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Purpose: To report a novel hemizygous nonsense variant in the CACNA1F gene associated with congenital stationary night blindness (CSNB) in a pediatric patient, emphasizing the utility of portable electroretinography (ERG) and genetic testing in diagnosing unexplained visual impairments., Methods: The patient, a 5-year-old male, underwent comprehensive clinical evaluation, including detailed anterior segment and fundus examinations, full-field electroretinogram (ffERG) using a RETeval™ portable device, and whole exome sequencing (WES) to elucidate the genetic basis of his visual impairment. Structural modeling of the mutated protein was performed using SWISS-MODEL and PYMOL., Results: Best-corrected visual acuity was 0.4 logMAR bilaterally, with unremarkable anterior segment and fundus examinations. FFERG revealed significant abnormalities consistent with incomplete CSNB: severely reduced rod response in dark-adapted (DA) 0.01, negative waveform with b/a wave ratio < 1.0 in DA 3.0, and diminished cone response in light-adapted ERG. WES identified a novel pathogenic variant in the CACNA1F gene (c.1234G > T, p.E412*), inherited maternally. This variant introduces a premature stop codon at position 412, likely resulting in a truncated CACNA1F protein., Conclusions: This case highlights the importance of comprehensive clinical assessments and genetic testing in pediatric patients with unexplained visual impairments, revealing a novel CACNA1F variant that expands our understanding of CSNB. The use of a portable ERG device proved particularly valuable in assessing retinal function in this young patient. Further investigations are warranted to elucidate the clinical implications of this novel pathogenic variant., Competing Interests: Declarations. Conflict of Interest: The authors declare that they have no competing interests. Informed consent: Informed consent was obtained from the patient’s parents. Human rights: The study received approval from the Medical Ethics Committee of Xiang'an Hospital of Xiamen University (XAHLL2022028, March 7, 2022), in accordance with the Declaration of Helsinki., (© 2024. The Author(s).)

Purpose: To elucidate the genetic basis of primary angle-closure glaucoma (PACG) by identifying pathogenic tissue and critical tissue-specific variants., Methods: The correlations among PACG susceptibility, axial length (AL), and anterior chamber depth (ACD) were evaluated using meta-analyses. Propensity score matching was utilized on 2161 participants from the Handan Eye Study to determine the risk factors independent of ACD and AL for PACG. Subsequently, we employed the assay for transposase-accessible chromatin with sequencing (ATAC-seq) and allele-specific self-transcribing active regulatory region sequencing (STARR-seq) to screen 202 PACG genome-wide association study (GWAS) variants for chromatin accessibility and functional roles., Results: The meta-analysis found that PACG susceptibility loci are not associated with ACD or AL. However, abnormal iris phenotypes emerged as significant independent risk factors for primary angle-closure disease (PACD), unrelated to ACD and AL. Substantial enrichment of PACG heritability was observed in the open chromatin regions of the human iris. Within the iris-relevant cellular context, 22 out of the 202 PACG GWAS variants could influence enhancer activity. Two variants in the iris open chromatin regions were implicated in the modulation of PLEKHA7 and C10orf53 expression. The downregulation of these two genes affects cytoskeletal organization., Conclusions: Our findings underscore the importance of the iris in the pathogenesis of PACG and identified iris-specific, enhancer-modulating variants that may influence disease risk. Our approach also provides a generalizable framework for studying ocular diseases from the perspective of enhancer-modulating variants.

Background: Older adults with chronic diseases are at higher risk of depressive symptoms than those without. For the onset of depressive symptoms, the prediction ability of changes in common risk factors over a 2-year follow-up period is unclear in the Chinese older population. This study aimed to build risk prediction models (RPMs) to estimate the probability of incident 2-year depression using data from the China Health and Retirement Longitudinal Study (CHARLS)., Methods: Four ML algorithms (logistic regression [LR], AdaBoost, random forest [RF] and k-nearest neighbor [kNN]) were applied to develop RPMs using the 2011-2015 cohort data. These developed models were then validated with 2018-2020 survey data. We evaluated the model performance using discrimination and calibration metrics, including an area under the receiver operating characteristic curve (AUROC) and the precision-recall curve (AUPRC), accuracy, sensitivity and calibrations plot. Finally, we explored the key factors of depressive symptoms by the selected best predictive models., Results: This study finally included 7,121 participants to build models to predict depressive symptoms, finding a 21.5% prevalence of depression. Combining the Synthetic Minority Oversampling Technique (SMOTE) with the logistic regression model (LR-SM) exhibited superior precision to predict depression than other models, with an AUROC and AUPRC of 0.612 and 0.468, respectively, an accuracy of 0.619 and a sensitivity of 0.546. In additiona, external validation of the LR-SM model using data from the 2018-2020 data also demonstrated good predictive ability with an AUROC of 0.623 (95% CI: 0.555- 0.673). Sex, self-rated health status, occupation, eyesight, memory and life satisfaction were identified as impactful predictors of depression., Conclusions: Our developed models exhibited high accuracy, good discrimination and calibration profiles in predicting two-year risk of depression among older adults with chronic diseases. This model can be used to identify Chinese older population at high risk of depression and intervene in a timely manner., Competing Interests: Declarations. Ethics approval and consent to participate: This study was carried out based on data extracted from the CHARLS public database, and all methods were performed according to the relevant guidelines and regulations. Written informed consent was obtained from all participants or their legal agents before the commencement of any study process. The CHARLS survey was approved by the biomedical ethics committee of Peking University, Beijing, China (approval number: IRB00001052-13074), and all respondents provided written informed consent. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

Purpose: To explore the in vitro killing effect of water-soluble berberine and lipid-soluble niclosamide against ocular Demodex folliculorum., Methods: Demodex with good vigor were collected from patients' eyelashes. These mites were randomly distributed into different groups with 20 mites in each group. Saline, Double Distilled Water (DDW), Polysorbate 80 (TWEEN 80), Polyethylene glycol 300 (PEG 300) and Castor Oil were used to screen solvents and cosolvents. 20 % Tea Tree Oil (TTO) and Anhydrous Ethanol (EtOH) were used as positive controls. 0.2 % Berberine, 0.25 % Niclosamide and 0.5 % Niclosamide, were designated as experimental groups. Following treatment, the analysis of Kaplan-Meier survival curves and survival time of mites and safety of drugs were then performed., Results: The survival of Demodex in vitro in Saline and DDW, was not significant different. Therefore, DDW, which was more conducive to the dissolution of berberine, was chosen as the solvent for berberine. 0.2 % Berberine significantly inhibited the survival distribution and survival time (P < 0.001) of Demodex in vitro compared with the DDW group. Through the evaluation of several cosolvents, PEG300 had milder effects on Demodex. Hence, the proportion of PEG300 in the niclosamide solvent group was increased to reduce the irritability of the vehicle. Furthermore, niclosamide could significantly inhibit the survival of Demodex compared with the vehicle group, and the effect of 0.5 % Niclosamide was more obvious (P < 0.001), and was better than 20 %TTO (P < 0.001). In addition, after niclosamide administration, Demodex bodies exhibited gradual distortion along with increased transparency and the presence of blurred dark particles compared to those in the vehicle group. Moreover, both drugs showed good subjective tolerability and safety in a mouse model., Conclusion: 0.2 % berberine and 0.5 % niclosamide effectively inhibited Demodex survival in vitro, with 0.5 % niclosamide superior to 20 % TTO. These two drugs, with anti-Demodex, anti-bacterial, and anti-inflammatory properties, may offer alternative treatment for Demodex blepharitis., (Copyright © 2024. Published by Elsevier Ltd.)

Enhancers play a critical role in dynamically regulating spatial-temporal gene expression and establishing cell identity, underscoring the significance of designing them with specific properties for applications in biosynthetic engineering and gene therapy. Despite numerous high-throughput methods facilitating genome-wide enhancer identification, deciphering the sequence determinants of their activity remains challenging. Here, we present the DREAM (DNA cis-Regulatory Elements with controllable Activity design platforM) framework, a novel deep learning-based approach for synthetic enhancer design. Proficient in uncovering subtle and intricate patterns within extensive enhancer screening data, DREAM achieves cutting-edge sequence-based enhancer activity prediction and highlights critical sequence features implicating strong enhancer activity. Leveraging DREAM, we have engineered enhancers that surpass the potency of the strongest enhancer within the Drosophila genome by approximately 3.6-fold. Remarkably, these synthetic enhancers exhibited conserved functionality across species that have diverged more than billion years, indicating that DREAM was able to learn highly conserved enhancer regulatory grammar. Additionally, we designed silencers and cell line-specific enhancers using DREAM, demonstrating its versatility. Overall, our study not only introduces an interpretable approach for enhancer design but also lays out a general framework applicable to the design of other types of cis-regulatory elements., (© The Author(s) 2024. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Super-enhancers (SEs) govern the expression of genes defining cell identity. However, the dynamic landscape of SEs and their critical constituent enhancers involved in skeletal muscle development remains unclear. In this study, using pig as a model, we employed cleavage under targets and tagmentation (CUT&Tag) to profile the enhancer-associated histone modification marker H3K27ac in skeletal muscle across two prenatal and three postnatal stages, and investigated how SEs influence skeletal muscle development. We identify three SE families with distinct temporal dynamics: continuous (Con, 397), transient (TS, 434), and de novo (DN, 756). These SE families are associated with different temporal gene expression trajectories, biological functions, and DNA methylation levels. Notably, several lines of evidence suggest a potential prominent role of Con SEs in regulating porcine muscle development and meat traits. To pinpoint key cis -regulatory units in Con SEs, we developed an integrative approach that leverages information from eRNA annotation, genome-wide association study (GWAS) signals, and high-throughput capture self-transcribing active regulatory region sequencing (STARR-seq) experiments. Within Con SEs, we identify 20 candidate critical enhancers with meat and carcass-associated DNA variations that affect enhancer activity, and infer their upstream transcription factors and downstream target genes. As a proof of concept, we experimentally validate the role of one such enhancer and its potential target gene during myogenesis. Our findings reveal the dynamic regulatory features of SEs in skeletal muscle development and provide a general integrative framework for identifying critical enhancers underlying the formation of complex traits., (© 2024 Zhang et al.; Published by Cold Spring Harbor Laboratory Press.)

Alkyl phosphonates are important motifs in medicinal chemistry, yet their efficient synthesis by direct C(sp 3 )-H functionalization remains a challenge. Here, we report straightforward access to benzylic phosphonates by direct C(sp 3 )-H functionalization in a cross-dehydrogenative-coupling reaction between non-specialized alkylarenes and unfunctionalized phosphites. Notably, the C-H substrates are used as the limiting reagents. The scope of benzylic C-H substrates is broad, and the mild reaction conditions allow for good functional group tolerance. Mechanistic studies indicate that the reaction proceeds via a radical pathway rather than the cationic pathway followed for specialized benzylic C-H substrates in previous methods., (© 2024 Wiley-VCH GmbH.)

Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy-tailed distributions in the complex traits. In the past decade, robust variable selection methods have emerged as powerful alternatives to the nonrobust ones to identify important genes associated with heterogeneous disease traits and build superior predictive models. In this study, to keep the remarkable features of the quantile LASSO and fully Bayesian regularized quantile regression while overcoming their disadvantage in the analysis of high-dimensional genomics data, we propose the spike-and-slab quantile LASSO through a fully Bayesian spike-and-slab formulation under the robust likelihood by adopting the asymmetric Laplace distribution (ALD). The proposed robust method has inherited the prominent properties of selective shrinkage and self-adaptivity to the sparsity pattern from the spike-and-slab LASSO (Roc̆ková and George, J Am Stat Associat, 2018, 113(521): 431-444). Furthermore, the spike-and-slab quantile LASSO has a computational advantage to locate the posterior modes via soft-thresholding rule guided Expectation-Maximization (EM) steps in the coordinate descent framework, a phenomenon rarely observed for robust regularization with nondifferentiable loss functions. We have conducted comprehensive simulation studies with a variety of heavy-tailed errors in both homogeneous and heterogeneous model settings to demonstrate the superiority of the spike-and-slab quantile LASSO over its competing methods. The advantage of the proposed method has been further demonstrated in case studies of the lung adenocarcinomas (LUAD) and skin cutaneous melanoma (SKCM) data from The Cancer Genome Atlas (TCGA)., (© 2024 John Wiley & Sons Ltd.)

Polyunsaturated fatty acids (PUFAs) are dietary components participating in neurotransmission and cell signaling. Pollen is a source of PUFAs for honeybees, and disruptions in dietary PUFAs reduce the cognitive performance of honeybees. We reveal that gut bacteria of honeybees contribute to fatty acid metabolism, impacting reward learning. Gut bacteria possess Δ-6 desaturases that mediate fatty acid elongation and compensate for the absence of honeybee factors required for fatty acid metabolism. Colonization with Gilliamella apicola, but not a mutant lacking the Δ-6 desaturase FADS2, increases the production of anandamide (AEA), a ligand of the endocannabinoid system, and alters learning and memory. AEA activates the Hymenoptera-specific transient receptor AmHsTRPA in astrocytes, which induces Ca 2+ influx and regulates glutamate re-uptake of glial cells to enhance reward learning. These findings illuminate the roles of gut symbionts in host fatty acid metabolism and the impacts of endocannabinoid signaling on the reward system of social insects., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: In recent years, ophthalmology has emerged as a new frontier in medical artificial intelligence (AI) with multi-modal AI in ophthalmology garnering significant attention across interdisciplinary research. This integration of various types and data models holds paramount importance as it enables the provision of detailed and precise information for diagnosing eye and vision diseases. By leveraging multi-modal ophthalmology AI techniques, clinicians can enhance the accuracy and efficiency of diagnoses, and thus reduce the risks associated with misdiagnosis and oversight while also enabling more precise management of eye and vision health. However, the widespread adoption of multi-modal ophthalmology poses significant challenges., Main Text: In this review, we first summarize comprehensively the concept of modalities in the field of ophthalmology, the forms of fusion between modalities, and the progress of multi-modal ophthalmic AI technology. Finally, we discuss the challenges of current multi-modal AI technology applications in ophthalmology and future feasible research directions., Conclusion: In the field of ophthalmic AI, evidence suggests that when utilizing multi-modal data, deep learning-based multi-modal AI technology exhibits excellent diagnostic efficacy in assisting the diagnosis of various ophthalmic diseases. Particularly, in the current era marked by the proliferation of large-scale models, multi-modal techniques represent the most promising and advantageous solution for addressing the diagnosis of various ophthalmic diseases from a comprehensive perspective. However, it must be acknowledged that there are still numerous challenges associated with the application of multi-modal techniques in ophthalmic AI before they can be effectively employed in the clinical setting., (© 2024. The Author(s).)

Whole-genome genotyping (WGG) stands as a pivotal element in genomic-assisted plant breeding. Nevertheless, sequencing-based approaches for WGG continue to be costly, primarily owing to the high expenses associated with library preparation and the laborious protocol. During prior development of foreground and background integrated genotyping by sequencing (FBI-seq), we discovered that any sequence-specific primer (SP) inherently possesses the capability to amplify a massive array of stable and reproducible non-specific PCR products across the genome. Here, we further improved FBI-seq by replacing the adapter ligated by Tn5 transposase with an arbitrary degenerate (AD) primer. The protocol for the enhanced FBI-seq unexpectedly mirrors a simplified thermal asymmetric interlaced (TAIL)-PCR, a technique that is widely used for isolation of flanking sequences. However, the improved TAIL-PCR maximizes the primer-template mismatched annealing capabilities of both SP and AD primers. In addition, leveraging of next-generation sequencing enhances the ability of this technique to assay tens of thousands of genome-wide loci for any species. This cost-effective, user-friendly, and powerful WGG tool, which we have named TAIL-PCR by sequencing (TAIL-peq), holds great potential for widespread application in breeding programs, thereby facilitating genome-assisted crop improvement., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

In addition to filtering some sediments, hydrophobic wood sponges can also absorb many organic solvents, particularly crude oil. The leakage of crude oil poses a serious threat to the marine ecosystem, and oil mixed with water also generates great danger for its use. From the perspective of low cost and high performance, wood sponges exhibit great potential for dealing with crude oil pollution. Wood sponge is a renewable material. With a highly oriented layered structure and a highly compressible three-dimensional porous frame, wood sponges are extremely hydrophobic, making them ideal for oil-water separation. Currently, the most common approach for creating wood sponge is to first destroy the wood cell wall to obtain a porous-oriented layered structure and then enhance the oil-water separation ability via superhydrophobic treatment. Wood sponge prepared using various experimental methods and different natural woods exhibits distinctive properties in regards to robustness, compressibility, fatigue resistance, and oil absorption ability. As an aerogel material, wood sponge offers multi-action (absorption, filtration) and reusable oil-water separation functions. This paper introduces the advantages of the use of wood sponge for oil-water separation. The physical and chemical properties of wood sponge and its mechanism of adsorbing crude oil are explained. The synthesis method and the properties are discussed. Finally, the use of wood sponge is summarized and prospected.

Background: Detecting potential depression and identifying the critical predictors of depression among older adults with chronic diseases are essential for timely intervention and management of depression. Therefore, risk prediction models (RPMs) of depression in elderly people should be further explored., Methods: A total of 3959 respondents aged 60 years or over from the wave four survey of the China Health and Retired Longitudinal Study (CHARLS) were included in this study. We used five machine learning (ML) algorithms and three data balancing techniques to construct RPMs of depression and calculated feature importance scores to determine which features are essential to depression., Results: The prevalence of depression was 19.2 % among older Chinese adults with chronic diseases in the wave four survey. The random forest (RF) model was more accurate than the other models after balancing the data using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, with an area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) of 0.957 and 0.920, respectively, a balanced accuracy of 0.891 and a sensitivity of 0.875. Furthermore, we further identified several important predictors between male and female patients via constructed sex-stratified models., Limitations: Further research on the clinical impact studies of our models and external validation are needed., Conclusions: After several techniques were used to address class imbalance issues, most RPMs achieved satisfactory accuracy in predicting depression among elderly people with chronic diseases. RPMs may thus become valuable screening tools for both older individuals and healthcare practitioners to assess the risk of depression., Competing Interests: Declaration of competing interest None., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.

We propose a visual Simultaneous Localization and Mapping (SLAM) algorithm that integrates target detection and clustering techniques in dynamic scenarios to address the vulnerability of traditional SLAM algorithms to moving targets. The proposed algorithm integrates the target detection module into the front end of the SLAM and identifies dynamic objects within the visual range by improving the YOLOv5. Feature points associated with the dynamic objects are disregarded, and only those that correspond to static targets are utilized for frame-to-frame matching. This approach effectively addresses the camera pose estimation in dynamic environments, enhances system positioning accuracy, and optimizes the visual SLAM performance. Experiments on the TUM public dataset and comparison with the traditional ORB-SLAM3 algorithm and DS-SLAM algorithm validate that the proposed visual SLAM algorithm demonstrates an average improvement of 85.70 and 30.92% in positioning accuracy in highly dynamic scenarios. In comparison to the DynaSLAM system using MASK-RCNN, our system exhibits superior real-time performance while maintaining a comparable ATE index. These results highlight that our pro-posed SLAM algorithm effectively reduces pose estimation errors, enhances positioning accuracy, and showcases enhanced robustness compared to conventional visual SLAM algorithms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gan, Xu, Jiang, Liu, Liu and Lan.)

Maintaining homeostasis within the intestinal microbiota is imperative for assessing the health status of hosts, and dysbiosis within the intestinal microbiota is closely associated with canine intestinal diseases. In recent decades, the modulation of canine intestinal health through probiotics and prebiotics has emerged as a prominent area of investigation. Evidence indicates that probiotics and prebiotics play pivotal roles in regulating intestinal health by modulating the intestinal microbiota, fortifying the epithelial barrier, and enhancing intestinal immunity. This review consolidates literature on using probiotics and prebiotics for regulating microbiota homeostasis in canines, thereby furnishing references for prospective studies and formulating evaluation criteria.

Objective: To develop an AI-assisted MRI model to identify surgical target areas in pediatric hip and periarticular infections., Methods: A retrospective study was conducted on the pediatric patients with hip and periarticular infections who underwent Magnetic Resonance Imaging(MRI)examinations from January 2010 to January 2023 in three hospitals in China. A total of 7970 axial Short Tau Inversion Recovery (STIR) images were selected, and the corresponding regions of osteomyelitis (label 1) and abscess (label 2) were labeled using the Labelme software. The images were randomly divided into training group, validation group, and test group at a ratio of 7:2:1. A Mask R-CNN model was constructed and optimized, and the performance of identifying label 1 and label 2 was evaluated using receiver operating characteristic (ROC) curves. Calculation of the average time it took for the model and specialists to process an image in the test group. Comparison of the accuracy of the model in the interpretation of MRI images with four orthopaedic surgeons, with statistical significance set at P < 0.05., Results: A total of 275 patients were enrolled, comprising 197 males and 78 females, with an average age of 7.10 ± 3.59 years, ranging from 0.00 to 14.00 years. The area under curve (AUC), accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 1 were 0.810, 0.976, 0.995, 0.969, 0.922, and 0.957, respectively. The AUC, accuracy, sensitivity, specificity, precision, and F1 score for the model to identify label 2 were 0.890, 0.957, 0.969, 0.915, 0.976, and 0.972, respectively. The model demonstrated a significant speed advantage, taking only 0.2 s to process an image compared to average 10 s required by the specialists. The model identified osteomyelitis with an accuracy of 0.976 and abscess with an accuracy of 0.957, both statistically better than the four orthopaedic surgeons, P < 0.05., Conclusion: The Mask R-CNN model is reliable for identifying surgical target areas in pediatric hip and periarticular infections, offering a more convenient and rapid option. It can assist unexperienced physicians in pre-treatment assessments, reducing the risk of missed and misdiagnosis., (© 2024. The Author(s).)

Campylobacter jejuni (C. jejuni) is a common pathogen that often causes diarrhea, loss of appetite, and even enteritis in domestic cats, affecting their growth and development, especially in kittens under 6 months of age. Oral passive immunization with chicken yolk antibody Y has been proved effective for the treatment of gastrointestinal pathogen infections due to its high specificity. In this study, C. jejuni was isolated from diarrheal cat feces, and the specific egg yolk antibody Y against C. jejuni was demonstrated to effectively inhibit its proliferation in vitro experiments. To evaluate the effect of anti- C. jejuni IgY, the mouse C. jejuni infection model was established and it was found that IgY could alleviate C. jejuni -induced clinical symptoms. Consistent with these results, the reduction of pro-inflammatory factors and intestinal colonization by C. jejuni in the IgY-treated groups, especially in the high dose group. We then evaluated the protective effect of IgY on young Ragdoll cats infected with C. jejuni . This specific antibody reduced the rate of feline diarrhea, protected the growth of young cats, inhibited systemic inflammatory hyperactivation, and increased fecal short-chain fatty acid concentrations. Notably, IgY may have a protective role by changing intestinal amino acid metabolism and affecting C. jejuni chemotaxis. Collectively, specific IgY is a promising therapeutic strategy for C. jejuni -induced cat diarrhea., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Li, Yan, Bian, Zhang, Liu, Deng, Deng and Han.)

Background: Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking., Results: Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model., Conclusions: Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms., (© 2024. The Author(s).)

Diabetic nephropathy (DN) is a primary diabetic complication ascribed to the pathological changes in renal microvessels. This study investigated the nuclear factor erythroid 2-related factor 2 (Nrf2)/Kelch ECH associating protein (Keap1)/antioxidant response element (ARE) signaling pathway impact of chitooligosaccharides (COS) with a certain degree of polymerization (DP) on DN mouse models and high glucose-damaged human kidney 2 (HK-2) cells. The findings indicated that COS effectively reduced the renal function indexes (uric acid [UA], urinary albumin excretion rate [UAER], urine albumin-to-creatinine ratio [UACR], blood urea nitrogen [BUN], and creatinine [Cre]) of DN mice. It increased ( p  < .05) the superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and catalase (CAT) antioxidant enzyme activity in the serum and kidneys, and decreased ( p  < .05) the malondialdehyde (MDA) content. The mechanistic investigation showed that COS significantly increased ( p  < .05) Nrf2 and downstream target gene ( GCLM , GCLC , HO-1 , and NQO-1 ) expression, and substantially decreased ( p  < .05) Keap1 expression. The protein level was consistent with the messenger RNA (mRNA) level in in vitro and in vivo models. The docking data indicated that COS and Keap1 protein binding included six hydrogen bond formation processes (Gly364, Arg415, Arg483, His436, Ser431, and Arg380). The COS intervention mechanism may be related to the Nrf2/Keap1/ARE antioxidant pathway. Therefore, it provides a scientific basis for COS application in developing special medical food for DN patients., Competing Interests: There is no conflict of interest among authors., (© 2024 The Authors. Food Science & Nutrition published by Wiley Periodicals LLC.)

Background/aims: To improve the accuracy of pterygium screening and detection through smartphones, we established a fusion training model by blending a large number of slit-lamp image data with a small proportion of smartphone data., Method: Two datasets were used, a slit-lamp image dataset containing 20 987 images and a smartphone-based image dataset containing 1094 images. The RFRC (Faster RCNN based on ResNet101) model for the detection model. The SRU-Net (U-Net based on SE-ResNeXt50) for the segmentation models. The open-cv algorithm measured the width, length and area of pterygium in the cornea., Results: The detection model (trained by slit-lamp images) obtained the mean accuracy of 95.24%. The fusion segmentation model (trained by smartphone and slit-lamp images) achieved a microaverage F 1 score of 0.8981, sensitivity of 0.8709, specificity of 0.9668 and area under the curve (AUC) of 0.9295. Compared with the same group of patients' smartphone and slit-lamp images, the fusion model performance in smartphone-based images (F 1 score of 0.9313, sensitivity of 0.9360, specificity of 0.9613, AUC of 0.9426, accuracy of 92.38%) is close to the model (trained by slit-lamp images) in slit-lamp images (F 1 score of 0.9448, sensitivity of 0.9165, specificity of 0.9689, AUC of 0.9569 and accuracy of 94.29%)., Conclusion: Our fusion model method got high pterygium detection and grading accuracy in insufficient smartphone data, and its performance is comparable to experienced ophthalmologists and works well in different smartphone brands., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Dry eye disease (DED) is a multifactorial disease in ocular surface, and inflammation plays an etiological role. Berberine (BBR) has shown efficacy in treating inflammatory diseases. Yet, there was no adequate information related to the therapeutic effects of BBR for DED., Purpose: To detect the effects and explore the potential mechanisms of BBR on DED., Study Design: In vitro, in vivo study and network pharmacology analysis were involved., Method: The human corneal epithelium cells viability was evaluated with different concentrations of BBR. Dry eye murine model was established by exposing to the desiccating stress, and Ciclosporin (CSA), BBR eye drops or vehicle were topical administration for 7 days. The phenol red cotton tests, Oregon-green-dextran staining and Periodic acid-Schiff staining were performed and evaluated the dry eye after treatment. Inflammation and apoptosis levels of ocular surface were quantified. The potential targets related to berberine and dry eye were collected from databases. The Protein-Protein interaction network analysis and GO & KEGG enrichment analysis were realized by STRING database, Metascape platform and Cytoscape software to find core targets and signaling pathways. The SchrÖdinger software was used to molecular docking and PyMOL software to visualization. Finally, the levels of PI3K/AKT/NFκB and MAPK pathways were detected., Result: The data revealed BBR could rescue impaired HCE under hyperosmotic conditions. In addition, BBR eye drops could ameliorate dry eye. And BBR eye drops suppressed the inflammatory factors and CD4 + T cells infiltration in conjunctiva. Besides, BBR eye drops protected ocular surface by avoiding the severe apoptosis and decreasing the level of MMP-3 and MMP-9. 148 common targets intersection between BBR and dry eye were found via network pharmacology analysis. Core proteins and core pathways were identified through PPI and GO&KEGG enrichment analysis. Molecular docking displayed excellent binding between BBR and those core targets. Finally, in vivo study verified that BBR eye drops had a therapeutic effect in dry eye by inhibiting PI3K/AKT/NFκB and MAPK pathways., Conclusion: The research provided convincing evidence that BBR could be a candidate drug for dry eye., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2023 Elsevier GmbH. All rights reserved.)

Eusocial pollinators are crucial elements in global agriculture. The honeybees and bumblebees are associated with a simple yet host-restricted gut community, which protect the hosts against pathogen infections. Recent genome mining has led to the discovery of biosynthesis pathways of bioactive natural products mediating microbe-microbe interactions from the gut microbiota. Here, we investigate the diversity of biosynthetic gene clusters in the bee gut microbiota by analyzing 477 genomes from cultivated bacteria and metagenome-assembled genomes. We identify 744 biosynthetic gene clusters (BGCs) covering multiple chemical classes. While gene clusters for the post-translationally modified peptides are widely distributed in the bee guts, the distribution of the BGC classes varies significantly in different bee species among geographic locations, which is attributed to the strain-level variation of bee gut members in the chemical repertoire. Interestingly, we find that Gilliamella strains possessing a thiopeptide-like BGC show potent activity against the pathogenic Melissococcus plutonius. The spectrometry-guided genome mining reveals a RiPP-encoding BGC from Gilliamella with a 10 amino acid-long core peptide exhibiting antibacterial potentials. This study illustrates the widespread small-molecule-encoding BGCs in the bee gut symbionts and provides insights into the bacteria-derived natural products as potential antimicrobial agents against pathogenic infections., (© 2023. The Author(s).)

The development and growth of porcine skeletal muscle determine pork quality and yield. While genetic regulation of porcine skeletal muscle development has been extensively studied using various omics data, the role of transposable elements (TEs) in this context has been less explored. To bridge this gap, we constructed a comprehensive atlas of TE expression throughout the developmental stages of porcine skeletal muscle. This was achieved by integrating porcine TE genomic coordinates with whole-transcriptome RNA-Seq data from 27 developmental stages. We discovered that in pig skeletal muscle, active Tes are closely associated with active epigenomic marks, including low levels of DNA methylation, high levels of chromatin accessibility, and active histone modifications. Moreover, these TEs include 6074 self-expressed TEs that are significantly enriched in terms of muscle cell development and myofibril assembly. Using the TE expression data, we conducted a weighted gene co-expression network analysis (WGCNA) and identified a module that is significantly associated with muscle tissue development as well as genome-wide association studies (GWAS) of the signals of pig meat and carcass traits. Within this module, we constructed a TE-mediated gene regulatory network by adopting a unique multi-omics integration approach. This network highlighted several established candidate genes associated with muscle-relevant traits, including HES6, CHRNG, ACTC1, CHRND, MAMSTR, and PER2, as well as novel genes like ENSSSCG00000005518, ENSSSCG00000033601, and PIEZO2. These novel genes hold promise for regulating muscle-related traits in pigs. In summary, our research not only enhances the TE-centered dissection of the genetic basis underlying pork production traits, but also offers a general approach for constructing TE-mediated regulatory networks to study complex traits or diseases.

Understanding the mechanism of slow lithium ion (Li + ) transport kinetics in LiFePO 4 is not only practically important for high power density batteries but also fundamentally significant as a prototypical ion-coupled electron transfer process. Substantial evidence has shown that the slow ion transport kinetics originates from the coupled transfer between electrons and ions and the phase segregation of Li + . Combining a model Hamiltonian analysis and DFT calculations, we reveal that electrostatic interactions play a decisive role in coupled charge transfer and Li + segregation. The obtained potential energy surfaces prove that ion-electron coupled transfer is the optimal reaction pathway due to electrostatic attractions between Li + and e - (Fe 2+ ), while prohibitively large energy barriers are required for separate electron tunneling or ion hopping to overcome the electrostatic energy between the Li + -e - (Fe 2+ ) pair. The model reveals that Li + -Li + repulsive interaction in the [010] transport channels together with Li + -e - (Fe 2+ )-Li + attractive interaction along the [100] direction cause the phase segregation of Li + . It explains why the thermodynamically stable phase interface between Li-rich and Li-poor phases in LiFePO 4 is perpendicular to [010] channels., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Chronic kidney disease (CKD) is an inflammatory disease characterized by the deterioration of renal function, which imposes a significant burden on the healthcare system. In the recent decades, the ageing of the population and the increase of ozone pollution have accelerated. However, epidemiological associations between long-term ozone exposure and renal function in susceptible populations are understudied. In this study, we aimed to investigate the association of 1 y ozone exposure with renal function among the older adults in Xiamen City, China. We recruited 6024 eligible participants with a median age of 65.00 years, estimated their ozone exposure data, and collected questionnaires on demographic status and lifestyle factors as well as information on healthcare access. A generalized linear model was used to assess the association. An increase of 10 μg/m 3 of 1 y ozone exposure was negatively associated with the estimated glomerular filtration rate (eGFR) [-3.12 (95% CI: -4.76, -1.48)]. The associations were stronger in men, non-smokers, and those with hypertension or T2DM. Clinical indicators of high-density lipoprotein, low-density lipoprotein, triglycerides, and total cholesterol were the main mediators to regulate the ozone-renal function association. Our results suggested that long-term ozone exposure is a potential risk factor for renal function in Chinese middle-aged and elderly adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Copy number variations (CNVs) are crucial structural genomic variants affecting complex traits in humans and livestock animals. The current study was designed to conduct a comprehensive comparative copy number variation analysis among three breeds, Debao (DB), Baise (BS), and Warmblood (WB), with a specific focus on identifying genomic regions associated with miniature features in horses. Using whole-genome next-generation resequencing data, we identified 18,974 CNVs across 31 autosomes. Among the breeds, we found 4279 breed-specific CNV regions (CNVRs). Baise, Debao, and Warmblood displayed 2978, 986, and 895 distinct CNVRs, respectively, with 202 CNVRs shared across all three breeds. After removing duplicates, we obtained 1545 CNVRs from 26 horse genomes. Functional annotation reveals enrichment in biological functions, including antigen processing, cell metabolism, olfactory conduction, and nervous system development. Debao horses have 970 genes overlapping with CNVRs, possibly causing their small size and mountainous adaptations. We also found that the genes GHR, SOX9 , and SOX11 may be responsible for the miniature features of the Debao horse by analyzing their overlapping CNVRs. Overall, this study offers valuable insights into the widespread presence of CNVs in the horse genome. The findings contribute to mapping horse CNVs and advance research on unique miniature traits observed in the Debao horse.

Chikungunya virus (CHIKV) is a re-emerging mosquito-transmitted RNA virus causing joint and muscle pain. To better understand how CHIKV rewires the host cell and usurps host cell functions, we generated a systematic CHIKV-human protein-protein interaction map and revealed several novel connections that will inform further mechanistic studies. One of these novel interactions, between the viral protein E1 and STIP1 homology and U-box containing protein 1 (STUB1), was found to mediate ubiquitination of E1 and degrade E1 through the proteasome. Capsid associated with G3BP1, G3BP2 and AAA+ ​ATPase valosin-containing protein (VCP). Furthermore, VCP inhibitors blocked CHIKV infection, suggesting VCP could serve as a therapeutic target. Further work is required to fully understand the functional consequences of these interactions. Given that CHIKV proteins are conserved across alphaviruses, many virus-host protein-protein interactions identified in this study might also exist in other alphaviruses. Construction of interactome of CHIKV provides the basis for further studying the function of alphavirus biology., (Copyright © 2023 The Authors. Publishing services by Elsevier B.V. All rights reserved.)

Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex traits. However, these tools primarily rely on human or mouse data for training, limiting their performance when applied to other species. Furthermore, the limited exploration of many species, particularly in the case of livestock, has led to a scarcity of comprehensive and high-quality epigenetic data, posing challenges in developing reliable deep learning models for decoding their non-coding genomes. The cross-species prediction of the regulatory genome can be achieved by leveraging publicly available data from extensively studied organisms and making use of the conserved DNA binding preferences of transcription factors within the same tissue. In this study, we introduced DeepSATA, a novel deep learning-based sequence analyzer that incorporates the transcription factor binding affinity for the cross-species prediction of chromatin accessibility. By applying DeepSATA to analyze the genomes of pigs, chickens, cattle, humans, and mice, we demonstrated its ability to improve the prediction accuracy of chromatin accessibility and achieve reliable cross-species predictions in animals. Additionally, we showcased its effectiveness in analyzing pig genetic variants associated with economic traits and in increasing the accuracy of genomic predictions. Overall, our study presents a valuable tool to explore the epigenomic landscape of various species and pinpoint regulatory deoxyribonucleic acid (DNA) variants associated with complex traits.

In high-dimensional data analysis, the bi-level (or the sparse group) variable selection can simultaneously conduct penalization on the group level and within groups, which has been developed for continuous, binary, and survival responses in the literature. Zhou et al. (2022) (PMID: 35766061) has further extended it under the longitudinal response by proposing a quadratic inference function-based penalization method in gene-environment interaction studies. This study introduces "springer," an R package implementing the bi-level variable selection within the QIF framework developed in Zhou et al. (2022). In addition, R package "springer" has also implemented the generalized estimating equation-based sparse group penalization method. Alternative methods focusing only on the group level or individual level have also been provided by the package. In this study, we have systematically introduced the longitudinal penalization methods implemented in the "springer" package. We demonstrate the usage of the core and supporting functions, which is followed by the numerical examples and discussions. R package "springer" is available at https://cran.r-project.org/package=springer., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhou, Liu, Ren, Wang and Wu.)

Whole-genome genotyping methods are important for breeding. However, it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species. In our study, we accidently discovered that in adapter ligation-mediated PCR, the amplification by primer-template mismatched annealing (PTMA) along the genome could generate thousands of stable PCR products. Based on this observation, we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing (FBI-seq) using one specific primer, in which foreground genotyping is performed by primer-template perfect annealing (PTPA), while background genotyping employs PTMA. Unlike DNA arrays, multiple PCR, or genome target enrichments, FBI-seq requires little preliminary work for primer design and synthesis, and it is easily adaptable to different foreground genes and species. FBI-seq therefore provides a prolific, robust, and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the post-genomics era., (© 2022 The Authors. Journal of Integrative Plant Biology published by John Wiley & Sons Australia, Ltd on behalf of Institute of Botany, Chinese Academy of Sciences.)

Background: Corneal fluorescein sodium staining is a valuable diagnostic method for various ocular surface diseases. However, the examination results are highly dependent on the subjective experience of ophthalmologists., Objectives: To develop an artificial intelligence system based on deep learning to provide an accurate quantitative assessment of sodium fluorescein staining score and the size of cornea epithelial patchy defect., Design: A prospective study., Methods: We proposed an artificial intelligence system for automatically evaluating corneal staining scores and accurately measuring patchy corneal epithelial defects based on corneal fluorescein sodium staining images. The design incorporates two segmentation models and a classification model to forecast and assess the stained images. Meanwhile, we compare the evaluation findings from the system with ophthalmologists with varying expertise., Results: For the segmentation task of cornea boundary and cornea epithelial patchy defect area, our proposed method can achieve the performance of dice similarity coefficient (DSC) is 0.98/0.97 and Hausdorff distance (HD) is 3.60/8.39, respectively, when compared with the manually labeled gold standard. This method significantly outperforms the four leading algorithms (Unet, Unet++, Swin-Unet, and TransUnet). For the classification task, our algorithm achieves the best performance in accuracy, recall, and F1-score, which are 91.2%, 78.6%, and 79.2%, respectively. The performance of our developed system exceeds seven different approaches (Inception, ShuffleNet, Xception, EfficientNet&#95;B7, DenseNet, ResNet, and VIT) in classification tasks. In addition, three ophthalmologists were selected to rate corneal staining images. The results showed that the performance of our artificial intelligence system significantly outperformed the junior doctors., Conclusion: The system offers a promising automated assessment method for corneal fluorescein staining, decreasing incorrect evaluations caused by ophthalmologists' subjective variance and limited knowledge., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s), 2023.)

Mpox is caused by the mpox virus, which belongs to the Orthopoxvirus genus and Poxviridae family. Animal hosts, such as African rodents, mice, prairie dogs, and non-human primates, play important roles in the development and transmission of outbreaks. Laboratory animal infection experiments have demonstrated that some animals are susceptible to mpox virus. This review summarizes the current progress on the animal hosts for mpox virus. The surveillance of mpox virus in animal hosts will provide important insights into virus tracing, analysis of mutation evolutionary patterns, transmission mechanisms, and development of control measures., (© 2023 Wiley Periodicals LLC.)

The Bama Xiang pig (BM) is a unique pig species in Guangxi Province, China. Compared to other breeds of domestic pig, such as the Debao pig (DB), it is smaller in size, better in meat quality, resistant to rough feeding and strong in stress resistance. These unique advantages of Bama Xiang pigs make them of great edible value and scientific research value. However, the differences in muscle metabolites between Bama Xiang pigs (BM) and Debao pigs (DB) are largely unexplored. Here, we identified 214 differential metabolites between these two pig breeds by LC-MS. Forty-one such metabolites are enriched into metabolic pathways, and these metabolites correspond to 11 metabolic pathways with significant differences. In Bama pigs, the abundance of various metabolites such as creatine, citric acid, L-valine and hypoxanthine is significantly higher than in Debao pigs, while the abundance of other metabolites, such as carnosine, is significantly lower. Among these, we propose six differential metabolites: L-proline, citric acid, ribose 1-phosphate, L-valine, creatine, and L-arginine, as well as four potential differential metabolites (without the KEGG pathway), alanyl-histidine, inosine 2'-phosphate, oleoylcarnitine, and histidinyl hydroxyproline, as features for evaluating the meat quality of Bama pigs and for differentiating pork from Bama pigs and Debao pigs. This study provides a proof-of-concept example of distinguishing pork from different pig breeds at the metabolite level and sheds light on elucidating the biological processes underlying meat quality differences. Our pork metabolites data are also of great value to the genomics breeding community in meat quality improvement.

Objective: This study aimed at establishing a new model to predict malignant thyroid nodules using machine learning algorithms., Methods: A retrospective study was performed on 274 patients with thyroid nodules who underwent fine-needle aspiration (FNA) cytology or surgery from October 2018 to 2020 in Xianyang Central Hospital. The least absolute shrinkage and selection operator (lasso) regression analysis and logistic analysis were applied to screen and identified variables. Six machine learning algorithms, including Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Naive Bayes Classifier (NBC), Random Forest (RF), and Logistic Regression (LR), were employed and compared in constructing the predictive model, coupled with preoperative clinical characteristics and ultrasound features. Internal validation was performed by using 10-fold cross-validation. The performance of the model was measured by the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, F1 score, Shapley additive explanations (SHAP) plot, feature importance, and correlation of features. The best cutoff value for risk stratification was identified by probability density function (PDF) and clinical utility curve (CUC)., Results: The malignant rate of thyroid nodules in the study cohort was 53.2%. The predictive models are constructed by age, margin, shape, echogenic foci, echogenicity, and lymph nodes. The XGBoost model was significantly superior to any one of the machine learning models, with an AUC value of 0.829. According to the PDF and CUC, we recommended that 51% probability be used as a threshold for determining the risk stratification of malignant nodules, where about 85.6% of patients with malignant nodules could be detected. Meanwhile, approximately 89.8% of unnecessary biopsy procedures would be saved. Finally, an online web risk calculator has been built to estimate the personal likelihood of malignant thyroid nodules based on the best-performing ML-ed model of XGBoost., Conclusions: Combining clinical characteristics and features of ultrasound images, ML algorithms can achieve reliable prediction of malignant thyroid nodules. The online web risk calculator based on the XGBoost model can easily identify in real-time the probability of malignant thyroid nodules, which can assist clinicians to formulate individualized management strategies for patients., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Li, Hong, Fang, Liu, Liu, He, Li, Xu, Wang, Chen, Sun, Li, Kang and Yin.)

Adipocytes or fat cells play a vital role in the storage and release of energy in pigs, and many circular RNAs (circRNAs) have emerged as important regulators in various tissues and cell types in pigs. However, the spatio-temporal expression pattern of circRNAs between different adipose deposition breeds remains elusive. In this study, RNA sequencing (RNA-seq) produced transcriptome profiles of Western Landrace (lean-type) and Chinese Songliao black pigs (obese-type) with different thicknesses of subcutaneous fat tissues and were used to identify circRNAs involved in the regulation of adipogenesis. Gene expression analysis revealed 883 circRNAs, among which 26 and 11 circRNAs were differentially expressed between Landrace vs. Songliao pigs and high- vs. low-thickness groups, respectively. We also analyzed the interaction between circRNAs and microRNAs (miRNAs) and constructed their interaction network in adipogenesis; gene ontology classification and pathway analysis revealed two vital circRNAs, with the majority of their target genes enriched in biological functions such as fatty acids biosynthesis, fatty acid metabolism, and Wnt/TGF-β signaling pathways. These candidate circRNAs can be taken as potential targets for further experimental studies. Our results show that circRNAs are dynamically expressed and provide a valuable basis for understanding the molecular mechanism of circRNAs in pig adipose biology.

Bartonella is one of the noncore bacterial genera in the honey bee (Apis mellifera) gut. So far, only one species, Bartonella apis, has been described from the honey bee gut. Previous analyses based on the genomic information of isolates and metagenome-assembled genomes suggested the existence of multiple Bartonella species in the bee guts. Here, 10 strains were isolated and characterized from the gut of A. mellifera from Jilin Province, China. New isolates shared ＞95% 16S rRNA gene sequence similarity with other species of the genus Bartonella. Phylogenetic analysis revealed that new isolates clustered with other type strains of Bartonella, and the bee gut Bartonella could be classified into three clades. The in silico DDH and average nucleotide identity values between strains of different clusters from the honey bee gut are 29.1-32.5% and 87.6-89.3%, all below the recommended 70.0% and 95% cutoff points. Cells are Gram-staining-negative rods and can grow on the surface of Brain Heart Infusion agar plates supplemented with defibrinated sheep blood in an aerobic environment with 5% CO 2 at 35-37 °C. Strains from different species varied in both phenotypic and chemotaxonomic characterizations. Comparative genomic analysis indicated that B. choladocola had unique sets of genes encoding invasin, representing the potential for this species to both live as a gut symbiont and also as an erythrocytic pathogen. Thus, we propose two novel species Bartonella choladocola sp. nov. whose type strain is W8125 T (=JCM 35030 T  = ACCC 62057 T ), and Bartonella apihabitans sp. nov. whose type strain is W8097 T (=JCM 35029 T  = ACCC 62056 T )., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

Background: The genetic mechanisms that underlie phenotypic differentiation in breeding animals have important implications in evolutionary biology and agriculture. However, the contribution of cis-regulatory variants to pig phenotypes is poorly understood. Therefore, our aim was to elucidate the molecular mechanisms by which non-coding variants cause phenotypic differences in pigs by combining evolutionary biology analyses and functional genomics., Results: We obtained a high-resolution phased chromosome-scale reference genome with a contig N50 of 18.03 Mb for the Luchuan pig breed (a representative eastern breed) and profiled potential selective sweeps in eastern and western pigs by resequencing the genomes of 234 pigs. Multi-tissue transcriptome and chromatin accessibility analyses of these regions suggest that tissue-specific selection pressure is mediated by promoters and distal cis-regulatory elements. Promoter variants that are associated with increased expression of the lysozyme (LYZ) gene in the small intestine might enhance the immunity of the gastrointestinal tract and roughage tolerance in pigs. In skeletal muscle, an enhancer-modulating single-nucleotide polymorphism that is associated with up-regulation of the expression of the troponin C1, slow skeletal and cardiac type (TNNC1) gene might increase the proportion of slow muscle fibers and affect meat quality., Conclusions: Our work sheds light on the molecular mechanisms by which non-coding variants shape phenotypic differences in pigs and provides valuable resources and novel perspectives to dissect the role of gene regulatory evolution in animal domestication and breeding., (© 2022. The Author(s).)

Heterogeneous bubble nucleation is one of the most fundamental interfacial processes ranging from nature to technology. There is excellent evidence that surface topology is important in directing heterogeneous nucleation; however, deep understanding of the energetics by which nanoscale architectures promote nucleation is still challenging. Herein, we report a direct and quantitative measurement of single-bubble nucleation on a single silica nanoparticle within a microsized droplet using scanning electrochemical cell microscopy. Local gas concentration at nucleation is determined from finite element simulation at the corresponding faradaic current of the peak-featured voltammogram. It is demonstrated that the criteria gas concentration for nucleation first drops and then rises with increasing nanoparticle radius. An optimum nanoparticle radius around 10 nm prominently expedites the nucleation by facilitating the special topological nanoconfinements that consequently catalyze the nucleation. Moreover, the experimental result is corroborated by our theoretical calculations of free energy change based on the classic nucleation theory. This study offers insights into the impact of surface topology on heterogenous nucleation that have not been previously observed.

The present study aimed to evaluate the spectrum-effect relationships between high-performance liquid chromatography fingerprints and anti-inflammatory effects of Tetrastigma planicaule(Hook.)Gagnep. Chemical fingerprints of ten batches of Tetrastigma planicaule from various sources were obtained by HPLC. The anti-inflammatory activity was investigated by a model of ear swelling in mice caused by xylene and a model of cotton pellet granuloma. Hierarchical cluster analysis (HCA) results showed that all the samples were clustered into four categories, which was basically consistent with the principal component analysis (PCA) results. The results of the joint grey relational analysis (GRA) and partial least squares regression analysis (PLSR) showed that peaks 1, 2 and 12 were positively correlated with the anti-acute inflammatory effect (ear swelling) in mice, and peaks 3, 5, 6 and 11 were positively correlated with the anti-chronic inflammatory effect (cotton pellet granuloma) in mice. The anti-inflammatory effect of Tetrastigma planicaule is the result of the synergistic effect of multiple components, which provides a basis for further exploring the anti-inflammatory substances and quality evaluation of the herb.

Background: The vital-sign monitoring strategy of patients with acute aortic dissection in the emergency department is mainly based on traditional experience. This study attempts to explore the significance of the national early warning score (NEWS) in monitoring the condition of patients with acute aortic dissection during emergency observation and to provide evidence for emergency nurses in optimal and scientific monitoring of patients., Methods: The case-control method was used to continuously enrol patients with acute aortic dissection who had been in the emergency department; the STROBE checklist was used in this process. Based on patients' clinical deterioration, they were divided into two groups: clinical deterioration and non-clinical deterioration. The NEWS at each time point was compared by independent-samples t-test, and the predictive power of NEWS was evaluated according to the area under the receiver operating characteristic curve., Results: A total of 290 patients with acute aortic dissection were included: 46 patients showed clinical deterioration and 244 did not. There were significant differences in the NEW scores of the two groups at admission time and at 12, 8, 4 and 0.5 h before clinical deterioration. The NEW scores of the clinical deterioration group showed an upward trend, while the non-clinical deterioration group showed a relatively stable trend. The NEWS can be used to predict the occurrence of clinical deterioration earlier at 4 h before clinical deterioration. Simultaneously, the patient's respiration rate and SpO 2 had better predictive performance than other vital signs., Conclusion: The NEWS can be used to triage patients with acute aortic dissection admitted to the emergency department. Continuous use of the NEWS for monitoring can play a vital role in early warning of clinical deterioration in patients with acute aortic dissection. In clinical care, attention should also be paid when patients with acute aortic dissection have abnormal respiration rate and SpO 2 ., (© 2021 John Wiley & Sons Ltd.)

Aqueous zinc-ion batteries (ZIBs) are receiving a continuously increasing attention for the flexible and wearable electronics, due to their non-toxicity, non-flammability, and low-cost features. The development of high-performance flexible cathodes is of great significance to the development of flexible ZIBs. In this work, the flexible electrode of three-dimensional (3D) interconnected ultrathin MnO 2 nanosheets on carbon cloth (CC@MnO 2 ) coated with Ti 3 C 2 T x MXene (CC@MnO 2 @MXene) is prepared by electrodeposition and dipping methods, in which CC@MnO 2 is put into MXene dispersion for impregnation treatment to make the CC@MnO 2 fibers wrapped with MXene completely. The results show that the coating of MXene improves the conductivity of the composite, and the interface between MXene and MnO 2 provides more active sites. Therefore, CC@MnO 2 @MXene-10 electrode as the cathode of zinc ion battery provides high charge storage performance (517.0 mAh g -1 at 0.1 A g -1 ), excellent cycling stability (80.6 mAh g -1 after 800 cycles at 1 A g -1 ) and excellent energy density (701.3 Wh kg -1 at 133.8 W kg -1 ). Finally, flexible quasi-solid battery based on CC@MnO 2 @MXene composite as cathode was assembled, and the flexible electrodes show potential for application., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Myogenesis is a central step in prenatal myofiber formation, postnatal myofiber hypertrophy, and muscle damage repair in adulthood. RNA-Seq technology has greatly helped reveal the molecular mechanism of myogenesis, but batch effects in different experiments inevitably lead to misinterpretation of differentially expressed genes (DEGs). We previously applied the robust rank aggregation (RRA) method to effectively circumvent batch effects across multiple RNA-Seq datasets from 3T3-L1 cells. Here, we also used the RRA method to integrate nine RNA-Seq datasets from C2C12 cells and obtained 3140 robust DEGs between myoblasts and myotubes, which were then validated with array expression profiles and H3K27ac signals. The upregulated robust DEGs were highly enriched in gene ontology (GO) terms related to muscle cell differentiation and development. Considering that the cooperative binding of transcription factors (TFs) to enhancers to regulate downstream gene expression is a classical epigenetic mechanism, differentially expressed TFs (DETFs) were screened, and potential novel myogenic factors (MAF, BCL6, and ESR1) with high connection degree in protein-protein interaction (PPI) network were presented. Moreover, KLF5 cooperatively binds with the three key myogenic factors (MYOD, MYOG, and MEF2D) in C2C12 cells. Motif analysis speculates that the binding of MYOD and MYOG is KLF5-independent, while MEF2D is KLF5-dependent. It was revealed that KLF5-binding sites could be exploited to filter redundant MYOD-, MYOG-, and MEF2D-binding sites to focus on key enhancers for myogenesis. Further functional annotation of KLF5-binding sites suggested that KLF5 may regulate myogenesis through the PI3K-AKt signaling pathway, Rap1 signaling pathway, and the Hippo signaling pathway. In general, our study provides a wealth of untapped candidate targets for myogenesis and contributes new insights into the core regulatory mechanisms of myogenesis relying on KLF5-binding signal.

Metformin, a traditional first-line pharmacological treatment for type 2 diabetes, has recently been shown to have anti-cancer effects on hepatocellular carcinoma (HCC). However, the molecular mechanism underlying the anti-tumor activity of metformin remains unclear. The Sonic hedgehog (Shh) signaling pathway is closely associated with the initiation and progression of HCC. Therefore, the aim of the current study was to investigate the effects of metformin on the biological behavior of HCC and the underlying functional mechanism of metformin in the Shh pathway. HCC was induced in HepG2 cells using recombinant human Shh (rhShh). The effects of metformin on proliferation and metastasis were evaluated using in vitro proliferation, wound healing, and invasion assays. The mRNA and protein expression levels of proteins related to the Shh pathway were measured using western blotting, quantitative PCR, and immunofluorescence staining. Metformin inhibited rhShh-induced proliferation and metastasis. Furthermore, metformin decreased the mRNA and protein expression of Shh pathway components, including Shh, Ptch, Smo, and Gli-1. Silencing of AMPK in the presence of metformin revealed that metformin exerted its inhibitory effects via AMPK. Our findings demonstrate that metformin suppresses the migration and invasion of HepG2 cells via AMPK-mediated inhibition of the Shh pathway.

We introduce interep , an R package for interaction analysis of repeated measurement data with high-dimensional main and interaction effects. In G × E interaction studies, the forms of environmental factors play a critical role in determining how structured sparsity should be imposed in the high-dimensional scenario to identify important effects. Zhou et al. (2019) (PMID: 31816972) proposed a longitudinal penalization method to select main and interaction effects corresponding to the individual and group structure, respectively, which requires a mixture of individual and group level penalties. The R package interep implements generalized estimating equation (GEE)-based penalization methods with this sparsity assumption. Moreover, alternative methods have also been implemented in the package. These alternative methods merely select effects on an individual level and ignore the group-level interaction structure. In this software article, we first introduce the statistical methodology corresponding to the penalized GEE methods implemented in the package. Next, we present the usage of the core and supporting functions, which is followed by a simulation example with R codes and annotations. The R package interep is available at The Comprehensive R Archive Network (CRAN).

The microstructural features and charge-potential relation of an electric double layer (EDL) at a stepped Pt(553)/water interface are investigated using ab initio molecular dynamics simulation. The results indicate that the chemisorbed O-down water molecules gather at the (110) step sites, while the (111) terrace sites are covered by the H-down water molecules, which greatly weakens the push-back effect of interface water on the spillover electrons of the stepped surface and, therefore, results in a much more positive potential of zero charge (PZC) than the extended low-index Pt surfaces. It is further revealed that around the PZC, the change in the surface charge density is dominated by the change in the coverage of chemisorbed water molecules, while EDL charging is the main cause of the change in the surface charge density at potential away from the PZC, thus leading to an S-shaped charge-potential relation and a maximum interface capacitance around PZC. Our results make up for the current lack of the atomic-scale understanding of the EDL microstructures and charge-potential relation on the real electrode surfaces with plentiful step and defect sites.

Growth factors (GF), with the activity of stimulating cell growth, play a significant role in biology, medicine, and exercise physiology. In the process of exercise, human tissues are impacted, making cells suffer damage. Growth factor can accelerate the repair of damaged cells and regulate the synthesis of protein, so biological preparations of growth factors can be added to traditional therapies. A combination of growth factor biologics and conventional therapies may improve the efficiency of injury repair, but growth factor biologics may not produce any results. The feasibility of growth factor biologics in the treatment of motor injury was discussed. The research have shown that: 1) GF biological agent therapy is a very promising treatment for motor injury, which is based on the power of autologous growth factor (GFs) to accelerate tissue healing, promote muscle regeneration, increase angiogenesis, reduce fibrosis, and make the muscle injury rapid recovery. 2) There are various methods for delivering the higher dose of GF to the injured tissue, but most of them depend on the platelet release of GF. At the site of injury, there are several ways to deliver higher doses of GF to the injured tissue. 3) At present, the inhibition of GF is mainly through signal transduction inhibitors and inhibition of transcription factor production. 4) Pattern of GF during wound repair: GF directly regulates many key steps of normal wound repair, including inflammatory cell chemotaxis, division and proliferation of fibroblasts, keratinocytes and vascular endothelial cells, formation of new blood vessels, and synthesis and degradation of intercellular substances. 5) When GF promotes chronic wound healing, in most cases, certain GF can be used targeted only when in vivo regulation still cannot meet the need for repair., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Tan, Li, Liu, Zhu and Shao.)