Divergence of the freshwater sleeper, Neodontobutishainanensis (Chen, 1985) (Teleostei, Odontobutidae), in the Pearl River basin and on Hainan Island of southern China.

Study of divergence of freshwater fish populations between island and adjacent mainland areas can shed light on the phylogeographical relationships of these regions. Neodontobutishainanensis is a freshwater fish species restricted to Hainan Island and in Guangdong and Guangxi provinces in the southern mainland China. We examine the phylogenetic relationship and population structure of N.hainanensis based on 3,176 nuclear loci using a gene-capture method. STRUCTURE analysis and principal coordinate analyses (PCA) indicate that populations from Guangdong, Guangxi and Hainan are each distinct, except that some individuals of the Guangdong population share minor genetic components with individuals of the Guangxi population. In the concatenated gene tree, the Hainan population is grouped with the Guangdong population, but the coalescent tree groups the Hainan population as the sister to the Guangxi population. Finally, coalescent simulations confirmed the divergence pattern supported by the coalescent tree and revealed a one-way introgression from the Guangxi population to the Guangdong population, which can explain the discordant results supported by the concatenated and coalescent phylogenetic analyses. Due to recent decline of N.hainanensis populations and the genetic patterns in this species, as revealed in this study, the populations in the three areas should be treated as separate conservation units.

Mutations in BrABCG26, encoding an ATP-binding cassette transporter, are responsible for male sterility in Chinese cabbage (Brassica rapa L. ssp. pekinensis).

KEY MESSAGE: The gene BrABCG26 responsible for male sterility of Chinese cabbage was confirmed by two allelic mutants. Male-sterile lines are an important way of heterosis utilization in Chinese cabbage. In this study, two allelic male-sterile mutants msm3-1 and msm3-2 were obtained from a Chinese cabbage double haploid (DH) line 'FT' by using EMS-mutagenesis. Compared to the wild-type 'FT,' the stamens of mutants were completely degenerated and had no pollen, and other characters had no obvious differences. Cytological observation revealed that the failure of vacuolation of the mononuclear microspore, accompanied by abnormal tapetal degradation, resulted in anther abortion in mutants. Genetic analysis showed that a recessive gene controlled the mutant trait. MutMap combined with kompetitive allele specific PCR genotyping analyses showed that BraA01g038270.3C, encoding a transporter ABCG26 that played a vital role in pollen wall formation, was the candidate gene for msm3-1, named BrABCG26. Compared with wild-type 'FT,' the mutations existed on the second exon (C to T) and the sixth exon (C to T) of BrABCG26 gene in mutants msm3-1 and msm3-2, leading to the loss-of-function truncated protein, which verified the BrABCG26 function in stamen development. Subcellular localization and expression pattern analysis indicated that BrABCG26 was localized in the nucleus and was expressed in all organs, with the highest expression in flower buds. Compared to the wild-type 'FT,' the expressions of BrABCG26 were significantly reduced in flower buds and anthers of mutants. Promoter activity analysis showed that a strong GUS signal was detected in flower buds. These results indicated that BrABCG26 is responsible for the male sterility of msm3 mutants in Chinese cabbage.

Spin-labeling Insights into How Chemical Fixation Impacts Glycan Organization on Cells.

As new methods to interrogate glycan organization on cells develop, it is important to have a molecular level understanding of how chemical fixation can impact results and interpretations. Site-directed spin labeling technologies are well suited to study how the spin label mobility is impacted by local environmental conditions, such as those imposed by cross-linking effects of paraformaldehyde cell fixation methods. Here, we utilize three different azide-containing sugars for metabolic glycan engineering with HeLa cells to incorporate azido glycans that are modified with a DBCO-based nitroxide moiety via click reaction. Continuous wave X-band electron paramagnetic resonance spectroscopy is employed to characterize how the chronological sequence of chemical fixation and spin labeling impacts the local mobility and accessibility of the nitroxide-labeled glycans in the glycocalyx of HeLa cells. Results demonstrate that chemical fixation with paraformaldehyde can alter local glycan mobility and care should be taken in the analysis of data in any study where chemical fixation and cellular labeling occur.

Designing surface exposed sites on Bacillus subtilis lipase A for spin-labeling and hydration studies.

Spin-labeling with electron paramagnetic resonance spectroscopy (EPR) is a facile method for interrogating macromolecular flexibility, conformational changes, accessibility, and hydration. Within we present a computationally based approach for the rational selection of reporter sites in Bacillus subtilis lipase A (BSLA) for substitution to cysteine residues with subsequent modification with a spin-label that are expected to not significantly perturb the wild-type structure, dynamics, or enzymatic function. Experimental circular dichroism spectroscopy, Michaelis-Menten kinetic parameters and EPR spectroscopy data validate the success of this approach to computationally select reporter sites for future magnetic resonance investigations of hydration and hydration changes induced by polymer conjugation, tethering, immobilization, or amino acid substitution in BSLA. Analysis of molecular dynamic simulations of the impact of substitutions on the secondary structure agree well with experimental findings. We propose that this computationally guided approach for choosing spin-labeled EPR reporter sites, which evaluates relative surface accessibility coupled with hydrogen bonding occupancy of amino acids to the catalytic pocket via atomistic simulations, should be readily transferable to other macromolecular systems of interest including selecting sites for paramagnetic relaxation enhancement NMR studies, other spin-labeling EPR studies or any method requiring a tagging method where it is desirable to not alter enzyme stability or activity.

The intersection of virus infection and liver disease: A comprehensive review of pathogenesis, diagnosis, and treatment.

Liver disease represents a significant global burden, placing individuals at a heightened risk of developing cirrhosis and liver cancer. Viral infections act as a primary cause of liver diseases on a worldwide scale. Infections involving hepatitis viruses, notably hepatitis B, C, and E viruses, stand out as the most prevalent contributors to acute and chronic intrahepatic adverse outcome, although the hepatitis C virus (HCV) can be effectively cured with antiviral drugs, but no preventative vaccination developed. Hepatitis B virus (HBV) and HCV can lead to both acute and chronic liver diseases, including liver cirrhosis and hepatocellular carcinoma (HCC), which are principal causes of worldwide morbidity and mortality. Other viruses, such as Epstein-Barr virus (EBV) and cytomegalovirus (CMV), are capable of causing liver damage. Therefore, it is essential to recognize that virus infections and liver diseases are intricate and interconnected processes. A profound understanding of the underlying relationship between virus infections and liver diseases proves pivotal in the effective prevention, diagnosis, and treatment of these conditions. In this review, we delve into the mechanisms by which virus infections induce liver diseases, as well as explore the pathogenesis, diagnosis, and treatment of liver diseases. This article is categorized under: Infectious Diseases > Biomedical Engineering.

Energy utilization of agricultural waste: Machine learning prediction and pyrolysis transformation.

The rapid screening of agricultural waste materials for capacitor preparation holds significant importance in comprehending the relationship between material properties and enhancing experimental efficiency. In this study, we developed two machine learning models to predict electrode material characteristics using 2997 data points extracted from 235 articles. The identification and influence of key features on prediction indices provide a theoretical foundation for subsequent practical preparation. Through regression analysis and index evaluation, corn straw emerged as the optimal material for capacitor preparation, leading us to propose a one-step activation and two-step modification approach to convert corn straw into porous biochar. By modifying biochar with Co(NO3)2·6H2O, the maximum electrode capacitance of porous carbon reached 732.6 F/g. Furthermore, the electrode exhibited exceptional cycle stability with a remaining capacitance of 96 % after 5000 cycles. The prepared symmetric capacitor demonstrated pseudocapacitance behavior with a capacitance of 183.15 F/g at a current density of 1.0 A/g, power density of 22 kW/kg, and energy density of 9.03 Wh/kg. Considering the increasing annual output of corn straw and its superior industrial application prospects compared to acid-, base-, or precious metal-based alternatives due to their cost-effectiveness and environmental friendliness, these findings highlight the potential practical value in utilizing modified corn straw biochar as an efficient energy storage electrode material.

Establishment and application of TSDPSO-SVM model combined with multi-dimensional feature fusion method in the identification of fracture-related infection.

Fracture-related infection (FRI) is one of the most common and intractable complications in orthopedic trauma surgery. This complication can impose severe psychological burdens and socio-economic impacts on patients. Although the definition of FRI has been proposed recently by an expert group, the diagnostic criteria for FRI are not yet standardized. A total of 4761 FRI patients and 4761 fracture patients (Non-FRI) were included in the study. The feature set of patients included imaging characteristics, demographic information, clinical symptoms, microbiological findings, and serum inflammatory markers, which were reduced by the Principal Component Analysis. To optimize the Support Vector Machine (SVM) model, the Traction Switching Delay Particle Swarm Optimization (TSDPSO) algorithm, a recognition method was proposed. Moreover, five machine learning models, including TSDPSO-SVM, were employed to distinguish FRI from Non-FRI. The Area under the Curve of TSDPSO-SVM was 0.91, at least 5% higher than that of other models. Compared with the Random Forest, Backpropagation Neural Network (BP), SVM and eXtreme Gradient Boosting (XGBoost), TSDPSO-SVM demonstrated remarkable accuracy in the test set ([Formula: see text]). The recall of TSDPSO-SVM was 98.32%, indicating a significant improvement ([Formula: see text]). Compared with BP and SVM, TSDPSO-SVM exhibited significantly superior specificity, false positive rate and precision ([Formula: see text]. The five models yielded consistent results in the training and testing of FRI patients across different age groups. TSDPSO-SVM is validated to have the maximum overall prediction ability and can effectively distinguish between FRI and Non-FRI. For the early diagnosis of FRI, TSDPSO-SVM may provide a reference basis for clinicians, especially those with insufficient experience. These results also lay a foundation for the intelligent diagnosis of FRI. Furthermore, these findings exhibit the application potential of this model in the diagnosis and classification of other diseases.

Dendrimer-conjugated isotretinoin for controlled transdermal drug delivery.

BACKGROUND: In the present study, we aimed to develop a novel isotretinoin delivery model for treating skin diseases, revealing its potential advantages in drug delivery and targeted therapy. Using a self-assembly strategy, we grafted a dendrimer, based on a well-defined branched structure for nanomedical devices, with a well-defined nanoarchitecture, yielding spherical, highly homogeneous molecules with multiple surface functionalities. Accordingly, a self-assembled dendrimer-conjugated system was developed to achieve the transdermal delivery of isotretinoin (13cRA-D). RESULTS: Herein, 13cRA-D showed remarkable controlled release, characterized by slow release in normal tissues but accelerated release in tissues with low pH, such as sites of inflammation. These release characteristics could abrogate the nonteratogenic side effects of isotretinoin and allow efficient skin permeation. Moreover, 13cRA-D exhibited high therapeutic efficacy in acne models. Based on in vitro and in vivo experimental results, 13cRA-D afforded better skin penetration than isotretinoin and allowed lesion targeting. Additionally, 13cRA-D induced minimal skin irritation. CONCLUSION: Our findings suggest that 13cRA-D is a safe and effective isotretinoin formulation for treating patients with skin disorders.

Spin-labeling Insights into How Chemical Fixation Impacts Glycan Organization on Cells.

As new methods to interrogate glycan organization on cells develop, it is important to have a molecular level understanding of how chemical fixation can impact results and interpretations. Site-directed spin labeling technologies are well suited to study how the spin label mobility is impacted by local environmental conditions, such as those imposed by cross-linking effects of paraformaldehyde cell fixation methods. Here, we utilize three different azide-containing sugars for metabolic glycan engineering with HeLa cells to incorporate azido glycans that are modified with a DBCO-based nitroxide moiety via click reaction. Continuous wave X-band electron paramagnetic resonance spectroscopy is employed to characterize how the chronological sequence of chemical fixation and spin labeling impacts the local mobility and accessibility of the nitroxide-labeled glycans in the glycocalyx of HeLa cells. Results demonstrate that chemical fixation with paraformaldehyde can alter local glycan mobility and care should be taken in the analysis of data in any study where chemical fixation and cellular labeling occur.

Stable tissue-mimicking phantoms for longitudinal multimodality imaging studies that incorporate optical, CT, and MRI contrast.

Significance: Tissue phantoms that mimic the optical and radiologic properties of human or animal tissue play an important role in the development, characterization, and evaluation of imaging systems. Phantoms that are easily produced and stable for longitudinal studies are highly desirable. Aim: A new type of long-lasting phantom was developed with commercially available materials and was assessed for fabrication ease, stability, and optical property control. Magnetic resonance imaging (MRI) and x-ray computed tomography (CT) contrast properties were also evaluated. Approach: A systematic investigation of relationships between concentrations of skin-like pigments and composite optical properties was conducted to realize optical property phantoms in the red and near-infrared (NIR) wavelength range that also offered contrast for CT and MRI. Results: Phantom fabrication time was < 1 h and did not involve any heating or cooling processes. Changes in optical properties were < 2 % over a 12-month period. Phantom optical and spectral features were similar to human soft tissue over the red to NIR wavelength ranges. Pigments used in the study also had CT and MRI contrasts for multimodality imaging studies. Conclusions: The phantoms described here mimic optical properties of soft tissue and are suitable for multimodality imaging studies involving CT or MRI without adding secondary contrast agents.

Discovery of Linvencorvir (RG7907), a Hepatitis B Virus Core Protein Allosteric Modulator, for the Treatment of Chronic HBV Infection.

Described herein is the first-time disclosure of Linvencorvir (RG7907), a clinical compound and a hepatitis B virus (HBV) core protein allosteric modulator, for the treatment of chronic HBV infection. Built upon the core structure of hetero aryl dihydropyrimidine, RG7907 was rationally designed by combining all the drug-like features of low CYP3A4 induction, potent anti-HBV activity, high metabolic stability, low hERG liability, and favorable animal pharmacokinetic (PK) profiles. In particular, the chemistry strategy to mitigate CYP3A4 induction through introducing a large, rigid, and polar substituent at the position that has less interaction with the therapeutic biological target (HBV core proteins herein) is of general interest to the medicinal chemistry community. RG7907 demonstrated favorable animal PK, pharmacodynamics, and safety profiles with sufficient safety margins supporting its clinical development in healthy volunteers and HBV-infected patients.

Different Biophysical Properties of Cell Surface α2,3- and α2,6-Sialoglycans Revealed by Electron Paramagnetic Resonance Spectroscopic Studies.

Sialoglycans on HeLa cells were labeled with a nitroxide spin radical through enzymatic glycoengineering (EGE)-mediated installation of azide-modified sialic acid (Neu5Ac9N3) and then click reaction-based attachment of a nitroxide spin radical. α2,6-Sialyltransferase (ST) Pd2,6ST and α2,3-ST CSTII were used for EGE to install α2,6- and α2,3-linked Neu5Ac9N3, respectively. The spin-labeled cells were analyzed by X-band continuous wave (CW) electron paramagnetic resonance (EPR) spectroscopy to gain insights into the dynamics and organizations of cell surface α2,6- and α2,3-sialoglycans. Simulations of the EPR spectra revealed average fast- and intermediate-motion components for the spin radicals in both sialoglycans. However, α2,6- and α2,3-sialoglycans in HeLa cells possess different distributions of the two components, e.g., a higher average population of the intermediate-motion component for α2,6-sialoglycans (78%) than that for α2,3-sialoglycans (53%). Thus, the average mobility of spin radicals in α2,3-sialoglycans was higher than that in α2,6-sialoglycans. Given the fact that a spin-labeled sialic acid residue attached to the 6-O-position of galactose/N-acetyl-galactosamine would experience less steric hindrance and show more flexibility than that attached to the 3-O-position, these results may reflect the differences in local crowding/packing that restrict the spin-label and sialic acid motion for α2,6-linked sialoglycans. The studies further suggest that Pd2,6ST and CSTII may have different preferences for glycan substrates in the complex environment of the extracellular matrix. The discoveries of this work are biologically important as they are useful for interpreting the different functions of α2,6- and α2,3-sialoglycans and indicate the possibility of using Pd2,6ST and CSTII to target different glycoconjugates on cells.

19.10% Efficiency and 80.5% Fill Factor Layer-by-Layer Organic Solar Cells Realized by 4-Bis(2-Thienyl)Pyrrole-2,5-Dione Based Polymer Additives for Inducing Vertical Segregation Morphology.

The morphology plays a key role in determining the charge generation and collection process, thus impacting the performances of organic solar cells (OSCs). The limited selection pool of additives to optimize the morphology of OSCs, especially for the emerging layer-by-layer (LbL) OSCs, impeding the improvements of photovoltaic performances. Herein, a new method of using conjugated polymers as the additives to optimize the morphology for improving the photovoltaic performances of LbL-OSCs is reported. Four polymers of PH, PS, PF, and PCl are developed with different side chains. These polymers exhibit poor performances as donor materials and additives in the BHJ devices, due to the unsuitable energy level alignment and unfavorable molecular interactions. By contrast, they can be served as efficient additives to optimize the PM6 fibril matrix for facilitating the penetration of BTP-eC9 and forming an intertwined D/A bicontinuous network with a vertical segregation. Such morphology is optimized by side chain engineering, which enables the progressive improvement of the charge separation and collection. As a result, adding a small amount of PCl as the additive, the optimized morphology contributes to a champion PCE of 19.10% with a high FF of 80.5%.

Neodontobutis lani, a new sleeper fish of the family Odontobutidae (Teleostei: Gobiiformes) from Guangxi, southern China.

A new species, Neodontobutis lani (Odontobutidae) is described from the Zuojiang River, a tributary of the Xijiang River of the Pearl River basin, at Longzhou Town, Guangxi Zhuang Autonomous Region, Southern China. This species can be distinguished from other Neodontobutis species by following characters: anterior head flat, with interorbital width / eye diameter = 1.41.9 (vs. less than 1.4); several rows (vs. single row) of transforming ctenii on posterior edges of body scales; sensory papilla on lower jaw arranged in two oblong clusters (vs. two single lines). It can be distinguished from Odontobutis species by: separated right and left gill membrane (vs. joined); barbel-like projection present on sensory papillae. Molecular phylogenetic analysis of 2,076 nuclear coding loci indicates that N. lani is a sister species of N. hainanensis, the only Neodontobutis species that has been described from China.

Review on Chemical Constituents of Schizonepeta tenuifolia Briq. and Their Pharmacological Effects

Schizonepeta tenuifolia Briq. is a famous Chinese traditional medicine with antipyretic, anti-inflammatory, analgesic and hemostatic effects. Many chemical components can be isolated and detected by using various analysis methods, including monoterpenes, sesquiterpenes, aldehydes, ketones, quinones, alcohols, phenols, carboxylic acids and esters, etc., in which volatile oil was considered to be the main chemical component. In this paper, the chemical constituents and their pharmacological effects were reviewed by summarizing the recent literature, revealing the relationship between them.

Tracking single adatoms in liquid in a transmission electron microscope.

Single atoms or ions on surfaces affect processes from nucleation1 to electrochemical reactions2 and heterogeneous catalysis3. Transmission electron microscopy is a leading approach for visualizing single atoms on a variety of substrates4,5. It conventionally requires high vacuum conditions, but has been developed for in situ imaging in liquid and gaseous environments6,7 with a combined spatial and temporal resolution that is unmatched by any other method-notwithstanding concerns about electron-beam effects on samples. When imaging in liquid using commercial technologies, electron scattering in the windows enclosing the sample and in the liquid generally limits the achievable resolution to a few nanometres6,8,9. Graphene liquid cells, on the other hand, have enabled atomic-resolution imaging of metal nanoparticles in liquids10. Here we show that a double graphene liquid cell, consisting of a central molybdenum disulfide monolayer separated by hexagonal boron nitride spacers from the two enclosing graphene windows, makes it possible to monitor, with atomic resolution, the dynamics of platinum adatoms on the monolayer in an aqueous salt solution. By imaging more than 70,000 single adatom adsorption sites, we compare the site preference and dynamic motion of the adatoms in both a fully hydrated and a vacuum state. We find a modified adsorption site distribution and higher diffusivities for the adatoms in the liquid phase compared with those in vacuum. This approach paves the way for in situ liquid-phase imaging of chemical processes with single-atom precision.

Single-shot hyperspectral imaging based on dual attention neural network with multi-modal learning.

Hyperspectral imaging is being extensively investigated owing to its promising future in critical applications such as medical diagnostics, sensing, and surveillance. However, current techniques are complex with multiple alignment-sensitive components and spatiospectral parameters predetermined by manufacturers. In this paper, we demonstrate an end-to-end snapshot hyperspectral imaging technique and build a physics-informed dual attention neural network with multimodal learning. By modeling the 3D spectral cube reconstruction procedure and solving that compressive-imaging inverse problem, the hyperspectral volume can be directly recovered from only one scene RGB image. Spectra features and camera spectral sensitivity are jointly leveraged to retrieve the multiplexed spatiospectral correlations and realize hyperspectral imaging. With the help of integrated attention mechanism, useful information supplied by disparate modal components is adaptively learned and aggregated to make our network flexible for variable imaging systems. Results show that the proposed method is ultra-faster than the traditional scanning method, and 3.4 times more precise than the existing hyperspectral imaging convolutional neural network. We provide theory for network design, demonstrate training process, and present experimental results with high accuracy. Without bulky benchtop setups and strict experimental limitations, this simple and effective method offers great potential for future spectral imaging applications such as pathological digital stain, computational imaging and virtual/augmented reality display, etc.

Enzymatic glycoengineering-based spin labelling of cell surface sialoglycans to enable their analysis by electron paramagnetic resonance (EPR) spectroscopy.

A novel method for spin labelling of sialoglycans on the cell surface is described. C9-Azido sialic acid was linked to glycans on live cells via CSTII-catalysed α2,3-sialylation utilizing azido-sialic acid nucleotide as a sialyl donor, which was followed by attachment of a spin label to the azide via click reaction. It enables the study of cell surface sialoglycans by EPR spectroscopy.

SL-HarDNet: Skin lesion segmentation with HarDNet.

Automatic segmentation of skin lesions from dermoscopy is of great significance for the early diagnosis of skin cancer. However, due to the complexity and fuzzy boundary of skin lesions, automatic segmentation of skin lesions is a challenging task. In this paper, we present a novel skin lesion segmentation network based on HarDNet (SL-HarDNet). We adopt HarDNet as the backbone, which can learn more robust feature representation. Furthermore, we introduce three powerful modules, including: cascaded fusion module (CFM), spatial channel attention module (SCAM) and feature aggregation module (FAM). Among them, CFM combines the features of different levels and effectively aggregates the semantic and location information of skin lesions. SCAM realizes the capture of key spatial information. The cross-level features are effectively fused through FAM, and the obtained high-level semantic position information features are reintegrated with the features from CFM to improve the segmentation performance of the model. We apply the challenge dataset ISIC-2016&PH2 and ISIC-2018, and extensively evaluate and compare the state-of-the-art skin lesion segmentation methods. Experiments show that our SL-HarDNet performance is always superior to other segmentation methods and achieves the latest performance.