$ </tex-math></inline-formula> technology. A standardized procedure has been developed to extract fundamental device characteristics for different technology nodes, which are subsequently fed into an optimizer script. Examples for implementing current-steering ROs and frequency dividers will be provided. The proposed approach can be employed to custom design high-speed sequential logic circuits, as well as voltage-controlled oscillators (VCOs), digitally controlled oscillators (DCOs), and frequency dividers for applications such as clock generators, sequential circuits, and serial data transceivers in modern integrated systems.

Excess Reintervention With Mitroflow Prosthesis for Aortic Valve Replacement: Ten-Year Outcomes of a Randomized Trial

BackgroundCurrent bioprostheses are considered to have improved durability and better hemodynamic performance compared with previous designs, but there are limited comparative data on late outcomes. MethodsFrom 2009 through 2011, 300 adults with severe aortic valve stenosis undergoing aortic valve replacement (AVR) were randomly assigned to receive Edwards Magna, St Jude Epic, or Sorin Mitroflow bioprostheses (n = 100, n = 101, n = 99, respectively). Overall survival was analyzed using Kaplan-Meier and Cox proportional hazards methods, whereas competing risk analysis was used for all time-to-event outcomes. Serial echocardiographic data were fitted with longitudinal models stratified by implant valve size. ResultsDuring median follow-up of 9.8 years (interquartile range, 8.7-10.2), 10-year survival was 50% for the Magna group, 42% for the Epic group, and 41% for the Mitroflow group (P = .415). Cumulative risk of stroke was 9% at 10 years, and rates were comparable for the three groups. Indexed aortic valve area and mean gradients were similar among the three groups receiving 19 mm and 21 mm valves, but in larger (23 mm or more) prostheses, gradients were lower (P < .001) and indexed aortic valve areas were higher in the Magna group (P < .001). The 10-year risk of endocarditis differed by group (P = .033), with higher incidence in the Mitroflow vs the Magna group (7% vs 0%, P = .019). Late risk of reinterventions in the Mitroflow group was 22%, compared with 0% in the Magna group (P < .001) and 5% in the Epic group (P = .008). ConclusionsThe Magna valve had the lowest gradients and largest indexed aortic valve area with larger implant sizes. The Mitroflow bioprosthesis is associated with an increased rate of reintervention and possible increased risk of infection compared with Magna and Epic valves.

Influence of Intra-Regional Trading on Uganda's Economic Progress

Purpose: The purpose of this study is to determine the trade impact of the EAC Customs Union and to analyze the impact of intra-EAC trade on Uganda's economic growth.&#x0D; Methodology: The study employed serial data and a non-experimental study design. Regression analysis was used capturing causal relationships between variables and measuring the impact of trading and shaping within the EAC customs union.&#x0D; Findings: The finding shows that after the formation of the custom union, the volume of trade in Uganda has increased proportionately by 0.9083 percent.&#x0D; Conclusion: The effect of the custom union on Uganda intra-EAC trade, the EAC dummy coefficient was also found to be positive and statistically significant.&#x0D; Recommendation: The study recommended the formation of the EAC Customs Union which is an important step in the process of deepening regional integration among its members.

FPGA Implementation of Digital Modulation Schemes Using Verilog HDL

Abstract: This paper describes the design and development of an FPGA-based digital Modulation Scheme for high-resolution Communication Application. We are focusing on implementation of Verilog based code simulation for fundamental and widely used digital modulation techniques such as Binary Amplitude-shift keying (BASK), Binary Frequency-shift keying (BFSK), Binary Phase-shift keying (BPSK) and Quadrature Phase Shift Keying(QPSK). In this work the idea of sinusoidal signals that have been generated is plain sailing in nature and based on fundamentals of signal sampling and quantization. Such concept of sinusoidal signals generation is not unfamiliar but somehow simplified using sampling and quantization in time and amplitude domain, respectively. The whole simulation is done on Modelsim and Xilinx-ISE using VERILOG Hardware descriptive language. The work has been accomplished on Thirty two bit serial data transmission with self-adjustable carrier frequency and bit duration length.

Nitrogen dioxide increases the risk of disease progression in idiopathic pulmonary fibrosis.

Air pollution affects clinical course and prognosis of idiopathic pulmonary fibrosis (IPF). However, the effect of individual exposure to air pollutants on disease progression is unclear. We aimed to identify the effect of individual exposure to nitrogen dioxide (NO2 ) and particulate matter (aerodynamic diameter ≤ 10μm [PM10 ]) on disease progression in patients with IPF. The serial lung function data of 946 IPF patients (mean age: 65.4 years, male: 80.9%) were analysed. Individual-level long-term exposures to NO2 and PM10 at the residential addresses of patients were estimated using a national-scale exposure prediction model, constructed based on air quality regulatory monitoring data. Progression was defined as a relative decline (≥10%) in forced vital capacity. Individual- and area-level covariates were adjusted in the primary analysis model. Overall, 547 patients (57.8%) experienced progression during a median follow-up of 1.0year (interquartile range: 0.4-2.6 years). In the primary model, a 10-ppb increase in NO2 concentration was associated with a 10.5% increase in the risk of progression (hazard ratio [HR]=1.105; 95% CI=1.000-1.219) in patients with IPF. There was also an increasing trend of progression in patients with IPF according to the second to fourth quartiles of NO2 (Q2 [HR=1.299; 95% CI=0.972-1.735], Q3 [1.409; 1.001-1.984], Q4 [1.598; 1.106-2.310]) compared to the first quartile. We found no association between PM10 and progression in IPF patients. Our data suggest that increased individual exposure to NO2 can increase the risk of progression in patients with IPF.

Cryptography-Based Medical Signal Securing Using Improved Variation Mode Decomposition with Machine Learning Techniques.

There is no question about the value that digital signal processing brings to the area of biomedical research. DSP processors are used to sample and process the analog inputs that are received from a human organ. These inputs come from the organ itself. DSP processors, because of their multidimensional data processing nature, are the electrical components that take up the greatest space and use the most power. In this age of digital technology and electronic gizmos, portable biomedical devices represent an essential step forward in technological advancement. Electrocardiogram (ECG) units are among the most common types of biomedical equipment, and their functions are absolutely necessary to the process of saving human life. In the latter part of the 1990s, portable electrocardiogram (ECG) devices began to appear on the market, and research into their signal processing and electronics design capabilities continues today. System-on-chip (SoC) design refers to the process through which the separate computing components of a DSP unit are combined onto a single chip in order to achieve greater power and space efficiency. In the design of biomedical DSP devices, this body of research presents a number of different solutions for reducing power consumption and space requirements. Using serial or parallel data buses, which are often the region that consumes the most power, it is possible to send data between the system-on-chip (SoC) and other components. To cut down on the number of needless switching operations that take place during data transmission, a hybrid solution that makes use of the shift invert bus encoding scheme has been developed. Using a phase-encoded shift invert bus encoding approach, which embeds the two-bit indication lines into a single-bit encoded line, is one way to solve the issue of having two distinct indicator bits. This method reduces the problem. The PESHINV approach is compared to the SHINV method that already exists, and the comparison reveals that the suggested PESHINV method reduces the total power consumption of the encoding circuit by around 30 percent. The computing unit of the DSP processor is the target of further optimization efforts. Virtually, all signal processing methods need memory and multiplier circuits to function properly.

Robust monitoring of multivariate processes with short‐ranged serial data correlation

AbstractControl charts are commonly used in practice for detecting distributional shifts of sequential processes. Traditional statistical process control (SPC) charts are based on the assumptions that process observations are independent and identically distributed and follow a parametric distribution when the process is in‐control (IC). In practice, these assumptions are rarely valid, and it has been well demonstrated that these traditional control charts are unreliable to use when their model assumptions are invalid. To overcome this limitation, nonparametric SPC has become an active research area, and some nonparametric control charts have been developed. But, most existing nonparametric control charts are based on data ordering and/or data categorization of the original process observations, which would result in information loss in the observed data and consequently reduce the effectiveness of the related control charts. In this paper, we suggest a new multivariate online monitoring scheme, in which process observations are first sequentially decorrelated, the decorrelated data of each quality variable are then transformed using their estimated IC distribution so that the IC distribution of the transformed data would be roughly N(0, 1), and finally the conventional multivariate exponentially weighted moving average (MEWMA) chart is applied to the transformed data of all quality variables for online process monitoring. This chart is self‐starting in the sense that estimates of all related IC quantities are updated recursively over time. It can well accommodate stationary short‐range serial data correlation, and its design is relatively simple since its control limit can be determined in advance by a Monte Carlo simulation. Because information loss due to data ordering and/or data categorization is avoided in this approach, numerical studies show that it is reliable to use and effective for process monitoring in various cases considered.

Changes in HIV care continuum indicators among community-based samples of HIV-infected people who inject drugs and men who have sex with men across 21 cities in India

ABSTRACT Monitoring key populations’ progress towards UNAIDS 90-90-90 targets is essential to achieving HIV/AIDS epidemic control. Using serial cross-sectional data, we evaluated changes in HIV care continuum among people who inject drugs(PWID) and men who have sex with men(MSM) in India. Cross-sectional baseline (2012/2013) and follow-up (2016/2017) samples were recruited using respondent-driven sampling across 21 cities. All participants were tested for HIV and RNA measured in HIV-positive participants. Linear regression was used to model temporal site-level changes in continuum indicators in MSM versus PWID. At baseline, we recruited 2,544 HIV-infected PWID and 1,086 HIV-infected MSM. At follow-up, we recruited 2,517 HIV-infected PWID and 1,763 HIV-infected MSM. At baseline, there were no significant differences in continuum indicators between MSM and PWID. At follow-up, compared to PWID, the proportion of MSM reaching each care continuum indicator—awareness of status, receipt of care, ART use, viral suppression—increased by 15-33 percentage points: 78% of MSM versus 49% of PWID were aware of their status (p < 0.01); 56% of MSM versus 32% of PWID were virologically suppressed (p = 0.05). MSM showed marked improvements across the care continuum, whereas PWID lagged and may require additional intervention. Differential improvement in HIV engagement may necessitate population-specific interventions and routine surveillance to facilitate HIV elimination.

Prediction of response to neoadjuvant chemotherapy in breast cancer with recurrent neural networks and raw ultrasound signals

Objective. Prediction of the response to neoadjuvant chemotherapy (NAC) in breast cancer is important for patient outcomes. In this work, we propose a deep learning based approach to NAC response prediction in ultrasound (US) imaging. Approach. We develop recurrent neural networks that can process serial US imaging data to predict chemotherapy outcomes. We present models that can process either raw radio-frequency (RF) US data or regular US images. The proposed approach is evaluated based on 204 sequences of US data from 51 breast cancers. Each sequence included US data collected before the chemotherapy and after each subsequent dose, up to the 4th course. We investigate three pre-trained convolutional neural networks (CNNs) as back-bone feature extractors for the recurrent network. The CNNs were pre-trained using raw US RF data, US b-mode images and RGB images from the ImageNet dataset. The first two networks were developed using US data collected from malignant and benign breast masses. Main results. For the pre-treatment data, the better performing network, with back-bone CNN pre-trained on US images, achieved area under the receiver operating curve (AUC) of 0.81 (±0.04). Performance of the recurrent networks improved with each course of the chemotherapy. For the 4th course, the better performing model, based on the CNN pre-trained with RGB images, achieved AUC value of 0.93 (±0.03). Statistical analysis based on the DeLong test presented that there were no significant differences in AUC values between the pre-trained networks at each stage of the chemotherapy (p-values > 0.05). Significance. Our study demonstrates the feasibility of using recurrent neural networks for the NAC response prediction in breast cancer US.

Synchronous chip-to-chip communication with a multi-chip resonator clock distribution network *

Superconducting digital circuits are a promising approach to build integrated systems with high energy-efficiency and computational density of the packaged chips. In such systems, performance of the data link between chips mounted on a multi-chip-module (MCM) is a critical driver of performance. In this work we report a synchronous data link using reciprocal quantum logic enabled by resonant clock distribution on-chip and on the MCM carrier. The simple physical link has only four Josephson junctions and 3 fJ/bit dissipation, including a 300 W/W cooling overhead. The driver produces a signal with 35 GHz analog bandwidth and connects to a single-ended receiver via 20 Ω Nb passive transmission line. To validate this link, we have designed, fabricated, and tested two 32 × 32 mm2 MCMs with eight 5 × 5 mm2 chips connected serially and powered by a traveling-wave clock, and with four 10 × 10 mm2 chips powered with a 2 GHz resonant clock. The traveling-wave clock MCM validates performance of the data link components and achieves a 5.4 dB AC bias margin with no degradation relative to individual chip tests. The resonator MCM validates synchronization between chips, with a measured AC bias margin up to 4.8 dB between two chips. The resonator MCM is capable of powering circuits of 4 million Josephson junctions across the four chips with a projected 10 Gbps serial data rate.

Acute clavicle fixation after blunt chest trauma: effect on pulmonary outcomes and patient disposition.

Clavicle fractures are common in patients who sustain blunt chest trauma (BCT). Recently, surgical fixation of rib fractures in patients with BCT has been shown to improve pulmonary and clinical outcomes. Therefore, the purpose of this study is to assess the role of early clavicle fixation (ECF) versus non-operative (NO) treatment for midshaft clavicle fractures in this same population. A retrospective chart review was performed in patients with midshaft clavicle fractures and BCT at a Level I Trauma Center between 2007 and 2017. Patients with pre-existing pulmonary conditions and head injuries necessitating mechanical ventilation were excluded. Demographic data, injury mechanisms, and Thoracic Trauma Severity Scores (TTS) were analyzed. Inpatient pulmonary outcomes were assessed with serial vital capacity (VC) measurements, intubation, mechanical ventilation, and pulmonary complications data. In addition, intensive care unit (ICU) and hospital length of stay (LOS), mortality, discharge location, and incidence of postoperative complications in the ECF group were also measured. Thirty-six patients underwent ECF, and 24 underwent NO treatment. The ECF cohort was statistically younger and had a greater incidence of clavicle fracture shortening than the NO group. There was no difference in pulmonary outcomes, ICU or hospital LOS, or mortality between groups. There were no complications associated with ECF. Patients who underwent ECF were more likely to discharge to home. There were no postoperative complications associated with ECF. ECF of midshaft clavicle fractures does not improve pulmonary outcomes in patients with BCT. However, despite the lack of pulmonary benefit, there appears to be no added risk of harm. Therefore, ECF is a reasonable consideration in this patient population who otherwise meet clavicle fracture operative indications.

Randomness in time-resolved serial crystallography data: alternatives to the binning and averaging approach

Randomness in time-resolved serial crystallography data: alternatives to the binning and averaging approach

Longitudinal Trends of Vascular Flow and Growth in Patients Undergoing Fontan Operation

BackgroundSingle ventricle (SV) patients undergo multiple surgeries with subsequent changes in anatomy and hemodynamics. There are little cardiac magnetic resonance (CMR) data on serial changes in these patients. This study aimed to assess longitudinal changes of SV anatomy and hemodynamics in a large cohort. MethodsAnatomy and flow in SV patients with serial CMRs performed between 2008 and 2019 at a single institution were retrospectively reviewed. Mixed-effects linear regression was used to estimate changes over time at 3 to 9 months, 1 to 5 years, and >5 years after Fontan. ResultsA total of 119 patients were included (51% with hypoplastic left heart syndrome; 77% underwent extracardiac Fontan). A total of 88 patients had 3 serial CMRs. Indexed right superior vena cava, inferior vena cava, neoaortic valve, and descending aorta area decreased over time (beta = -0.19, -0.44, and -0.23, respectively; P < .01), as did indexed right superior vena cava, neoaorta and native aorta, and descending aorta flow (beta = -0.49, -0.53, and -0.59, respectively; P < .0001). Inferior vena cava flow and its contribution to total caval flow increased (beta = 0.33; P < .0001). Indexed right and left pulmonary artery flow did not change; however, indexed left pulmonary artery area decreased (beta = -0.16; P = .0014) with time. Systemic-to-pulmonary collateral flow remained unchanged before and early after Fontan (beta = -0.54; P = .42) but decreased with time from Fontan (beta = -0.22; P < .0001). ConclusionsIn this cohort of longitudinally followed SV patients, there are significant trends in vascular size and flow over time from Fontan. These findings can be used as a framework to interpret serial CMR data in the SV and noninvasively identify deviations from expected patterns before the development of clinical symptoms.

Parallel-and-stream accelerator for computationally fast supervised learning

Two dominant distributed computing strategies have emerged to overcome the computational bottleneck of supervised learning with big data: parallel data processing in the MapReduce paradigm and serial data processing in the online streaming paradigm. Despite the two strategies' common divide-and-combine approach, they differ in how they aggregate information, leading to different trade-offs between statistical and computational performance. The authors propose a new hybrid paradigm, termed a Parallel-and-Stream Accelerator (PASA), that uses the strengths of both strategies for computationally fast and statistically efficient supervised learning. PASA's architecture nests online streaming processing into each distributed and parallelized data process in a MapReduce framework. PASA leverages the advantages and mitigates the disadvantages of both the MapReduce and online streaming approaches to deliver a more flexible paradigm satisfying practical computing needs. The authors study the analytic properties and computational complexity of PASA, and detail its implementation for two key statistical learning tasks. PASA's performance is illustrated through simulations and a large-scale data example building a prediction model for online purchases from advertising data.

A 13 Gbps 1:16 deserializer ASIC for NICA multi purpose detector project

This paper presents the design and test results of a 13 Gbps 1:16 deserializer ASIC fabricated in a 55 nm CMOS technology for Nuclotron-based Ion Collider fAcility (NICA) Multi Purpose Detector (MPD) project. The deserializer would be used in the downlink data transmission of MPD readout system to recover the serial data from the back-end to the parallel data for the front-end. The ASIC adopts a tree-type structure, consisting of a high-speed data receiver (RXDATA), a high-speed clock receiver (RXCLK), four levels of demultiplexer (DEMUX) modules, clock dividers and 16 Low-Voltage Differential Signaling (LVDS) drivers. The demultiplexer modules are composed of different numbers of high-speed DEMUX unit and low-speed DEMUX unit. The high-speed DEMUX unit and the high-frequency clock divider adopt an optimized compressed current mode logic (CML) differential structure to ensure the bandwidth with limited voltage headroom. The low-speed DEMUX unit and the low-frequency clock divider use CMOS latch to save power consumption. The duty cycle correction (DCC) circuit and the clock aligner are employed in the clock paths to ensure the correct duty cycle and aligned clock edges. In the chip test, the ASIC receives 13 Gbps serial data and outputs 16 channels of 812.5 Mbps data correctly with wide-open eye diagram. The tested power consumption is 203 mA with 1.2 V power supply including the RXDATA, the RXCLK and the 16 channels of LVDS drivers, and the core power consumption is 122.7 mA.

Acquisition and Analysis of Serial Electron Diffraction Data for Structure Determination

Acquisition and Analysis of Serial Electron Diffraction Data for Structure Determination

Complementarity of neutron, XFEL and synchrotron crystallography for defining the structures of metalloenzymes at room temperature.

Room-temperature macromolecular crystallography allows protein structures tobe determined under close-to-physiological conditions, permits dynamic freedom in protein motions and enables time-resolved studies. In the case of metalloenzymes that are highly sensitive to radiation damage, such room-temperature experiments can present challenges, including increased rates of X-ray reduction of metal centres and site-specific radiation-damage artefacts, as well as in devising appropriate sample-delivery and data-collection methods. It can also be problematic to compare structures measured using different crystal sizes and light sources. In this study, structures of a multifunctional globin, dehaloperoxidase B (DHP-B), obtained using several methods of room-temperature crystallographic structure determination are described and compared. Here, data were measured from large single crystals and multiple microcrystals using neutrons, X-ray free-electron laser pulses, monochromatic synchrotron radiation and polychromatic (Laue) radiation light sources. These approaches span a range of 18 orders of magnitude in measurement time per diffraction pattern and four orders of magnitude in crystal volume. The first room-temperature neutron structures of DHP-B are also presented, allowing the explicit identification of the hydrogen positions. The neutron data proved to be complementary to the serial femtosecond crystallography data, with both methods providing structures free of the effects of X-ray radiation damage when compared with standard cryo-crystallography. Comparison of these room-temperature methods demonstrated the large differences in sample requirements, data-collection time and the potential for radiation damage between them. With regard to the structure and function of DHP-B, despite the results being partly limited by differences in the underlying structures, new information was gained on the protonation states of active-site residues which may guide future studies of DHP-B.