Identification of bHLH transcription factors and screening of anthocyanin-related genes in Lagerstroemia indica.

The basic helix-loop-helix (bHLH) family is one of the three major transcription factor families that play important transcriptional regulatory roles in plant growth and development. One of the most crucial elements in defining Lagerstroemia indica's decorative qualities is flower color. However, the function of the bHLH transcription factor family in L. indica anthocyanin glycoside synthesis has not been clarified. Using the transcriptome data of flower color, 79 LibHLH genes were found in this study. Phylogenetic analysis showed that the LibHLH genes can be divided into 16 subfamilies, and most of the genes in the same subfamily have similar conserved motifs. The total anthocyanin glycoside content of L. indica 'Zihua Guifei' petals was determined during three developmental stages of the petals' growth. The results showed that the total anthocyanin glycoside content grew gradually with growth and development, and that it accumulated most during the full bloom stage. By using gene expression analysis, protein interaction network analysis, and bioinformatics, it was possible to determine which member of the III f family, LibHLH29, is important for the synthesis of anthocyanin glycosides in L. indica. Its expression was confirmed by qRT-PCR, and the results were essentially compatible with the transcriptome data. It was more prominent in the light-colored bloom stage the color-transition stage of L. indica 'Zihua Guifei'. It can be further investigated as a major candidate gene for regulating anthocyanin glycoside synthesis in L. indica, thus laying the foundation for an in-depth study of the interactions among transcription factors.

Impact of permanganate with polyaluminium chloride on algae-laden karst water: Behaviors and disinfection by-products control.

The removal of algal organic matter (AOM) through water treatment processes is a major approach of reducing the formation of disinfection by-products (DBP). Here, the formation of DBP from AOM in karst water under different combination of potassium permanganate (KMnO4) and polyaluminium chloride (PACl) was investigated. The effect of divalent ions (Ca2+ and Mg2+) on DBP formation was traced by AOM chemistry variations. For DBP formation after KMnO4 preoxidation, total carbonaceous DBPs (C-DBPs) decreased by 12.9% but nitrogen-containing DBPs (N-DBPs) increased by 18.8%. Conversely, the C-DBPs further increased by 3.3% but N-DBPs reduced by 10.7% after the addition of PACl besides KMnO4 preoxidation. The variations of aromatic protein-like, soluble microbial products-like compounds and ultraviolet absorbance at 254 nm (UV254) were highly correlated with the formation of DBPs, which suggest aromatic substances strongly affect DBP behaviors at different treatment conditions. In the presence of divalent ions (Ca2+ = 135.86 mg/L, Mg2+ = 18.51 mg/L), the combination of KMnO4 and PACl was more effective in controlling DBP formation compared to the situation without Ca2+ and Mg2+. Specifically, trichloromethane formation was largely inhibited compared to the other tested DBPs, which may refer to complexation of electron-donating groups via divalent ions. While Ca2+ and Mg2+ may not affect the nature of α-carbon and amine groups, so the variation of haloacetonitriles (HANs) was not obvious. The study enhances the understanding of the DBP formation patterns, transformation of carbon and nitrogen by preoxidation-coagulation (KMnO4-PACl) treatment in algae-laden karst water.

Are Latent Factor Regression and Sparse Regression Adequate?

We propose the Factor Augmented (sparse linear) Regression Model (FARM) that not only admits both the latent factor regression and sparse linear regression as special cases but also bridges dimension reduction and sparse regression together. We provide theoretical guarantees for the estimation of our model under the existence of sub-Gaussian and heavy-tailed noises (with bounded (1 + ϑ) -th moment, for all ϑ > 0) respectively. In addition, the existing works on supervised learning often assume the latent factor regression or sparse linear regression is the true underlying model without justifying its adequacy. To fill in such an important gap on high-dimensional inference, we also leverage our model as the alternative model to test the sufficiency of the latent factor regression and the sparse linear regression models. To accomplish these goals, we propose the Factor-Adjusted deBiased Test (FabTest) and a two-stage ANOVA type test respectively. We also conduct large-scale numerical experiments including both synthetic and FRED macroeconomics data to corroborate the theoretical properties of our methods. Numerical results illustrate the robustness and effectiveness of our model against latent factor regression and sparse linear regression models.

Algae removal and algal organic matter chemistry modulated by KMnO4-PAC in simulated karst water.

In this study, we examined the modulation of algae removal and algal organic matter (AOM) chemistry by potassium permanganate and poly-aluminum chloride (KMnO4-PAC) in simulated karst water. Specifically, we verified the compositional changes of AOM sourcing from Chlorella sp. and Pseudanabaena sp. in response to the presence of divalent ions (Ca2+ and Mg2+). Aromatic protein and soluble microbial products were identified as the primary AOM components. Divalent ions accelerated dissolved organic carbon (DOC) and UV254 removal, particularly with Pseudanabaena sp. greater than Chlorella sp. (P < 0.05). Surface morphology analysis manifested that the removal of filamentous Pseudanabaena sp. was more feasible in comparison to globular Chlorella sp.. Our results highlight the significance of divalent ions in governing chemical behaviors and subsequent removal of both algae and AOM. This study upscales the understanding of the interactions among divalent ions, algae and AOM during preoxidation and coagulation process in algae-laden karst water.

Admission Point-of-Care Testing for the Clinical Care of Children with Cerebral Malaria.

Point-of-care testing (PoCT), an alternative to laboratory-based testing, may be useful in the clinical care of critically ill children in resource-limited settings. We evaluated the clinical utility of PoCT in the care of 193 Malawian children treated for World Health Organization-defined cerebral malaria (CM) between March 2019 and May 2023. We assessed the frequency of abnormal PoCT results and the clinical interventions performed in response to these abnormalities. We determined the association between abnormal PoCT results and patient outcomes. Overall, 52.1% of all PoCT results were abnormal. Of the children with abnormal results, clinical interventions occurred in 16.9%. Interventions most commonly followed abnormal results for PoCT glucose (100.0% of the patients had treatment for hypoglycemia), potassium (32.1%), lactate (22.0%), and creatinine (16.3%). Patients with hypoglycemia, hyperlactatemia, and hypocalcemia had a higher mortality risk than children with normal values. Future studies are needed to determine whether obtaining laboratory values using PoCT and the clinical response to these interventions modify outcomes in critically ill African children with CM.

Understanding Implicit Regularization in Over-Parameterized Single Index Model.

In this paper, we leverage over-parameterization to design regularization-free algorithms for the high-dimensional single index model and provide theoretical guarantees for the induced implicit regularization phenomenon. Specifically, we study both vector and matrix single index models where the link function is nonlinear and unknown, the signal parameter is either a sparse vector or a low-rank symmetric matrix, and the response variable can be heavy-tailed. To gain a better understanding of the role played by implicit regularization without excess technicality, we assume that the distribution of the covariates is known a priori. For both the vector and matrix settings, we construct an over-parameterized least-squares loss function by employing the score function transform and a robust truncation step designed specifically for heavy-tailed data. We propose to estimate the true parameter by applying regularization-free gradient descent to the loss function. When the initialization is close to the origin and the stepsize is sufficiently small, we prove that the obtained solution achieves minimax optimal statistical rates of convergence in both the vector and matrix cases. In addition, our experimental results support our theoretical findings and also demonstrate that our methods empirically outperform classical methods with explicit regularization in terms of both ℓ2-statistical rate and variable selection consistency.

The chloroplast genome of Cuphea hookeriana Walp. (Lythraceae), a Mexico ornamental plant.

Cuphea hookeriana Walp. is an ornamental plant belonging to the Lythraceae. In this study, we reported the complete chloroplast (cp) genome sequence here and analyzed the phylogenetic relationship among Lythraceae plants. The length of the cp genome was 158,999 bp, including a large single-copy (LSC, 89,311 bp) region and a small single-copy (SSC, 18,436 bp) region separated by a pair of inverted repeats (IRs, 25,626 bp). There were 72 unique protein-coding genes (PCGs), 30 transfer RNA (tRNA) genes, and four ribosomal RNA (rRNA) genes in the cp genome of C. hookeriana. A total of 223 simple sequence repeats (SSRs) and 34 long repeat sequences were identified. Phylogenetic analyses using maximum-likelihood (ML) revealed that C. hookeriana was close to C. hyssopifolia. In addition, the two Cuphea species were the sister group of Woodfordia fruticosa.

Research progress and hotspot of the artificial intelligence application in the ultrasound during 2011-2021: A bibliometric analysis.

Ultrasound, as a common clinical examination tool, inevitably has human errors due to the limitations of manual operation. Artificial intelligence is an advanced computer program that can solve this problem. Therefore, the relevant literature on the application of artificial intelligence in the ultrasonic field from 2011 to 2021 was screened by authors from the Web of Science Core Collection, which aims to summarize the trend of artificial intelligence application in the field of ultrasound, meanwhile, visualize and predict research hotspots. A total of 908 publications were included in the study. Overall, the number of global publications is on the rise, and studies on the application of artificial intelligence in the field of ultrasound continue to increase. China has made the largest contribution in this field. In terms of institutions, Fudan University has the most number of publications. Recently, IEEE Access is the most published journal. Suri J. S. published most of the articles and had the highest number of citations in this field (29 articles). It's worth noting that, convolutional neural networks (CNN), as a kind of deep learning algorithm, was considered to bring better image analysis and processing ability in recent most-cited articles. According to the analysis of keywords, the latest keyword is "COVID-19" (2020.8). The co-occurrence analysis of keywords by VOSviewer visually presented four clusters which consisted of "deep learning," "machine learning," "application in the field of visceral organs," and "application in the field of cardiovascular". The latest hot words of these clusters were "COVID-19; neural-network; hepatocellular carcinoma; atherosclerotic plaques". This study reveals the importance of multi-institutional and multi-field collaboration in promoting research progress.

A new calcium(II) complex of marbofloxacin showing much lower acute toxicity with retained antibacterial activity.

Marbofloxacin (MB) is a newly developed veterinary drug with broad-spectrum antibacterial activity. In this study, a new calcium(II)-based complex of marbofloxacin, MB-Ca, was synthesized and structurally characterized by IR, ESI-MS, UV-Vis and single crystal X-ray diffraction analysis. The characterization of this complex in solution state indicated that the coordinated MB-Ca was partly retained, along with the monomeric and dimeric forms of MB. It also showed satisfactory water solubility (1.89 mg/mL), comparing with MB (2.82 mg/mL) at 35 °C. The in vitro antibacterial activity of MB-Ca was also screened towards a series of typical pathogenic bacteria, and determined by the methods of turbidimetry and disc diffusion. The results indicated it showed comparable antibacterial activity to MB. However, it exhibited higher inhibitive ability in vitro on DNA gyrase than MB alone. Furthermore, MB-Ca showed significantly lower acute toxicity (LD50, 3186 mg/kg) than MB (LD50, 1294 mg/kg) in mice, based on the in vivo acute toxicity test. The histopathological examination on the major organs of the mice by the oral administration of MB-Ca did not show obvious organic lesions, which is similar to those treated by MB. The research results suggest that MB-Ca could be further developed into a new promising metal-based veterinary drug and a better substitute of MB, showing unabated antibacterial activity along with lower toxicity.