Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological Processes of Bacterial and Fungal Communities Associated with Typha orientalis Roots in Wetlands Were Distinct during Plant Development

Our findings provide empirical evidence for the assembly, sources, interactions, and potential functions of wetland plant root microbial communities, and have significant implications for the future applications of plant microbiomes in the wetland ecosystem. ABSTRACT Root-associated microbiomes are essential for the ecological function of the root system. However, their assembly mechanisms in wetland are poorly understood. In this study, we explored and compared the ecological processes of bacterial and fungal communities in water, bulk soil, rhizosphere soil, and root endosphere niches for 3 developmental stages of Typha orientalis at different wetland sites, and assessed the potential functions of root endosphere microbiomes with function prediction. Our findings suggest that the microbial diversity, composition, and interaction networks along the water-soil-plant continuum are shaped predominantly by compartment niche and developmental stage, rather than by wetland site. Source tracking analysis indicated that T. orientalis’ root endosphere is derived primarily from the rhizosphere soil (bacteria 39.9%, fungi 27.3%) and water (bacteria 18.9%, fungi 19.1%) niches. In addition, we found that the assembly of bacterial communities is driven primarily by deterministic processes and fungal communities by stochastic processes. The interaction network among microbes varies at different developmental stages of T. orientalis, and is accompanied by changes in microbial keystone taxa. The functional prediction data supports the distribution pattern of the bacterial and fungal microbiomes, which have different ecological roles at different plant developmental stages, where more beneficial bacterial taxa are observed in the root endosphere in the early stages, but more saprophytic fungi in the late stages. Our findings provide empirical evidence for the assembly, sources, interactions, and potential functions of wetland plant root microbial communities and have significant implications for the future applications of plant microbiomes in the wetland ecosystem. IMPORTANCE Our findings provide empirical evidence for the assembly, sources, interactions, and potential functions of wetland plant root microbial communities, and have significant implications for the future applications of plant microbiomes in the wetland ecosystem.
A Variational Continuous Assimilation Technique

Abstract A variational assimilation technique is presented which continuously adjusts a model solution by introducing a correction term to the model equations. The technique is essentially a modification of the adjoint technique. The Variational Continuous Assimilation (VCA) technique optimizes the correction to the model equations rather than the initial conditions as is done in the adjoint technique. The VCA-technique characteristics were examined by inserting independent analyses into a simple quasi- geostrophic model using both the VCA technique and the adjoint technique. Because the model equations do not have to be satisfied exactly in the VCA technique, some of the effects of systematic model errors can be removed from the assimilation. Thus, the VCA technique was able to consistently fit the data better than the adjoint technique. Predictions from the results from the assimilation techniques showed that the forecast from the adjoint technique's solution was consistently inferior to those from the .
Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

ABSTRACT Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a library containing improved variants from the information of the “weakly enriched” library where functional variants were weakly enriched. Deep sequencing for the previous biopanning result, where no functional antibody mimetics were experimentally identified, revealed that weak enrichment was partly due to undesirable biases during phage infection and amplification steps. The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. Phage libraries were designed on the basis of the sequence patterns identified, and four improved variants with target-specific affinity (EC50 = 80–277 nM) were identified by biopanning. The selection and use of deep sequencing data without undesirable bias enabled us to extract the information on prospective variants. In summary, the use of appropriate deep sequencing data and machine learning with the sequence data has the possibility of finding sequence space where functional variants are enriched.
Evaluating the Clinical Utility of a Long-Read Sequencing-Based Approach in Prenatal Diagnosis of Thalassemia.

BACKGROUND The aim is to evaluate the clinical utility of a long-read sequencing-based approach termed comprehensive analysis of thalassemia alleles (CATSA) in prenatal diagnosis of thalassemia. METHODS A total of 278 fetuses from at-risk pregnancies identified in thalassemia carrier screening by PCR-based methods were recruited from 9 hospitals, and PCR-based methods were employed for prenatal diagnosis. CATSA was performed retrospectively and blindly for all 278 fetuses. RESULTS Among the 278 fetuses, 263 (94.6%) had concordant results and 15 (5.4%) had discordant results between the 2 methods. Of the 15 fetuses, 4 had discordant thalassemia variants within the PCR detection range and 11 had additional variants identified by CATSA. Independent PCR and Sanger sequencing confirmed the CATSA results. In total, CATSA and PCR-based methods correctly detected 206 and 191 fetuses with variants, respectively. Thus, CATSA yielded a 7.9% (15 of 191) increment as compared with PCR-based methods. CATSA also corrected the predicted phenotype in 8 fetuses. Specifically, a PCR-based method showed one fetus had homozygous HBB c.52A > T variants, while CATSA determined the variant was heterozygous, which corrected the predicted phenotype from β-thalassemia major to trait, potentially impacting the pregnancy outcome. CATSA additionally identified α-globin triplicates in 2 fetuses with the heterozygous HBB c.316-197C > T variant, which corrected the predicted phenotype from β-thalassemia trait to intermedia and changed the disease prognosis. CONCLUSIONS CATSA represents a more comprehensive and accurate approach that potentially enables more informed genetic counseling and improved clinical outcomes compared to PCR-based methods.
Effect of external sleep disturbance on sleep architecture in perimenopausal and postmenopausal women

Abstract Objective This study aimed to use external sleep disturbance as a model to evaluate sleep architecture in climacteric women before and after menopausal hormone therapy (MHT). Methods Seventeen perimenopausal and 18 postmenopausal women underwent a polysomnography protocol: an adaptation night, a reference night and a sleep disturbance night with one hand loosely tied to the bed for blood sampling. The sleep architecture of the reference and disturbance nights were compared. The 24-h urinary free cortisol concentration (UFC) was measured. The procedure was repeated after 6 months on MHT or placebo. Results Fifteen perimenopausal and 17 postmenopausal women completed the study. The perimenopausal and postmenopausal groups were combined. During external sleep disturbance, sleep was shorter and more fragmented; with less stage 2, slow-wave and rapid eye movement (REM) sleep and more wake time and awakenings, both at baseline and after the treatment period. Compared to the placebo group, sleep disturbance was minor for women on MHT: sleep was not shortened and the amount of slow-wave sleep did not decrease. Increased 24-h UFC was observed only during MHT. Conclusions Sleep in climacteric women is easily disturbed, leading to shorter and more fragmented sleep with less deep sleep and REM sleep. Six months of MHT attenuates the observed sleep disturbance.
Euclasta condylotricha flowers essential oils: A new source of juvenile hormones and its larvicidal activity against Anopheles gambiae s.s. (Diptera: Culicidae)

The essential oil (EO) of plants of the Poaceae family has diverse chemical constituents with several biological properties. But, data on the chemical constituents and toxicity are still unavailable for some species belonging to this family, such as Euclasta condylotricha Steud (Eu. condylotricha). In this study, the chemical composition of the EOs of Eu. condylotricha flowers was evaluated by gas chromatography coupled with mass spectrometry (GC–MS). The EOs larvicidal property was assessed against third instar larvae of three Anopheles gambiae laboratory strains (Kisumu, Acerkis and Kiskdr) according to the WHO standard protocol. The percentage yields of the EOs obtained from hydro distillation of Eu. condylotricha flowers varied 0.070 to 0.097%. Gas Chromatography-Mass Spectrometry (GC-MS) applied to the EOs revealed fifty-five (55) chemical constituents, representing 94.95% to 97.78% of the total essential oils. Although different chemical profiles of the dominant terpenes were observed for each sample, EOs were generally dominated by sesquiterpenoids with juvenile hormones as the major compounds. The primary compounds were juvenile hormone C16 (JH III) (35.97–48.72%), Methyl farnesoate 10,11-diol (18.56–28.73%), tau-Cadinol (18.54%), and β-Eudesmene (12.75–13.46%). Eu. condylotricha EOs showed a strong larvicidal activity with LC50 values ranging from 35.21 to 52.34 ppm after 24 hours of exposition. This study showed that Eu. Condylotricha flowers essential oils are potent sources of juvenile hormones that could be a promising tool for developing an eco-friendly malaria vector control strategy.
LGEANet: LSTM-Global temporal convolution-external attention network for respiratory motion prediction.

PURPOSE To develop a deep learning network that treats the three-dimensional respiratory motion signals as a whole and considers the inter-dimensional correlation between signals of different directions for accurate respiratory tumor motion prediction. METHODS We propose a deep learning framework, named as LSTM-Global Temporal Convolution-External Attention Network (LGEANet). In LGEANet, we first feed each of the univariate time series into the Long Short-Term Memory (LSTM) module respectively and utilize the strength of the global temporal convolutional layer to discover the temporal pattern of the univariate signals from hidden states of the LSTM. Then, External attention is adopted to capture the dynamic dependence of the multiple time series. Also, a traditional autoregressive linear model in parallel to the non-linear neural network part was integrated to mitigate the scale insensitivity of the networks. A total of 304 motion traces for 31 patients are acquired from a public dataset in the experiments and four representative cases were selected for model evaluation. The respiratory signals were sampled at intervals of about 37.5 ms (26 frames per second) for an average duration of 71 min. RESULTS The proposed LGEANet achieved better performance with higher empirical correlation coefficient value (CORRs) and lower mean absolute error value (MAEs) and relative squared error value (RSEs) than other investigated models. For the four representative datasets, when the response time is less than 231 ms, the model can achieve CORRs more than 0.96. And the averaged position error reduction by using the proposed model was about 67% in the superior-inferior (SI) direction, 41% in the anterior-posterior (AP) direction and 38% in the right-left (RL) direction compared to that without prediction. The proposed network achieved the greatest error reduction in the SI direction, which is the main direction of tumor motion. CONCLUSIONS The LGEANet achieves promising performance in minimizing the prediction error due to system latencies during real-time tumor motion tracking. This article is protected by copyright. All rights reserved.
Ecological Dynamics of Broad- and Narrow-Host-Range Viruses Infecting the Bloom-Forming Toxic Cyanobacterium Microcystis aeruginosa

The bloom-forming toxic cyanobacterium Microcystis aeruginosa interacts with diverse broad- and narrow-host-range viruses. However, the dynamics of the Microcystis population (at the intraspecies level) and viruses with different host ranges remain unknown. ABSTRACT Microcystis aeruginosa is predicted to interact and coexist with diverse broad- and narrow-host-range viruses within a bloom; however, little is known about their affects on Microcystis population dynamics. Here, we developed a real-time PCR assay for the quantification of these viruses that have different host ranges. During the sampling period, total Microcystis abundance showed two peaks in May and August with a temporary decrease in June. The Microcystis population is largely divided into three phylotypes based on internal transcribed sequences (ITS; ITS types I to III). ITS I was the dominant phylotype (66% to 88%) except in June. Although the ITS II and III phylotypes were mostly less abundant, these phylotypes temporarily increased to approximately equivalent abundances of the ITS I population in June. During the same sampling period, the abundances of the broad-host-range virus MVGF_NODE331 increased from April to May and from July to October with a temporary decrease in June, in which its dynamics were in proportion to the increase of total Microcystis abundances regardless of changes in host ITS population composition. In contrast, the narrow-host-range viruses MVG_NODE620 and Ma-LMM01 were considerably less abundant than the broad-host-range virus and generally did not fluctuate in the environment. Considering that M. aeruginosa could increase the abundance and sustain the bloom under the prevalence of the broad-host-range virus, host abundant and diverse antiviral mechanisms might contribute to coexistence with its viruses. IMPORTANCE The bloom-forming toxic cyanobacterium Microcystis aeruginosa interacts with diverse broad- and narrow-host-range viruses. However, the dynamics of the Microcystis population (at the intraspecies level) and viruses with different host ranges remain unknown. Our real-time PCR assays unveiled that the broad-host-range virus gradually increased in abundance over the sampling period, in proportion to the increase in total Microcystis abundance regardless of changes in genotypic composition. The narrow-host-range viruses were considerably less abundant than the broad-host-range virus and did not generally fluctuate in the environment. The expansion and maintenance of the Microcystis bloom even under the increased infection by the broad-host-range virus suggested that highly abundant and diverse antiviral mechanisms allowed them to coexist with viruses under selective pressure. This paper expands our knowledge about the ecological dynamics of Microcystis viruses and provides potential insights into their coexistence with their host.
Multiscale geometric analysis for 3D catalogs

We have developed tools for analysis of 3D volumetric data which allow sensitive characterizations of filamentary structures in 3D point clouds. These tools rapidly compute multiscale X-ray transforms of the data volume. Subcubes of varying locations and scales are extracted from the data volume and each is analyzed by integrating along a strategically chosen set of line segments covering all different orientations. The underlying motivation is that point clouds with different degrees of filamentarity will lead to multiscale X-ray coefficients having different distributions when viewed at the right scale. The multiscale approach guarantees that information from all scales is available; by extracting the information from the transform in a statistically appropriate fashion, we can sensitively resolve differences in details of the filamentarity. We will describe the algorithm and the results of comparing different simulated galaxy distributions.
The opportunistic pathogen Pseudomonas aeruginosa exploits bacterial biotin synthesis pathway to benefit its infectivity

Pseudomonas aeruginosa is an opportunistic pathogen that predominantly causes nosocomial and community-acquired lung infections. As a member of ESKAPE pathogens, carbapenem-resistant P. aeruginosa (CRPA) compromises the limited therapeutic options, raising an urgent demand for the development of lead compounds against previously-unrecognized drug targets. Biotin is an important cofactor, of which the de novo synthesis is an attractive antimicrobial target in certain recalcitrant infections. Here we report genetic and biochemical definition of P. aeruginosa BioH (PA0502) that functions as a gatekeeper enzyme allowing the product pimeloyl-ACP to exit from fatty acid synthesis cycle and to enter the late stage of biotin synthesis pathway. In relative to Escherichia coli, P. aeruginosa physiologically requires 3-fold higher level of cytosolic biotin, which can be attributed to the occurrence of multiple biotinylated enzymes. The BioH protein enables the in vitro reconstitution of biotin synthesis. The repertoire of biotin abundance is assigned to different mouse tissues and/or organ contents, and the plasma biotin level of mouse is around 6-fold higher than that of human. Removal of bioH renders P. aeruginosa biotin auxotrophic and impairs its intra-phagosome persistence. Based on a model of CD-1 mice mimicking the human environment, lung challenge combined with systemic infection suggested that BioH is necessary for the full virulence of P. aeruginosa. As expected, the biotin synthesis inhibitor MAC13772 is capable of dampening the viability of CRPA. Notably, MAC13772 interferes the production of pyocyanin, an important virulence factor of P. aeruginosa. Our data expands our understanding of P. aeruginosa biotin synthesis relevant to bacterial infectivity. In particular, this study represents the first example of an extracellular pathogen P. aeruginosa that exploits biotin cofactor as a fitness determinant, raising the possibility of biotin synthesis as an anti-CRPA target.
Analysis and design of a signed regressor LMS algorithm for stationary and nonstationary adaptive filtering with correlated Gaussian data

A least mean square (LMS) algorithm with clipped data is studied for use when updating the weights of an adaptive filter with correlated Gaussian input. Both stationary and nonstationary environments are considered. Three main contributions are presented. The first, corresponding to the stationary case, is a proof of the convergence of the algorithm in the case of a M-dependent sequence of correlated observation vectors. It is proven that the steady state mean square misalignment of the adaptive filter weights has an upper bound proportional to the algorithm step size mu . The second contribution, also belonging to the stationary case, is the derivation of the expressions of convergence time N/sub c/ and steady state mean square excess estimation error epsilon . It is shown that N/sub c/ is proportional to 1/( mu lambda ), with lambda being the minimum eigenvalue of the input covariance matrix. It is also shown that the product N/sub c/ epsilon is independent of mu . For a given epsilon , the convergence time increases with the eigenvalue spread of the input covariance matrix and the filter length, as well as its input noise power. The range of mu that achieves tolerable values of N/sub c/ and epsilon is determined. The third contribution is concerned with the nonstationary case. It is shown that the mean square excess estimation error is the sum of the two terms with opposite dependencies on mu . An optimum value of mu is derived. >
Optimal control of a linear time-invariant space–time fractional diffusion process

This paper presents a formulation and numerical solutions of an optimal control problem of a linear time-invariant space–time fractional diffusion equation. The main aim of this formulation is minimization of a performance index, which is a functional of both state and control functions of the diffusion system. The dynamics of the system are defined by the space–time fractional diffusion equation in the sense of Caputo and fractional Laplacian operators. The separation of variables technique and a spectral representation of a fractional Laplacian operator are applied to determine the eigenfunctions that represent the space parameters. Therefore, the state and control functions are defined by linear infinite combinations of eigenfunctions. Optimality conditions described by Euler–Lagrange equations are found by using a Lagrange multiplier technique. The Grünwald–Letnikov definition is used to approximate to the time fractional derivative. The applicapability and effectiveness of the numerical scheme are shown by comparison of analytical and numerical solutions for a numerical example. Finally, the variations of problem parameters are analyzed, with some figures obtained using MATLAB.
Low glycemic index common bean snack increased satiety without modifying energy intake in adults with normal weight: randomized crossover trials

Abstract This study aimed to evaluate the short-term effect of a common bean baked snack (CBBS) and cooked bean consumption on energy intake, satiety, glycemic response, and palatability in subjects with normal weight (Study 1) and overweight (Study 2) and to determine the glycemic index of CBBS (Study 3). For studies 1 and 2, satiety and glycemic response were measured over 45 min after consuming CBBS, cooked beans or white bread preload, and energy intake at an ad libitum test meal was calculated. Energy intake remained similar after consuming the three preloads in both studies. Compared to white bread, CBBS consumption increased fullness by 52% in subjects with normal weight but not in those with overweight. The CBBS calculated glycemic index was considered low (42). Consumption of low glycemic index CBBS increased satiety in adults with a normal weight. Long-term trials assessing the effects on body weight management are necessary.
Autologous Blood-Clot Embolisation of Iatrogenic Femoral Artery Pseudoaneurysm Caused by Arterial Sheath Placement; A Case Report

Iatrogenic Femoral Artery Pseudoaneurysm (FAP) is a common complication that occurs in diagnostic and therapeutic catheterization procedures and can cause morbidity and even mortality in patients. Aneurysm larger than 2 cm, symptomatic or complicated should be treated. Here we report a 59-year-old man with post-catheterization FAP following femoral artery angiography, treated successfully by direct transcatheter autologous blood clot embolisation. To the best of our knowledge, our case report is the first to demonstrate that FAP can be successfully treated endovascularly by autologous blood clot embolisation.
Surface plasmon resonance of nanoshell particles with PMMA-graphene core

Purpose – The purpose of this paper is to contribute an analytical and numerical study of a new type of nanoshell particles operating in the visible regime. Design/methodology/approach – The structure consists of a core/shell particle, arranged in a planar array configuration, with a polymethyl methacrylate (PMMA)-graphene core and gold thin shell. Findings – By exploiting the proposed analytical model the design of a metamaterial-based sensor, operating in the optical frequency range, for the detection of tissue diseases is shown. Originality/value – Full-wave simulations confirm the capability of the proposed sensor to identify different compounds by refractive index measurement.