Whole-Exome Sequencing Reveals Mutational Signature of Hypertrophic Cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is an extremely insidious and lethal disease caused by genetic variation. It has been studied for nearly 70 years since its discovery, but its cause of the disease remains a mystery. This study is aimed to explore the genetic pathogenesis of HCM in order to provide new insight for the diagnosis and treatment of HCM. Methods: Patients with HCM at 4 hospitals from January 1, 2020, to December 31, 2021, were collected. Peripheral blood of these patients was collected for whole exome sequencing. Moreover, data on the HCM transcriptome were analyzed in the GEO database. Results: Totally, 14 patients were enrolled, and 6 single-nucleotide variation (SNV) mutant genes represented by MUC12 were observed. Most of the gene mutations in HCM patients were synonymous and non-synonymous, and the types of base mutations were mainly C > T and G > A. Copy number variants (CNVs) predominantly occurred on chromosome 1 in HCM patients. Furthermore, we found that the only ATP2A2 gene was differentially expressed in 3 groups of transcriptome data in GEO database, and the presence of ATP2A2 mutation in 10 samples was observed in this study. Conclusion: In summary, 7 mutated genes represented by MUC12 and ATP2A2 were found in this study, which may provide novel insights into the pathogenic mechanism of HCM.

Findings from a decade of experience following implementation of a Rapid Response System into an Asian hospital.

Aim: Rapid response systems (RRS) are present in many acute hospitals in western nations but are not widely adopted in Asia. The influence of healthcare culture and the effect of implementing an RRS over time are infrequently reported. We describe the introduction a RRS into a Singaporean hospital and the barriers encountered. The efferent limb activation rates, cardiac arrest rates and unplanned intensive care unit (ICU) admissions are trended over eleven years. Methods: We conducted a retrospective observational study using prospectively collected data derived from administrative and Medical Emergency Team (MET) databases. Results: The RRS used a MET with a single parameter track and trigger and physician led efferent limb. Barriers encountered included clinical leadership buy-in, assembling and equipping the efferent team, maintaining a non-punitive mindset, improving accessibility to MET and communicating the impact of the MET. Over an 11-year period with 488,252 hospital admissions, MET activation rates increased from 1.6/1000 admissions (2009) to 14.1/1000 admissions (2019). Code blue activations and unplanned ICU admission rates decreased from 2.9 to 1.7 and from 8.8 to 2.0/1000 admissions, respectively over the 11 years. There were associations between increasing MET activation rate and reduction in code blue activations (p = 0.013) and unplanned medical ICU admission rates (p = 0.001). Conclusion: Implementing, sustaining and continued improvement of an RRS in Singapore is possible despite challenges encountered. With increasing activation rates over a decade, there were reductions in cardiac arrest rates and unplanned medical ICU admissions.

Construction of a prognostic risk model based on apoptosis-related genes to assess tumor immune microenvironment and predict prognosis in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a serious malignant disease with high incidence, high mortality and poor prognosis. This study aimed to establish a novel signature based on apoptosis-related genes (ARGs) to predict the prognosis of HCC. METHODS: Expression data of HCC from TCGA database and the list of 160 ARGs from MSigDB were downloaded. The genes included in apoptosis-related signature were selected by univariate Cox regression analysis and lasso Cox regression analysis. Subsequently, a prognostic risk model for scoring patients was developed, and then separates patients into two groups. Kaplan-Meier and receiver operating characteristic analysis were performed to evaluate the prognostic value of the model in TCGA, GEO and ICGC databases. The characteristics of immune cell infiltration between two groups of HCC were investigated. Finally, a nomogram was plotted to visualize the prognosis prediction. RESULTS: Nine genes (CDC25B, DAP3, ETF1, GSR, LGALS3, MGMT, PPP2R5B, SQSTM1 and VDAC2) were included in the prognostic risk model. Survival was lower in the high-risk group. Surprisingly, the high-risk group was significantly more in immune cell infiltration and with higher immunoscore and stromalscore than in the low-risk group. In addition, the risk score was an independent prognostic factor for HCC. CONCLUSIONS: Prognostic signature comprising nine ARGs could be used as a potential prognostic factor for HCC. It also provides an important idea for further understanding the immunotherapy of HCC.

The molecular differences of young and mature landfill leachates: Molecular composition, chemical property, and structural characteristic.

Landfill leachate is a highly contaminated and complex organic wastewater. It can be categorized into young (YL) and mature leachate (ML) based on the landfill age, with significant differences in the composition of organic matter, resulting from the significant differences in humification degree. To compare the organic composition of YL and ML, ESI FT-ICR MS was applied to systematically investigate their molecular composition, chemical properties, and structural characteristics. The molecular weight of YL organics was lower than that of ML organics. In addition, O/C and H/C distributions of YL and ML organics were significantly different. YL mainly consisted of CHO compounds and aliphatic compounds. ML mainly consisted of CHON compounds and high oxygen highly unsaturated and phenolic compounds. The unsaturation degree of YL organics was expressed by carbon double bond equivalents ((DBE-C)/C = -0.0336) and was not significantly different from that of ML (-0.0241), but nominal oxidation state of carbon (NOSC = -0.8010) and aromaticity (AImod = 0.1254) of YL were significantly lower than of ML (NOSC = -0.0692; AImod = 0.2464). In addition, YL and ML organics were rich in functional groups, but the YL organics contained more straight-chain structures. The ML organics contained fewer straight-chain structures, a larger number of benzene-ring structures, and more oxygen-containing functional groups. The more complex structural properties of ML organics may be the result of the transformation of YL organics after a long series of reactions, including electrocyclization, decarboxylation, and hydrogen abstraction reactions, which eventually increased the humification degree of leachate organic matter.

Uncovering potential single nucleotide polymorphisms, copy number variations and related signaling pathways in primary Sjogren's syndrome.

Primary Sjogren's syndrome (pSS) is a complex systemic autoimmune disease, which is difficult to accurately diagnose due to symptom diversity in patients, especially at earlier stages. We tried to find potential single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and related signaling pathways. Genomic DNA was extracted from peripheral blood of 12 individuals (7 individuals from 3 pSS pedigrees and 5 sporadic cases) for whole-exome sequencing (WES) analysis. SNPs and CNVs were identified, followed by functional annotation of genes with SNPs and CNVs. Gene expression profile (involving 64 normal controls and 166 cases) was downloaded from the Gene Expression Omnibus database (GEO) dataset for differentially expression analysis. Sanger sequencing and in vitro validation was used to validate the identified SNPs and differentially expressed genes, respectively. A total of 5 SNPs were identified in both pedigrees and sporadic cases, such as FES, PPM1J, and TRAPPC9. A total of 3402 and 19 CNVs were identified in pedigrees and sporadic cases, respectively. Fifty-one differentially expressed genes were associated with immunity, such as BATF3, LAP3, BATF2, PARP9, and IL15RA. AMPK signaling pathway and cell adhesion molecules (CAMs) were the most significantly enriched signaling pathways of identified SNPs. Identified CNVs were associated with systemic lupus erythematosus, mineral absorption, and HTLV-I infection. IL2-STAT5 signaling, interferon-gamma response, and interferon-alpha response were significantly enriched immune related signaling pathways of identified differentially expressed genes. In conclusion, our study found some potential SNPs, CNVs, and related signaling pathways, which could be useful in understanding the pathological mechanism of pSS.

DOA Estimation of Coherent Signals on Coprime Arrays Exploiting Fourth-Order Cumulants.

This paper considers the problem of direction-of-arrival (DOA) estimation of coherent signals on passive coprime arrays, where we resort to the fourth-order cumulants of the received signal to explore more information. A fourth-order cumulant matrix (FCM) is introduced for the coprime array. The special structure of the FCM is combined with the array configuration to resolve the coherent signals. Since each sparse array of a coprime array is uniform, a series of overlapping identical subarrays can be extracted. Using this property, we propose a generalized spatial smoothing scheme applied to the FCM. From the smoothed FCM, the DOAs of both the coherent and independent signals can be successfully estimated on the pseudo-spectrum generated by the fourth-order MUSIC algorithm. To overcome the problem of occasional false peaks appearing on the pseudo-spectrum, we use a supplementary sparse array whose inter-sensor spacing is coprime to that of either existing sparse array. From the combined spectrum aided by the supplementary sensors, the false peaks are removed while the true peaks remain. The effectiveness of the proposed methods is demonstrated by simulation examples.

A constant speed changing rate and constant turn rate model for maneuvering target tracking.

This paper addresses the problem of modeling maneuvering target motion in tracking applications. A target trajectory can typically be divided into segments with different dynamic motion modes, such as a constant velocity motion, a constant acceleration motion or a constant turn rate motion. To integrate the different motion modes into a uniform model, a Constant Speed Changing Rate and Constant Turn Rate (CSCRCTR) model is proposed. A new state vector is defined, and the state transition function is derived. Based on the CSCRCTR model, we present a tracking algorithm using a particle filter. The performances of the CSCRCTR model, the uniform model (UM) and the interacting multiple model (IMM) for tracking a simulated maneuvering target are compared and show that the CSCRCTR model maintains a good consistency for different types of motions and achieves better accuracy than UM and IMM when maneuvers occur.

[Adsorption characteristics of acetone and butanone onto honeycomb ZSM-5 molecular sieve].

Adsorption capacity of acetone and acetone-butanone mixture onto honeycomb ZSM-5 molecular sieve was measured in this paper, and the influences of relative humidity, initial adsorbate concentration and airflow velocity on the adsorption process were investigated. Besides, adsorption performance parameters were calculated by Wheeler's equation. The results showed that relative humidity had no obvious influence on the acetone adsorption performance, which suggests that this material has good hydrophobic ability; in the low concentration range, the dynamic saturated adsorption capacity of acetone increased with the increase of initial concentration, but in the occasion of high concentration of acetone gas (more than 9 mg x L(-1)), the dynamic saturated adsorption capacity maintained at a certain level and did not vary with the increase of initial concentration; the increase of air flow velocity resulted in significant increase of acetone adsorption rate constant, at the same time the critical layer thickness of the adsorbent bed also increased significantly. In the cases of acetone-butanone mixture, the adsorption capacity of butanone onto ZSM-5 was clearly higher than that of acetone.

A comparison of error bounds for a nonlinear tracking system with detection probability Pd < 1.

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds.

Distribution and sources of organochlorine pesticides in Taihu Lake, China.

Thirty surface sediments, corresponding overlying water and porewater samples were collected for analysis of organochlorine pesticides (OCPs) from Taihu Lake, China in May 2010. Altogether six OCPs, i.e. hexachlorobenzene (HCB), ß-hexachlorohexane (ß-HCH), p,p'-DDE, p,p'-DDD, p,p'-DDT, and o,p'-DDT were detected, and the total OCPs varied from 7.84 to 32.23 ng g(-1) in sediments, from 136.97 to 2,185.14 ng L(-1) in porewater and from 24.27 to 154.07 ng L(-1) in overlying water, respectively. The highest levels of contamination in sediment was observed in southeast of the lake, while in water and porewater samples highest levels were found in Zhushan Bay, the seriously polluted area in the north part of Taihu Lake. The partition coefficient of measured OCPs between sediment-overlying water was five and six fold higher than that between sediment-porewater, indicating the different distribution patterns of OCPs among sediment, overlying water and porewater matrices. The ratios of DDT/(DDD + DDE) ranged from 0.57 to 2.28 in sediments, 0.93-13.02 in porewater and 0.84-15.98 in overlying water, respectively, suggesting the potential new source of DDTs into the lake. The ratios of o,p'-DDT/p,p'-DDT in the three matrices were centered around 0.2-0.3, indicating the o,p'-DDT in the lake was originated from historical usage of technical DDTs.

Adaptive sparse representation for source localization with gain/phase errors.

Sparse representation (SR) algorithms can be implemented for high-resolution direction of arrival (DOA) estimation. Additionally, SR can effectively separate the coherent signal sources because the spectrum estimation is based on the optimization technique, such as the L(1) norm minimization, but not on subspace orthogonality. However, in the actual source localization scenario, an unknown gain/phase error between the array sensors is inevitable. Due to this nonideal factor, the predefined overcomplete basis mismatches the actual array manifold so that the estimation performance is degraded in SR. In this paper, an adaptive SR algorithm is proposed to improve the robustness with respect to the gain/phase error, where the overcomplete basis is dynamically adjusted using multiple snapshots and the sparse solution is adaptively acquired to match with the actual scenario. The simulation results demonstrate the estimation robustness to the gain/phase error using the proposed method.

Phase-modulated waveform design for extended target detection in the presence of clutter.

The problem to be addressed in this paper is a phase-modulated waveform design for the detection of extended targets contaminated by signal-dependent noise (clutter) and additive noise in practical radar systems. An optimal waveform design method that leads to the energy spectral density (ESD) of signal under the maximum signal-to-clutter-and-noise ratio (SCNR) criterion is introduced first. In order to make full use of the transmission power, a novel phase-iterative algorithm is then proposed for designing the phase-modulated waveform with a constant envelope, whose ESD matches the optimal one. This method is proven to be able to achieve a small SCNR loss by minimizing the mean-square spectral distance between the optimal waveform and the designed waveform. The results of extensive simulations demonstrate that our approach provides less than 1 dB SCNR loss when the signal duration is greater than 1 µs, and outperforms the stationary phase method and other phase-modulated waveform design methods.

[Evaluation of treatment technology of volatile organic compounds for fixed industrial resources].

The reduction of the emission of volatile organic compounds (VOCs) from fixed industrial resources is considered more necessary than before. The traditional treatment techniques, newly developed ones and some combinations of these treatment techniques are reviewed in this paper. The applying conditions, developing trend and existing problems of these techniques are also evaluated.

[Regulations and policies for control of volatile organic compounds and the emission standards in Taiwan].

Due to the well-developed managing system including policies, laws, regulations and emission standards, now the emission of volatile organic compounds (VOCs) is strictly controlled in Taiwai. The policy frameworks of VOCs control including both command control and economic incentives makes an excellent effect for VOCs treatment.

[Preparation of honeycombed monolithic zeolite and hydrophobic modification with SiCl4].

A kind of hydrophobic zeolitic monolith were prepared by mixing HY/ZSM-5, additives and water, followed by processes of extrusion and drying, and then hydrophobic modification with SiCl4. The structures and properties of the adsorbent were examined by nitrogen adsorption and desorption measurement, XRD, and benzene adsorption experiment. The results show that those adsorbents possess hierarchical pore structures and excellent hydrophobicity.

Extended target recognition in cognitive radar networks.

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

Performance bound for extended target tracking using high resolution sensors.

This article concerns the problem of the estimation bound for tracking an extended target observed by a high resolution sensor. Two types of commonly used models for extended targets and the corresponding posterior Cramer-Rao lower bound (PCRLB) are discussed. The first type is the equation-extension model which extends the state space to include parameters such as target size and shape. Thus, the extended state vector can be estimated through the measurements obtained by a high resolution sensor. The measurement vector is also an expansion of the conventional one, and the additional measurements such as target extent can provide extra information for the estimation. The second model is based on multiple target measurements, each of which is an independent random draw from a spatial probability distribution. As the number of measurements per frame is unknown and random, the general form of the measurement contribution to the Fisher information matrix (FIM) conditional on the number of measurements is presented, and an extended information reduction factor (EIRF) approach is proposed to calculate the overall FIM and, therefore, the PCRLB. The bound of the second extended target model is also less than that of the point model, on condition that the average number of measurements is greater than one. Illustrative simulation examples of the two models are discussed and demonstrated.

Water quality assessment and source identification of Daliao River Basin using multivariate statistical methods.

Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA), were used to analyze the water quality dataset including 13 parameters at 18 sites of the Daliao River Basin from 2003-2005 (8424 observations) to obtain temporal and spatial variations and to identify potential pollution sources. Using Hierarchical CA it is classified 12 months into three periods (first, second and third period) and the 18 sampling sites into three groups (groups A, B and C). Six significant parameters (temperature, pH, DO, BOD(5), volatile phenol and E. coli) were identified by DA for distinguishing temporal or spatial groups, with close to 84.5% correct assignment for temporal variation analysis, while five parameters (DO, NH(4)(+)-N, Hg, volatile phenol and E. coli) were discovered to correctly assign about 73.61% for the spatial variation analysis. PCA is useful in identifying five latent pollution sources for group B and C (oxygen consuming organic pollution, toxic organic pollution, heavy metal pollution, fecal pollution and oil pollution). During the first period, sites received more oxygen consuming organic pollution, toxic organic pollution and heavy metal pollution than those in the other two periods. For group B, sites were mainly affected by oxygen consuming organic pollution and toxic organic pollution during the first period. The level of pollution in the second period was between the other two periods. For group C, sites were mainly affected by oil pollution during the first period and oxygen consuming organic pollution during the third period. Furthermore, source identification of each period for group B and group C provided useful information about seasonal pollution. Sites were mainly affected by fecal pollution in the third period for group B, indicating the character of non-point source pollution. In addition, all the sites were also affected by physical-chemistry pollution. In the second and third period for group B and second period for group C sites were also affected by natural pollution.

Motion Compensation of Moving Targets for High Range Resolution Stepped-Frequency Radar.

High range resolution (HRR) profiling using stepped-frequency pulse trains suffers from range shift and the attenuation/dispersion of range profiles while the target of interest is moving. To overcome these two drawbacks, a new algorithm based on the maximum likelihood (ML) estimation is proposed in this paper. Without altering the conventional stepped-frequency waveform, this algorithm can estimate the target velocity and thereby compensate the phase errors caused by the target's motion. It is shown that the velocity can be accurately estimated and the range profile can be correctly reconstructed.

Methodology to determine regional water demand for instream flow and its application in the Yellow River Basin.

In order to realistically reflect the difference between regional water demand for instream flow and river ecological water demand as well as to resolve the problem that water demand may be counted repeatedly, a concept of regional water demand for minimum instream flow have been developed. The concept was used in the process of determining river functions and calculating ecological water demand for a river. The Yellow River watershed was used to validate the calculation methodology for regional water demand. Calculation results indicate that there are significant differences in water demands among the different regions. The regional water demand at the downstream of the Yellow River is the largest about 14.893 X 10(9) m(3)/a. The regional water demand of upstream, Lanzhou-Hekou section is the smallest about -5.012 x 10(9) m(3)/a. The total ecological water demand of the Yellow River Basin is 23.06 X 10(9) m(3)/a, about the 39% of surface water resources of the Yellow River Basin. That means the maximum available surface water resources should not exceed 61% in the Yellow River Basin. The regional river ecological water demands at the Lower Section of the Yellow River and Longyangxia-Lanzhou Section exceed the surface water resources produced in its region and need to be supplemented from other regions through the water rational planning of watershed water resources. These results provides technical basis for rational plan of water resources of the Yellow River Basin.