Data_Sheet_1_Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.PDF

<p>The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.</p

A mechanism-based fate model of pesticide solutions on the plant surface under aerial application

Pesticide residues on plant surfaces are a primary source of pesticide bioaccumulation in crops. In this context, we propose a mechanism-based model for understanding the pesticide fate on the plant surface following aerial application, taking into account fate modelling of the pesticide spray solution on the plant surface. Using chlorothalonil as an example, the simulation results revealed that the spray solution dissipated rapidly after aerial application, resulting in the formation of a saturated pesticide solution, which facilitated the diffusion process of the pesticide residue from the plant surface into the peel tissue. The proposed model generated higher simulated residue concentrations in the peel or pulp than the current model, owing to the proposed model’s assumption of rapid dissipation of the spray solution. This indicated that the proposed model specified the influence of the spray solution on the plant’s exposure to residues via the surface deposition pathway, whereas the current modelling approach presented a generic estimate of the residue dissipation on the plant surface that linked to the residue’s fate in the soil.</p

Global survey on sequence characteristics of plant microRNA genes: <i>Cis</i>-regulatory SNPs in promoters and microRNA precursors

<div><p>MicroRNAs (miRNAs) are tiny molecules with multiple essential roles in plant growth and development. So far, numerous miRNA families, both highly conserved and species-specific, have been identified and functionally characterized. However, we are still far from a thorough understanding of these molecules, including their sequence characteristics. In this bioinformatics study, <i>cis</i>-acting regulatory elements located within plant miRNA promoters were predicted, and a comprehensive list of single nucleotide polymorphisms (SNPs) residing within these <i>cis</i>-elements, designated as <i>cis</i>-regulatory SNPs, was identified. These SNPs potentially contribute to the distinct expression patterns of miRNA genes in various Arabidopsis (<i>Arabidopsis thaliana</i>) or rice (<i>Oryza sativa</i>) subspecies. Additionally, sequence conservation analysis was carried out for all the currently miRBase-registered pre-miRNAs (precursor miRNAs) belonging to numerous plant species. Together, these analyses provide a basis to gain deeper insights into the biological role of miRNA sequence characteristics.</p></div

A SAR-based mechanistic study on the combined toxicities of sulfonamides and quorum sensing inhibitors on <i>Escherichia coli</i>

<p>Quorum sensing inhibitors (QSIs) are promising alternatives to antibiotics, but they are discharged into the environment after their use cycle. This poses joint effects on the organisms in the environment. Therefore, it is of great importance to study the combined toxicities of QSIs and antibiotics. In this study, we investigated the single and combined toxicities of four potential QSIs and 11 sulfonamides (SAs) on <i>Escherichia coli.</i> The results revealed that the single toxicities of SAs were greater than those of QSIs, and the toxicities were found positively related to the binding energies (<i>E</i>_bind) with their target proteins, for both antibiotics and QSIs. The combined toxicities of the binary mixtures were observed to be either antagonism or addition. The antagonism could be explained by the phenomenon that QSIs changed SAs molecules into ionic forms, preventing the SA molecules entering the bacteria. Furthermore, it was found that the ratios of the effective concentration (the actual concentration involved in the interaction with the proteins) in the antagonistic cases were higher than those in the additive cases. This study would benefit both rational use of the drug combination and ecological risk assessment of antibiotics and QSIs in the real environment.</p

Risk of using logistic regression to illustrate exposure-response relationship of infectious diseases

Background: In most biological experiments, especially infectious disease, the exposure-response relationship is interrelated by a multitude of factors rather than many independent factors. Little is known about the suitability of ordinary, categorical exposures, and logarithmic transformation which have been presented in logistic regression models to assess the likelihood of an infectious disease as a function of a risk or exposure. This study aims to examine and compare the current approaches. Methods: A simulated human immunodeficiency virus (HIV) population, dynamic infection data for 100,000 individuals with 1% initial prevalence and 2% infectivity, was created. Using the Monte Carlo method (computational algorithm) to repeat random sampling to obtain numerical results, linearity between log odds and exposure, and suitability in practice were examined in the three model approaches. Results: Despite diverse population prevalence, the linearity was not satisfied between log odds and raw exposures. Logarithmic transformation of exposures improved the linearity to a certain extent, and categorical exposures satisfied the linear assumption (which was important for modelling). When the population prevalence was low (assumed < 10%), performances of the three models were significantly different. Comparing to ordinary logistic regression, the logarithmic transformation approach demonstrated better accuracy of estimation except that at the two inflection points: likelihood of infection increased from slowly to sharply, then slowly again. The approach using categorical exposures had better estimations around the real values, but the measurement was coarse due to categorization. Conclusions: It is not suitable to directly use ordinary logistic regression to explore the exposure-response relationship of HIV as an infectious disease. This study provides some recommendations for practical implementations including: 1) utilize categorical exposure if a large sample size and low population prevalence are provided; 2) utilize a logarithmic transformed exposure if the sample size is insufficient or the population prevalence is too high (such as 30%). Keywords: Logistic regression, Measurement error, Infectious disease, Exposure-response relationship, Computer simulatio

Additional file 1 of Mesenchymal stem cells transplantation for perianal fistulas: a systematic review and meta-analysis of clinical trials

Additional file 1. Materials to interpret for this study: search strategy of databases, the flow diagram of the six clinical trials and the HR of every clinical trial in different phases

sj-docx-1-jdr-10.1177_00220345231195765 – Supplemental material for Force-Loaded Cementocytes Regulate Osteoclastogenesis via S1P/S1PR1/Rac1 Axis

Supplemental material, sj-docx-1-jdr-10.1177_00220345231195765 for Force-Loaded Cementocytes Regulate Osteoclastogenesis via S1P/S1PR1/Rac1 Axis by H. Wang, T. Li, Y. Jiang, S. Chen, S. Zou, L.F. Bonewald and P. Duan in Journal of Dental Research</p

DS_10.1177_0022034518781509 – Supplemental material for Overexpressed Sirt1 in MSCs Promotes Dentin Formation in Bmi1-Deficient Mice

<p>Supplemental material, DS_10.1177_0022034518781509 for Overexpressed Sirt1 in MSCs Promotes Dentin Formation in Bmi1-Deficient Mice by H. Wang, C. Lv, Y. Gu, Q. Li, L. Xie, H. Zhang, D. Miao and W. Sun in Journal of Dental Research</p

Anion Photoelectron Spectroscopy and CASSCF/CASPT2/RASSI Study of La_<i>n</i>^– (<i>n</i> = 1, 3–7)

We present a combined experimental and theoretical study of small lanthanum clusters. The experimental photoelectron spectra of La_<i>n</i>^– (<i>n</i> = 1, 3–7) were obtained using negative ion photoelectron spectroscopy. Electron affinities for these clusters were found to be in a range of 0.49 eV (La) to 1.5 eV (La₇). Our computational <i>tour de force</i> in exploring the electronic structure and its consequences for the lanthanum atom and its anion as well as for lanthanum trimer and its anion shows the multiconfigurational method and large basis set with spin–orbit corrections: CASSCF/CASPT2/RASSI/ANO-RCC-L level of theory is needed to reproduce experimental accuracy. The most stable structure for La₃^– was established to be an equilateral triangle (¹A₁′). Chemical bonding analysis of the La₃^– global minimum reveals that this is the first experimentally observed species with d-AO double σ and π aromaticity

Metal Iodate-Based Energetic Composites and Their Combustion and Biocidal Performance

The biological agents that can be weaponized, such as <i>Bacillus anthracis,</i> pose a considerable potential public threat. Bacterial spores, in particular, are highly stress resistant and cannot be completely neutralized by common bactericides. This paper reports on synthesis of metal iodate-based aluminized electrospray-assembled nanocomposites which neutralize spores through a combined thermal and chemical mechanism. Here metal iodates (Bi­(IO₃)₃, Cu­(IO₃)₂, and Fe­(IO₃)₃) act as a strong oxidizer to nanoaluminum to yield a very exothermic and violent reaction, and simultaneously generate iodine as a long-lived bactericide. These microparticle-assembled nanocomposites when characterized in terms of reaction times and temporal pressure release show significantly improved reactivity. Furthermore, sporicidal performance superior to conventional metal-oxide-based thermites clearly shows the advantages of combining both a thermal and biocidal mechanism in spore neutralization