Unraveling the important role of comammox Nitrospira to nitrification in the coastal aquaculture system.

Increasing nitrogen (N) input to coastal ecosystems poses a serious environmental threat. It is important to understand the responses and feedback of N removal microbial communities, particularly nitrifiers including the newly recognized complete ammonia-oxidizers (comammox), to improve aquaculture sustainability. In this study, we conducted a holistic evaluation of the functional communities responsible for nitrification by quantifying and sequencing the key functional genes of comammox Nitrospira-amoA, AOA-amoA, AOB-amoA and Nitrospira-nxrB in fish ponds with different fish feeding levels and evaluated the contribution of nitrifiers in the nitrification process through experiments of mixing pure cultures. We found that higher fish feeding dramatically increased N-related concentration, affecting the nitrifying communities. Compared to AOA and AOB, comammox Nitrospira and NOB were more sensitive to environmental changes. Unexpectedly, we detected an equivalent abundance of comammox Nitrospira and AOB and observed an increase in the proportion of clade A in comammox Nitrospira with the increase in fish feeding. Furthermore, a simplified network and shift of keystone species from NOB to comammox Nitrospira were observed in higher fish-feeding ponds. Random forest analysis suggested that the comammox Nitrospira community played a critical role in the nitrification of eutrophic aquaculture ponds (40-70 µM). Through the additional experiment of mixing nitrifying pure cultures, we found that comammox Nitrospira is the primary contributor to the nitrification process at 200 µM ammonium. These results advance our understanding of nitrifying communities and highlight the importance of comammox Nitrospira in driving nitrification in eutrophic aquaculture systems.

Inactivation of mitochondrial MUL1 E3 ubiquitin ligase deregulates mitophagy and prevents diet-induced obesity in mice.

Obesity is a growing epidemic affecting millions of people worldwide and a major risk factor for a multitude of chronic diseases and premature mortality. Accumulating evidence suggests that mitochondria have a profound role in diet-induced obesity and the associated metabolic changes, but the molecular mechanisms linking mitochondria to obesity remain poorly understood. Our studies have identified a new function for mitochondrial MUL1 E3 ubiquitin ligase, a protein known to regulate mitochondrial dynamics and mitophagy, in the control of energy metabolism and lipogenesis. Genetic deletion of Mul1 in mice impedes mitophagy and presents a metabolic phenotype that is resistant to high-fat diet (HFD)-induced obesity and metabolic syndrome. Several metabolic and lipidomic pathways are perturbed in the liver and white adipose tissue (WAT) of Mul1(-/-) animals on HFD, including the one driven by Stearoyl-CoA Desaturase 1 (SCD1), a pivotal regulator of lipid metabolism and obesity. In addition, key enzymes crucial for lipogenesis and fatty acid oxidation such as ACC1, FASN, AMPK, and CPT1 are also modulated in the absence of MUL1. The concerted action of these enzymes, in the absence of MUL1, results in diminished fat storage and heightened fatty acid oxidation. Our findings underscore the significance of MUL1-mediated mitophagy in regulating lipogenesis and adiposity, particularly in the context of HFD. Consequently, our data advocate the potential of MUL1 as a therapeutic target for drug development in the treatment of obesity, insulin resistance, NAFLD, and cardiometabolic diseases.

Identification of molecular subtypes based on chromatin regulator-related genes and experimental verification of the role of ASCL1 in conferring chemotherapy resistance to breast cancer.

Objective: The aim of this study was to identify the molecular subtypes of breast cancer based on chromatin regulator-related genes. Methods: The RNA sequencing data of The Cancer Genome Atlas-Breast Cancer cohort were obtained from the official website, while the single-cell data were downloaded from the Gene Expression Omnibus database (GSE176078). Validation was performed using the Molecular Taxonomy of Breast Cancer International Consortium dataset. Furthermore, the immune characteristics, tumor stemness, heterogeneity, and clinical characteristics of these molecular subtypes were analyzed. The correlation between chromatin regulators and chemotherapy resistance was examined in vitro using the quantitative real-time polymerase chain reaction (qRT-PCR) and Cell Counting Kit-8 (CCK8) assays. Results: This study identified three stable molecular subtypes with different prognostic and pathological features. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction analyses revealed that the differentially expressed genes were associated with disease processes, such as mitotic nuclear division, chromosome segregation, condensed chromosome, and specific chromosome region. The T stage and subtypes were correlated with the clinical features. Tumor heterogeneity (mutant-allele tumor heterogeneity, tumor mutational burden, purity, and homologous recombination deficiency) and tumor stemness (RNA expression-based stemness score, epigenetically regulated RNA expression-based stemness score, DNA methylation-based stemness score, and epigenetically regulated DNA methylation-based stemness score) significantly varied between the three subtypes. Furthermore, Western blotting, qRT-PCR, and CCK8 assays demonstrated that the expression of ASCL1 was positively correlated with chemotherapy resistance in breast cancer. Conclusion: This study identified the subtypes of breast cancer based on chromatin regulators and analyzed their clinical features, gene mutation status, immunophenotype, and drug sensitivity. The results of this study provide effective strategies for assessing clinical prognosis and developing personalized treatment strategies.

Establishment of a real-time fluorescent quantitative PCR detection method and phylogenetic analysis of BoAHV-1.

BACKGROUND: Infectious bovine rhinotracheitis (IBR), caused by Bovine alphaherpesvirus-1 (BoAHV-1), is an acute, highly contagious disease primarily characterized by respiratory tract lesions in infected cattle. Due to its severe pathological damage and extensive transmission, it results in significant economic losses in the cattle industry. Accurate detection of BoAHV-1 is of paramount importance. In this study, we developed a real-time fluorescent quantitative PCR detection method for detecting BoAHV-1 infections. Utilizing this method, we tested clinical samples and successfully identified and isolated a strain of BoAHV-1.1 from positive samples. Subsequently, we conducted a genetic evolution analysis on the isolate strain's gC, TK, gG, gD, and gE genes. RESULTS: The study developed a real-time quantitative PCR detection method using SYBR Green II, achieving a detection limit of 7.8 × 101 DNA copies/µL. Specificity and repeatability analyses demonstrated no cross-reactivity with other related pathogens, highlighting excellent repeatability. Using this method, 15 out of 86 clinical nasal swab samples from cattle were found to be positive (17.44%), which was higher than the results obtained from conventional PCR detection (13.95%, 12/86). The homology analysis and phylogenetic tree analysis of the gC, TK, gG, gD, and gE genes of the isolated strain indicate that the JL5 strain shares high homology with the BoAHV-1.1 reference strains. Amino acid sequence analysis revealed that gC, gE, and gG each had two amino acid mutations, while the TK gene had one synonymous mutation and one H to Y mutation, with no amino acid mutations observed in the gD gene. Phylogenetic tree analysis indicated that the JL5 strain belongs to the BoAHV-1.1 genotype and is closely related to American strains such as C33, C14, and C28. CONCLUSIONS: The established real-time fluorescent quantitative PCR detection method exhibits good repeatability, specificity, and sensitivity. Furthermore, genetic evolution analysis of the isolated BoAHV-1 JL-5 strain indicates that it belongs to the BoAHV-1.1 subtype. These findings provide a foundation and data for the detection, prevention, and control Infectious Bovine Rhinotracheitis.

Surfactant Self-Assembly Enhances Tribopositivity of Stretchable Ionic Conductors for Wearable Energy Harvesting and Motion Sensing.

Boosting stretchability and electric output is critical for high-performance wearable triboelectric nanogenerators (TENG). Herein, for the first time, we propose a new approach for tuning the composition of surface functional groups through surfactant self-assembly to improve the tribopositivity, where the assembly increases the transferred charge density and the relative permittivity of water polyurethane (WPU). Incorporating bis(trifluoromethanesulfonyl)imide (TFSI-) and alkali metal ions into a mixture of WPU and the surfactant forms a stretchable film that simultaneously functions as positive tribolayer and electrode, preventing the conventional detachment of tribolayer and electrode in long term usage. Further the introduction of surfactant and alkali metal ions in WPU forms a strong crosslinking network. Resultantly, the conductivity of the crosslinked film reaches 3.3 × 10-3 mS cm-1 while the elongation at break reaches 362%, which are 4.8×104-fold and 1.3-fold higher than pristine WPU, respectively. Moreover, the surfactant self-assembly impedes the adverse impact of the fluorine-containing groups on tribopositivity. The self-assembled and LiTFSI-doped WPU-based TENG generates an open circuit voltage of 120 V, a short circuit current of 7.5 µA and a transfer charge of 62 nC, representing a 4-fold increase compared to LiTFSI-doped WPU-based TENG. Consequently, the charge density reaches 155 µC m-2, being the highest recorded for WPU-based and stretchable ionic conductive TENG. This work introduces a novel approach for boosting the output charge density while avoiding the adverse effect of ionic salt in solid conductors through a universal surfactant self-assembly strategy, which can be extended to other materials, such as polyvinyl alcohol. Further, the device was used to monitor and harvest the kinetic energy of human body motion. This article is protected by copyright. All rights reserved.

Effects of virtual reality OSCE on nursing students' education: a study protocol for systematic review and meta-analysis.

INTRODUCTION: Virtual objective structured clinical examination (OSCE) has been shown to influence the performance of nursing students. However, its specific effects, particularly students' competence, stress, anxiety, confidence, satisfaction with virtual reality OSCE and examiners' satisfaction, remain unclear. METHOD AND ANALYSIS: This study aims to assess the effects of virtual reality OSCE on nursing students' education. The study follows the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol guidelines. A literature search is performed on electronic databases, namely, PubMed, Web of Science, CINAHL, EBSCO, EMBASE and the Cochrane Library. The inclusion criteria adhere to the PICOS principle, encompassing nursing students, including those studying in school and those engaged in hospital internship. This review includes studies on the use of virtual reality OSCE as an assessment tool, compared with traditional clinical examinations, such as in-person OSCE. The outcome assessments encompass (1) competence, (2) stress, (3) anxiety, (4) confidence, (5) student satisfaction with virtual reality OSCE and (6) examiners' satisfaction. These studies are designed as randomised controlled trials (RCTs) or quasi-experimental research. The search time is from the inception of each database to 30 June 2023, without language restriction. Studies for inclusion are screened by two reviewers for data extraction dependently. Any dispute is resolved through discussion. Unresolved disputes are decided by consulting a third author. For the risk of bias (ROB) assessment, the Cochrane ROB tool for RCTs and the risk of bias in non-randomised studies of intervention tool are used. Moreover, RevMan V.5.3 is used for meta-analysis. ETHICS AND DISSEMINATION: This study protocol does not include any clinical research and thus does not require ethical approval. Research findings are published in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023437685.

Identifying potential drug targets for keloid: A Mendelian randomization study.

Keloids are a skin fibrosis disease characterized by troublesome symptoms, a varying degree of recurrence and inevitable side effects from treatments. Thus, identifying their drug targets is necessary. A two-sample MR analysis was conducted using proteins from the intersection of the deCODE database and "The Druggable Genome and Support for Target Identification and Validation in Drug Development" as the exposure variable. The outcome variable was based on recently published GWAS of keloids. SMR and colocalization analysis was employed to distinguish pleiotropy from linkage. Candidate targets underwent drug target analysis. The primary findings were validated through scRNA-seq data, Western Blot and immunofluorescence staining on keloids. Seven proteins were identified as potential drug targets for keloids. Among these proteins, HHIP, NTM, KLKB1, and CRIPTO showed positive correlations with keloids, while PLXNC1, SCG3 and PDGF-D exhibited negative correlations. Combined with the scRNA-seq data, NTM, PLXNC1, and PDGF-D were found highly expressed in the fibroblasts. NTM showed a significant increase in keloids as compared to normal scars. In accordance with the analysis, higher levels of protein expression of NTM in keloids compared to normal skin was observed. The identified proteins may be appealing drug targets for keloids treatment with a special emphasis on NTM.

Protein of yak milk residue: Structure, functionality, and the effects on the quality of non-fat yogurt.

The purpose of this study was to compare the structural and functional of protein from yak milk residue, which collected from different elevations (MRP1 and MRP2) in Tibet, as well as their potential for enhancing the quality of non-fat yogurt. The results showed that MRP1 exhibited higher levels of ß-sheet, turbidity, particle size, and gel properties. MRP2 had better flexibility, emulsification, foaming, water/oil absorption capacity. The addition of MRP1 (3%) could improve texture and sensory properties of yogurt. Although MRP2 yogurt had higher hardness, gumminess, chewiness and water holding capacity, poor mouthfeel. Rheological test showed that MRPs yogurt exhibited typical gel-like and shear-thinning behavior. Moreover, the fortification of non-fat yogurts with MRP1 brought the formation of larger protein clusters with a more tightly knit network of smaller pores. These results indicate that MRP1 can be used as a fat substitute to improve the quality of non-fat yogurt.

Hetero Diels-Alder reactions of isolable N-borylenamines.

A new strategy for N-borylenamines by reaction of 2-alkynyl benzyl azides with B(C6F5)3 was developed. This novel 1,3-carboboration reaction proceeded via a 5-exo-dig cyclization/formal 1,1-carboboration/B(C6F5)2 shift reaction sequence. Additionally, N-borylenamines can undergo hetero Diels-Alder (HDA) reactions with a variety of dienophiles. Our results are an attractive complement to HDA reactions.

Impact of Health Education Based on Protective Motivation Theory on the Mood State, Cancer-Related Fatigue, and Hope Level of Gastric Cancer Patients.

Background: Gastric cancer patients often feel physically tired and weak, lacking confidence and enthusiasm for relevant treatments. We aimed to explore the impacts of health education based on the theory of protective motivation on the emotional state, cancer-related fatigue, and hope levels of gastric cancer patients. Methods: A total of 160 gastric cancer patients admitted to the Sanmenxia Central Hospital, Henan, China, from May 2019 to March 2022 were selected as subjects. The control group (n=80) received routine health education, while the observation group (n=80) received health education based on the theory of protective motivation. Intervention evaluations included the Morisky medication compliance score, Plain Mood State Scale (POMS), Cancer Fatigue Scale (CFS), Herth Hope Scale (HHI), and Simple Health Survey Scale (SF-36). Results: After intervention, both groups showed an improvement in Morisky's medication compliance score, HHI scale score, and SF-36 scale score (all P<0.05). Additionally, the observation group exhibited greater improvement than the control group (P<0.05). There were no significant differences in POMS scale score and CFS scale score between the two groups before and after intervention. However, after intervention, both groups experienced a decrease in POMS scale score and CFS scale score (both P<0.05), with the observation group showing a more significant decrease compared to the control group (P<0.05). Conclusion: Health education based on the theory of protective motivation effectively enhances the mood state, reduces cancer-related fatigue, and increases hope levels among gastric cancer patients, thereby improving their medication compliance and overall quality of life.

Site-Specifically Modified Peptide Inhibitors of Protein Tyrosine Phosphatase 1B and T-Cell Protein Tyrosine Phosphatase with Enhanced Stability and Improved In Vivo Long-Acting Activity.

Protein tyrosine phosphatase 1B (PTP1B) and TC-PTP can function in a coordinated manner to regulate diverse biological processes including insulin and leptin signaling, T-cell activation, and tumor antigen presentation, which makes them potential targets for several therapeutic applications. We have previously demonstrated that the lipidated BimBH3 peptide analogues were a new class of promising PTP1B inhibitors with once-weekly antidiabetic potency. Herein, we chemically synthesized two series of BimBH3 analogues via site-specific modification and studied their structure-activity relationship. The screened analogues S2, S6, A2-14, A2-17, A2-20, and A2-21 exhibited an improved PTP1B/TC-PTP dual inhibitory activity and achieved good stability in the plasma of mice and dogs, which indicated long-acting potential. In mouse models of type 2 diabetes mellitus (T2DM), the selected analogues S6, S7, A2-20, and A2-21 with an excellent target activity and plasma stability generated once-weekly therapeutic potency for T2DM at lower dosage (0.5 µmol/kg). In addition, evidence was provided to confirm the cell permeability and targeted enrichment of the BimBH3 analogues. In summary, we report here that site-specific modification and long fatty acid conjugation afforded cell-permeable peptidomimetic analogues of BimBH3 with enhanced stability, in vivo activity, and long-acting pharmacokinetic profile. Our findings could guide the further optimization of BimBH3 analogues and provide a proof-of-concept for PTP1B/TC-PTP targeting as a new therapeutic approach for T2DM, which may facilitate the discovery and development of alternative once-weekly anti-T2DM drug candidates.

Physician and Artificial Intelligence Chatbot Responses to Cancer Questions From Social Media.

Importance: Artificial intelligence (AI) chatbots pose the opportunity to draft template responses to patient questions. However, the ability of chatbots to generate responses based on domain-specific knowledge of cancer remains to be tested. Objective: To evaluate the competency of AI chatbots (GPT-3.5 [chatbot 1], GPT-4 [chatbot 2], and Claude AI [chatbot 3]) to generate high-quality, empathetic, and readable responses to patient questions about cancer. Design, Setting, and Participants: This equivalence study compared the AI chatbot responses and responses by 6 verified oncologists to 200 patient questions about cancer from a public online forum. Data were collected on May 31, 2023. Exposures: Random sample of 200 patient questions related to cancer from a public online forum (Reddit r/AskDocs) spanning from January 1, 2018, to May 31, 2023, was posed to 3 AI chatbots. Main Outcomes and Measures: The primary outcomes were pilot ratings of the quality, empathy, and readability on a Likert scale from 1 (very poor) to 5 (very good). Two teams of attending oncology specialists evaluated each response based on pilot measures of quality, empathy, and readability in triplicate. The secondary outcome was readability assessed using Flesch-Kincaid Grade Level. Results: Responses to 200 questions generated by chatbot 3, the best-performing AI chatbot, were rated consistently higher in overall measures of quality (mean, 3.56 [95% CI, 3.48-3.63] vs 3.00 [95% CI, 2.91-3.09]; P < .001), empathy (mean, 3.62 [95% CI, 3.53-3.70] vs 2.43 [95% CI, 2.32-2.53]; P < .001), and readability (mean, 3.79 [95% CI, 3.72-3.87] vs 3.07 [95% CI, 3.00-3.15]; P < .001) compared with physician responses. The mean Flesch-Kincaid Grade Level of physician responses (mean, 10.11 [95% CI, 9.21-11.03]) was not significantly different from chatbot 3 responses (mean, 10.31 [95% CI, 9.89-10.72]; P > .99) but was lower than those from chatbot 1 (mean, 12.33 [95% CI, 11.84-12.83]; P < .001) and chatbot 2 (mean, 11.32 [95% CI, 11.05-11.79]; P = .01). Conclusions and Relevance: The findings of this study suggest that chatbots can generate quality, empathetic, and readable responses to patient questions comparable to physician responses sourced from an online forum. Further research is required to assess the scope, process integration, and patient and physician outcomes of chatbot-facilitated interactions.

Response of microbial community composition and function to land use in mining soils of Xikuang Mountain in Hunan.

Nine land types in the northern mining area (BKQ) (mining land, smelting land, living area), the old mining area (LKQ) (whole-ore heap, wasteland, grassland), and southern mining area (NKQ) (grassland, shrubs, farmland) of Xikuang Mountain were chosen to explore the composition and functions of soil bacterial communities under different habitats around mining areas. The composition and functions of soil bacterial communities were compared among the sampling sites using 16S rRNA high-throughput sequencing and metagenomic sequencing. α diversity analysis showed the soil bacterial diversity and abundance in the old mining area were significantly higher than those in the northern mining area. ß diversity analysis demonstrated that the soil bacterial community composition was highly similar among different vegetation coverages in the southern mining area. Microbial community function analysis showed the annotated KEGG function pathways and eggNOG function composition were consistent between the grassland of the old mining area and the grassland of the southern mining area. This study uncovers the soil bacterial community composition and functions among different habitats in the mining areas of Xikuang Mountain and will underlie soil ecosystem restoration in different habitats under heavy metal pollution around the mining areas there.

From Organelle Morphology to Whole-Plant Phenotyping: A Phenotypic Detection Method Based on Deep Learning.

The analysis of plant phenotype parameters is closely related to breeding, so plant phenotype research has strong practical significance. This paper used deep learning to classify Arabidopsis thaliana from the macro (plant) to the micro level (organelle). First, the multi-output model identifies Arabidopsis accession lines and regression to predict Arabidopsis's 22-day growth status. The experimental results showed that the model had excellent performance in identifying Arabidopsis lines, and the model's classification accuracy was 99.92%. The model also had good performance in predicting plant growth status, and the regression prediction of the model root mean square error (RMSE) was 1.536. Next, a new dataset was obtained by increasing the time interval of Arabidopsis images, and the model's performance was verified at different time intervals. Finally, the model was applied to classify Arabidopsis organelles to verify the model's generalizability. Research suggested that deep learning will broaden plant phenotype detection methods. Furthermore, this method will facilitate the design and development of a high-throughput information collection platform for plant phenotypes.

Efficacy and safety of CO2 fractional laser versus Er:YAG fractional laser in the treatment of atrophic acne scar: A meta-analysis and systematic review.

BACKGROUND: To date, a consensus on the relative efficacy and safety of CO2 fractional laser versus erbium-doped yttrium aluminum garnet (Er:YAG) fractional laser treatments for atrophic acne scars has not been reached. This meta-analysis aims to systematically assess and compare their effectiveness and safety in clinical practice. METHODS: For this meta-analysis, we conducted comprehensive searches in Pubmed, Embase, and Cochrane databases, covering publications from their inception up to August 2023. Our focus was on studies comparing fractional CO2 laser with Er:YAG fractional laser treatments for atrophic acne scars. We excluded duplicate publications, research lacking full-text access, incomplete data, or cases where data extraction was not feasible. Additionally, animal experiments, reviews, and systematic reviews were not considered. Data analysis was performed using STATA 15.1. RESULTS: Eight studies (seven randomized controlled trials (RCTs) and a retrospective study) were included in this meta-analysis. The sample size ranged from 28 to 106 with a total of 418 patients, including 210 in the CO2 fractional group and 208 in Er:YAG fractional group. The pooled results showed that the effective rate of CO2 fractional laser in treating atrophic acne scar was significantly higher than that of Er:YAG fractional laser (OR = 1.81, 95% CI: 1.08-3.01) and the downtime of CO2 fractional laser in treating atrophic acne scar was significantly shorter than that of Er:YAG fractional laser (Weighted Mean Difference (WMD) = -2.11, 95% CI: -3.11 to -1.10). In addition, VAS of CO2 fractional laser in treating atrophic acne scar was significantly higher than that of Er:YAG fractional laser (WMD = 1.77, 95% CI: 1.32-2.21) and the duration of erythema of CO2 fractional laser in treating atrophic acne scar was significantly longer than that of Er:YAG fractional laser (WMD = 1.85, 95% CI: 1.63-2.07). However, there was no significant difference in the duration of pain and incidence of PIHbetween CO2 fractional laser and of Er:YAG fractional laser. CONCLUSION: When it comes to treating atrophic acne scars, CO2 fractional laser demonstrates superior efficacy and leads to shorter downtime. However, it is important to note that CO2 fractional laser treatments tend to result in higher pain intensity and may carry a higher risk of post-treatment pigmentation compared to Er:YAG fractional laser procedures.

Integrative analyses of bulk and single-cell transcriptomics reveals the infiltration and crosstalk of cancer-associated fibroblasts as a novel predictor for prognosis and microenvironment remodeling in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant neoplasm and characterized by desmoplastic matrix. The heterogeneity and crosstalk of tumor microenvironment remain incompletely understood. METHODS: To address this gap, we performed Weighted Gene Co-expression Network Analysis (WGCNA) to identify and construct a cancer associated fibroblasts (CAFs) infiltration biomarker. We also depicted the intercellular communication network and important receptor-ligand complexes using the single-cell transcriptomics analysis of tumor and Adjacent normal tissue. RESULTS: Through the intersection of TCGA DEGs and WGCNA module genes, 784 differential genes related to CAFs infiltration were obtained. After a series of regression analyses, the CAFs score was generated by integrating the expressions of EVA1A, APBA2, LRRTM4, GOLGA8M, BPIFB2, and their corresponding coefficients. In the TCGA-CHOL, GSE89748, and 107,943 cohorts, the high CAFs score group showed unfavorable survival prognosis (p < 0.001, p = 0.0074, p = 0.028, respectively). Additionally, a series of drugs have been predicted to be more sensitive to the high-risk group (p < 0.05). Subsequent to dimension reduction and clustering, thirteen clusters were identified to construct the single-cell atlas. Cell-cell interaction analysis unveiled significant enhancement of signal transduction in tumor tissues, particularly from fibroblasts to malignant cells via diverse pathways. Moreover, SCENIC analysis indicated that HOXA5, WT1, and LHX2 are fibroblast specific motifs. CONCLUSIONS: This study reveals the key role of fibroblasts - oncocytes interaction in the remodeling of the immunosuppressive microenvironment in intrahepatic cholangiocarcinoma. Subsequently, it may trigger cascade activation of downstream signaling pathways such as PI3K-AKT and Notch in tumor, thus initiating tumorigenesis. Targeted drugs aimed at disrupting fibroblasts-tumor cell interaction, along with associated enrichment pathways, show potential in mitigating the immunosuppressive microenvironment that facilitates tumor progression.

Hydrolyzed egg yolk peptide prevented osteoporosis by regulating Wnt/ß-catenin signaling pathway in ovariectomized rats.

Hydrolyzed egg yolk peptide (YPEP) was shown to increase bone mineral density in ovariectomized rats. However, the underlying mechanism of YPEP on osteoporosis has not been explored. Recent studies have shown that Wnt/ß-catenin signaling pathway and gut microbiota may be involved in the regulation of bone metabolism and the progression of osteoporosis. The present study aimed to explore the preventive effect of the YPEP supplementation on osteoporosis in ovariectomized (OVX) rats and to verify whether YPEP can improve osteoporosis by regulating Wnt/ß-catenin signaling pathway and gut microbiota. The experiment included five groups: sham surgery group (SHAM), ovariectomy group (OVX), 17-ß estradiol group (E2: 25 µg /kg/d 17ß-estradiol), OVX with low-dose YPEP group (LYPEP: 10 mg /kg/d YPEP) and OVX with high-dose YPEP group (HYPEP: 40 mg /kg/d YPEP). In this study, all the bone samples used were femurs. Micro-CT analysis revealed improvements in both bone mineral density (BMD) and microstructure by YPEP treatment. The three-point mechanical bending test indicated an enhancement in the biomechanical properties of the YPEP groups. The serum levels of bone alkaline phosphatase (BALP), bone gla protein (BGP), calcium (Ca), and phosphorus (P) were markedly higher in the YPEP groups than in the OVX group. The LYPEP group had markedly lower levels of alkaline phosphatase (ALP), tartrate-resistant acid phosphatase (TRAP) and C-terminal telopeptide of type I collagen (CTX-I) than the OVX group. The YPEP groups had significantly higher protein levels of the Wnt3a, ß-catenin, LRP5, RUNX2 and OPG of the Wnt/ß-catenin signaling pathway compared with the OVX group. Compared to the OVX group, the ratio of OPG/RANKL was markedly higher in the LYPEP group. At the genus level, there was a significantly increase in relative abundance of Lachnospiraceae_NK4A136_group and a decrease in Escherichia_Shigella in YPEP groups, compared with the OVX group. However, in the correlation analysis, there was no correlation between these two bacteria and bone metabolism and microstructure indexes. These findings demonstrate that YPEP has the potential to improve osteoporosis, and the mechanism may be associated with its modulating effect on Wnt/ß-catenin signaling pathway.

Metal Nanogap Memory: Performances and Switching Mechanism.

The nanogap memory (NGM) device, emerging as a promising nonvolatile memory candidate, has attracted increasing attention for its simple structure, nano/atomic scale size, elevated operating speed, and robustness to high temperatures. In this study, nanogap memories based on Pd, Au, and Pt were fabricated by combining nanofabrication with electromigration technology. Subsequent evaluations of the electrical characteristics were conducted under ambient air or vacuum conditions at room temperature. The investigation unveiled persistent challenges associated with metal NGM devices, including (1) prolonged SET operation time in comparison to RESET, (2) the potential generation of error bits when enhancing switching speeds, and (3) susceptibility to degradation during program/erase cycles. While these issues have been encountered by predecessors in NGM device development, the underlying causes have remained elusive. Employing molecular dynamics (MD) simulation, we have, for the first time, unveiled the dynamic processes of NGM devices during both SET and RESET operations. The MD simulation highlights that the adjustment of the tunneling gap spacing in nanogap memory primarily occurs through atomic migration or field evaporation. This dynamic process enables the device to transition between the high-resistance state (HRS) and the low-resistance state (LRS). The identified mechanism provides insight into the origins of the aforementioned challenges. Furthermore, the study proposes an effective method to enhance the endurance of NGM devices based on the elucidated mechanism.

Preliminary study on the mechanism by which exosomes derived from human exfoliated deciduous teeth improve the proliferation and osteogenic inhibitory effect of glucocorticoid-induced BMSCs.

BACKGROUND: Steroid-induced osteonecrosis of the femoral head (SONFH) is a disease characterized by a collapsed femoral head caused by the overuse of glucocorticoids. Dysfunction of bone marrow mesenchymal stem cells (BMSCs) is an important pathological feature of SONFH. In this study, we investigated whether exosomes from SHEDs (stem cells from human exfoliated deciduous teeth) have a therapeutic effect on glucocorticoid-induced inhibition of proliferation and osteogenesis in BMSCs, and elucidated the underlying mechanisms involved. METHODS: Primary dental pulp cells were isolated and cultured from human deciduous tooth pulp, SHEDs were isolated and purified by the limiting dilution method and exosomes were isolated from the supernatants of SHEDs by ultracentrifugation. The cell surface markers CD31, CD34, CD45, CD73, CD90 and CD105 were detected by flow cytometry. A Cell-Counting-Kit-8 assay was used to detect cell activity. ALP and Alizarin Red staining were used to identify osteogenic differentiation ability, and exosomes were identified using transmission electron microscopy, NanoFCM and Western blotting. PKH67 fluorescence was used to track the uptake of exosomes by BMSCs. Transcriptome analysis combined with quantitative real-time PCR was used to explore the underlying mechanism involved. RESULTS: Exosomes secreted by SHEDs can be endocytosed by BMSCs, and can partially reverse the inhibitory effects of glucocorticoids on the viability and osteogenic differentiation of BMSCs. Transcriptome sequencing analysis revealed that the differentially expressed mRNAs regulated by SHED-derived exosomes were enriched mainly in signaling pathways such as the apoptosis pathway, the PI3K-Akt signaling pathway, the Hippo signaling pathway and the p53 signaling pathway. qPCR showed that SHED-derived exosomes reversed the dexamethasone-induced upregulation of HGF and ITGB8 expression and the inhibition of EFNA1 expression, but further increased the dexamethasone-induced downregulation of IL7 expression. In conclusion, SHED-derived exosomes partially reversed the inhibitory effects of glucocorticoids on BMSC proliferation and osteogenesis by inhibiting the expression of HGF, ITGB8 and IL7, and upregulating the expression of EFNA1.

BERT-TFBS: a novel BERT-based model for predicting transcription factor binding sites by transfer learning.

Transcription factors (TFs) are proteins essential for regulating genetic transcriptions by binding to transcription factor binding sites (TFBSs) in DNA sequences. Accurate predictions of TFBSs can contribute to the design and construction of metabolic regulatory systems based on TFs. Although various deep-learning algorithms have been developed for predicting TFBSs, the prediction performance needs to be improved. This paper proposes a bidirectional encoder representations from transformers (BERT)-based model, called BERT-TFBS, to predict TFBSs solely based on DNA sequences. The model consists of a pre-trained BERT module (DNABERT-2), a convolutional neural network (CNN) module, a convolutional block attention module (CBAM) and an output module. The BERT-TFBS model utilizes the pre-trained DNABERT-2 module to acquire the complex long-term dependencies in DNA sequences through a transfer learning approach, and applies the CNN module and the CBAM to extract high-order local features. The proposed model is trained and tested based on 165 ENCODE ChIP-seq datasets. We conducted experiments with model variants, cross-cell-line validations and comparisons with other models. The experimental results demonstrate the effectiveness and generalization capability of BERT-TFBS in predicting TFBSs, and they show that the proposed model outperforms other deep-learning models. The source code for BERT-TFBS is available at https://github.com/ZX1998-12/BERT-TFBS.