Lingguizhugan Decoction Improved Obesity by Modulating the Gut Microbiota and its Metabolites in Mice.

BACKGROUND: The global obese population is rapidly increasing, urgently requiring the development of effective and safe weight-loss medications. The classic Chinese medicine formulation Lingguizhugan De-coction has exerted a significant anti-obesity effect. However, the underlying mechanism is still unclear. OBJECTIVE: This study aimed to explore the mechanism of LGZGD in the treatment of obesity based on the gut microbiota and its metabolites. METHODS: Three different dosages of LGZGD were gavaged to ob/ob mice for 8 weeks. Body mass and visceral fat mass were evaluated. Additionally, the changes in gut microbiota, fecal and plasma metabolites in mice after LGZGD treatment were analyzed by metagenomics and non-targeted metabolomics. RESULTS: The results demonstrated a significant anti-obesity effect of LGZGD treatment in ob/ob mice. Fur-thermore, the metagenomic analysis revealed that LGZGD reduced the ratio of Firmicutes / Bacteroidetes (F to B) in the gut, restored gut microbiota diversity, and identified 3 enriched KEGG pathways, including energy metabolism, lipid metabolism, and energy production and conversion pathways. Based on non-targeted metab-olomics analysis, 20 key metabolites in the feces and 30 key metabolites in the plasma responding to LGZGD treatment were identified, and the levels of Eicosapentaenoic acid (EPA) and Myristoleic acid (MA) might be the metabolites related to gut microbiota after LGZGD treatment. Their biological functions were mainly re-lated to the metabolism pathway. CONCLUSIONS: These findings suggested that LGZGD had therapeutic potential for obesity. The mechanism of LGZGD alleviating obesity was associated with improving dysbiosis of the gut microbiota. LDZGD affected gut microbiota-derived metabolites of EPA and MA and may act on energy metabolism pathways.

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.

Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to predict epidermal growth factor receptor (EGFR) mutation status in patients with stage I non-small cell lung cancer (NSCLC). We retrospectively included 438 patients who underwent curative surgery and completed driver-gene mutation tests for stage I NSCLC from four academic medical centers. Predictive models were established by extracting and analyzing radiomic features in intratumoral, peritumoral, and habitat regions of CT images to identify EGFR mutation status in stage I NSCLC. Additionally, three deep learning models based on the intratumoral region were constructed. A nomogram was developed by integrating representative radiomic signatures, deep learning, and clinical features. Model performance was assessed by calculating the area under the receiver operating characteristic (ROC) curve. The established habitat radiomics features demonstrated encouraging performance in discriminating between EGFR mutant and wild-type, with predictive ability superior to other single models (AUC 0.886, 0.812, and 0.790 for the training, validation, and external test sets, respectively). The radiomics-based nomogram exhibited excellent performance, achieving the highest AUC values of 0.917, 0.837, and 0.809 in the training, validation, and external test sets, respectively. Decision curve analysis (DCA) indicated that the nomogram provided a higher net benefit than other radiomics models, offering valuable information for treatment.

STIL facilitates the development and malignant progression of triple-negative breast cancer through activation of Fanconi anemia pathway via interacting with KLF16.

BACKGROUND: STIL is an important cell cycle-regulating protein specifically recruited to the mitotic centrosome to promote the replication of centrioles in dividing cells. However, the potential role of STIL in the regulation of the biological functions of triple-negative breast cancer remains still unclear. METHODS: We screened for differentially expressed STIL in the Cancer Genome Atlas database. The expression of STIL protein in 10 pairs of breast cancer tissues and adjacent normal tissues was further assessed by western blotting. Functionally, the knockdown and overexpression of STIL have been used to explore the effects of STIL on breast cancer cell proliferation, migration, and invasion. Mechanistically, RNA-seq, dual-luciferase reporter assay, chromatin immunoprecipitation assay, mass spectrometry, immunoprecipitation assay, and DNA pull-down assay were performed. RESULTS: Breast cancer tissues and cells have higher STIL expression than normal tissues and cells. STIL knockdown impairs breast cancer cell growth, migration, and invasion, whereas STIL overexpression accelerates these processes. STIL promotes breast cancer progression by regulating FANCD2 expression, and exploration of its molecular mechanism demonstrated that STIL interacts with KLF16 to regulate the expression of FANCD2. CONCLUSIONS: Collectively, our findings identified STIL as a critical promoter of breast cancer progression that interacts with KLF16 to regulate Fanconi anemia pathway protein FANCD2. In summary, STIL is a potential novel biomarker and therapeutic target for breast cancer.

Coupled physicochemical dual-crosslinking Ti3C2Tx composite aerogels for the selective adsorption of gallium ions in acid fly ash leaching.

Herein, in order to extract Ga3+ from acid fly ash leaching, we propose a functionalized Ti3C2Tx-based MXene composite aerogel adsorbent for Ga3+ adsorption. The prepared physicochemical dual-crosslinking network aerogel MPHG-40 possesses good Ga3+ adsorption performance (132.52 mg g-1) at the pH of 3 and Ga3+ initial concentration of 50 mg L-1 within 6 h. After five adsorption-desorption cycles, the material shows good mass retention and a 95.65 % retention of its initial adsorption capacity, compared to most reported adsorbents. The optimized adsorbent realized good selective adsorption of Ga3+ against Cu2+, Zn2+, Fe3+, and Al3+ in a simulated acid fly ash leaching with the selective coefficient of 8.63, 96.10, 4.49, and 28.30, respectively. The adsorption may comply with a combined mechanism of physical adsorption, electrostatic interactions, ion-exchange mechanism, and ligand chelation, dominated by chemical adsorption, as identified by theoretical calculations based on density functional theory and experimental data. The three-dimensional solid adsorbent constructed in this study provides a new strategy for selective adsorption of Ga3+, making it possible to be applied to solid waste utilization of fly ash.

Multi-Instance Learning for Vocal Fold Leukoplakia Diagnosis Using White Light and Narrow-Band Imaging: A Multicenter Study.

OBJECTIVES: Vocal fold leukoplakia (VFL) is a precancerous lesion of laryngeal cancer, and its endoscopic diagnosis poses challenges. We aim to develop an artificial intelligence (AI) model using white light imaging (WLI) and narrow-band imaging (NBI) to distinguish benign from malignant VFL. METHODS: A total of 7057 images from 426 patients were used for model development and internal validation. Additionally, 1617 images from two other hospitals were used for model external validation. Modeling learning based on WLI and NBI modalities was conducted using deep learning combined with a multi-instance learning approach (MIL). Furthermore, 50 prospectively collected videos were used to evaluate real-time model performance. A human-machine comparison involving 100 patients and 12 laryngologists assessed the real-world effectiveness of the model. RESULTS: The model achieved the highest area under the receiver operating characteristic curve (AUC) values of 0.868 and 0.884 in the internal and external validation sets, respectively. AUC in the video validation set was 0.825 (95% CI: 0.704-0.946). In the human-machine comparison, AI significantly improved AUC and accuracy for all laryngologists (p < 0.05). With the assistance of AI, the diagnostic abilities and consistency of all laryngologists improved. CONCLUSIONS: Our multicenter study developed an effective AI model using MIL and fusion of WLI and NBI images for VFL diagnosis, particularly aiding junior laryngologists. However, further optimization and validation are necessary to fully assess its potential impact in clinical settings. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Hydrophobic SiO2 Armor: Stabilizing Cuδ+ to Enhance CO2 Electroreduction toward C2+ Products in Strong Acidic Environments.

Electroreduction of CO2 in highly acidic environments holds promise for enhancing CO2 utilization efficiency. Due to the HER interference and structural instability, however, challenges in improving the selectivity and stability toward multicarbon (C2+) products remain. In this study, we proposed an "armor protection" strategy involving the deposition of ultrathin, hydrophobic SiO2 onto the Cu surface (Cu/SiO2) through a simple one-step hydrolysis. Our results confirmed the effective inhibition of HER by a hydrophobic SiO2 layer, leading to a high Faradaic efficiency (FE) of up to 76.9% for C2+ products at a current density of 900 mA cm-2 under a strongly acidic condition with a pH of 1. The observed high performance surpassed the reported performance for most previously studied Cu-based catalysts in acidic CO2RR systems. Furthermore, the ultrathin hydrophobic SiO2 shell was demonstrated to effectively prevent the structural reconstruction of Cu and preserve the oxidation state of Cuδ+ active sites during CO2RR. Additionally, it hindered the accumulation of K+ ions on the catalyst surface and diffusion of in situ generated OH- ions away from the electrode, thereby favoring C2+ product generation. In situ Raman analyses coupled with DFT simulations further elucidated that the SiO2 shell proficiently modulated *CO adsorption behavior on the Cu/SiO2 catalyst by reducing *CO adsorption energy, facilitating the C-C coupling. This work offers a compelling strategy for rationally designing and exploiting highly stable and active Cu-based catalysts for CO2RR in highly acidic environments.

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL). METHODS: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features. MIL was used to fusion image level results to patient level features, then the extracted features were modeled by seven machine learning algorithms. Finally, we evaluated the image level and patient level results. Additionally, 50 videos of VFL were prospectively gathered to assess the system's real-time diagnostic capabilities. A human-machine comparison database was also constructed to compare the diagnostic performance of otolaryngologists with and without AI assistance. RESULTS: In internal and external validation sets, the maximum area under the curve (AUC) for image level segmentation models was 0.775 (95 % CI 0.740-0.811) and 0.720 (95 % CI 0.684-0.756), respectively. Utilizing a MIL-based fusion strategy, the AUC at the patient level increased to 0.869 (95 % CI 0.798-0.940) and 0.851 (95 % CI 0.756-0.945). For real-time video diagnosis, the maximum AUC at the patient level reached 0.850 (95 % CI, 0.743-0.957). With AI assistance, the AUC improved from 0.720 (95 % CI 0.682-0.755) to 0.808 (95 % CI 0.775-0.839) for senior otolaryngologists and from 0.647 (95 % CI 0.608-0.686) to 0.807 (95 % CI 0.773-0.837) for junior otolaryngologists. CONCLUSIONS: The MIL based AI-assisted diagnosis system can significantly improve the diagnostic performance of otolaryngologists for VFL and help to make proper clinical decisions.

Revealing molecular and cellular heterogeneity in hypopharyngeal carcinogenesis through single-cell RNA and TCR/BCR sequencing.

Introduction: Hypopharyngeal squamous cell carcinoma (HSCC) is one of the malignant tumors with the worst prognosis in head and neck cancers. The transformation from normal tissue through low-grade and high-grade intraepithelial neoplasia to cancerous tissue in HSCC is typically viewed as a progressive pathological sequence typical of tumorigenesis. Nonetheless, the alterations in diverse cell clusters within the tissue microenvironment (TME) throughout tumorigenesis and their impact on the development of HSCC are yet to be fully understood. Methods: We employed single-cell RNA sequencing and TCR/BCR sequencing to sequence 60,854 cells from nine tissue samples representing different stages during the progression of HSCC. This allowed us to construct dynamic transcriptomic maps of cells in diverse TME across various disease stages, and experimentally validated the key molecules within it. Results: We delineated the heterogeneity among tumor cells, immune cells (including T cells, B cells, and myeloid cells), and stromal cells (such as fibroblasts and endothelial cells) during the tumorigenesis of HSCC. We uncovered the alterations in function and state of distinct cell clusters at different stages of tumor development and identified specific clusters closely associated with the tumorigenesis of HSCC. Consequently, we discovered molecules like MAGEA3 and MMP3, pivotal for the diagnosis and treatment of HSCC. Discussion: Our research sheds light on the dynamic alterations within the TME during the tumorigenesis of HSCC, which will help to understand its mechanism of canceration, identify early diagnostic markers, and discover new therapeutic targets.

A 3D-printable gelatin/alginate/ε-poly-l-lysine hydrogel scaffold to enable porcine muscle stem cells expansion and differentiation for cultured meat development.

The mass proliferation of seed cells and imitation of meat structures remain challenging for cell-cultured meat production. With excellent biocompatibility, high water content and porosity, hydrogels are frequently-studied materials for anchorage-dependent cell scaffolds in biotechnology applications. Herein, a scaffold based on gelatin/alginate/ε-Poly-l-lysine (GAL) hydrogel is developed for skeletal muscle cells, which has a great prospect in cell-cultured meat production. In this work, the hydrogel GAL-4:1, composed of gelatin (5 %, w/v), alginate (5 %, w/v) and ε-Poly-l-lysine (molar ratio vs. alginate: 4:1) is selected as cell scaffold based on Young's modulus of 11.29 ± 1.94 kPa, satisfactory shear-thinning property and suitable porous organized structure. The commercially available C2C12 mouse skeletal myoblasts and porcine muscle stem cells (PMuSCs), are cultured in the 3D-printed scaffold. The cells show strong ability of attachment, proliferation and differentiation after induction, showing high biocompatibility. Furthermore, the cellular bioprinting is performed with GAL-4:1 hydrogel and freshly extracted PMuSCs. The extracted PMuSCs exhibit high viability and display early myogenesis (desmin) on the 3D scaffold, suggesting the great potential of GAL hydrogel as 3D cellular constructs scaffolds. Overall, we develop a novel GAL hydrogel as a 3D-printed bioactive platform for cultured meat research.

MXene-based composite aerogels with bifunctional ferrous ions for the efficient degradation of phenol from wastewater.

Herein, MXene-based composite aerogel (MXene-Fe2+ aerogel) are constructed by a one-step freeze-drying method, using Ti3C2Tx MXene layers as substrate material and ferrous ion (Fe2+) as crosslinking agent. With the aid of the Fe2+ induced Fenton reaction, the synthesized aerogels are used as the particle electrodes to remove phenol from wastewater with three-dimensional electrode technology. Combined with the dual roles of Fe2+ and the highly conductive MXene, the obtained particle electrode possesses extremely effective phenol degradation. The effects of experiment parameters such as Fe2+ to MXene ratio, particle electrode dosage, applied voltage, and initial pH of solution on the removal of phenol are discussed. At pH = 2.5, phenol with 50 mg/L of initial concentration can be completely removed within 50 min at 10 V with the particle electrode dosage of 0.56 g/L. Finally, the mechanism of degradation is explored. This work provides an effective way for phenol degradation by MXene-based aerogel, which has great potential for the degradation of other organic pollutants in wastewater.

Continuous and low-carbon production of biomass flash graphene.

Flash Joule heating (FJH) is an emerging and profitable technology for converting inexhaustible biomass into flash graphene (FG). However, it is challenging to produce biomass FG continuously due to the lack of an integrated device. Furthermore, the high-carbon footprint induced by both excessive energy allocation for massive pyrolytic volatiles release and carbon black utilization in alternating current-FJH (AC-FJH) reaction exacerbates this challenge. Here, we create an integrated automatic system with energy requirement-oriented allocation to achieve continuous biomass FG production with a much lower carbon footprint. The programmable logic controller flexibly coordinated the FJH modular components to realize the turnover of biomass FG production. Furthermore, we propose pyrolysis-FJH nexus to achieve biomass FG production. Initially, we utilize pyrolysis to release biomass pyrolytic volatiles, and subsequently carry out the FJH reaction to focus on optimizing the FG structure. Importantly, biochar with appropriate resistance is self-sufficient to initiate the FJH reaction. Accordingly, the medium-temperature biochar-based FG production without carbon black utilization exhibited low carbon emission (1.9 g CO2-eq g-1 graphene), equivalent to a reduction of up to ~86.1% compared to biomass-based FG production. Undoubtedly, this integrated automatic system assisted by pyrolysis-FJH nexus can facilitate biomass FG into a broad spectrum of applications.

Jasmonates Promote ß-Amylase-Mediated Starch Degradation to Confer Cold Tolerance in Tomato Plants.

Cold stress severely restricts growth and development, reduces yields, and impairs quality in tomatoes (Solanum lycopersicum). Amylase-associated starch degradation and soluble sugar accumulation have been implicated in adaptation and resistance to abiotic stress. Here, we report a ß-amylase (BAM) gene, SlBAM3, which plays a central role in tomato cold tolerance. The expression of SlBAM3 was triggered by cold stress. SlBAM3 knockout using the CRISPR/Cas9 system retarded starch degradation and reduced soluble sugar accumulation in tomato plants, eventually attenuating cold tolerance. Expression analysis revealed that the SlBAM3 transcript level was boosted by MeJA. Furthermore, MYC2, an essential component of the JA signaling pathway, could bind to the SlBAM3 promoter and directly activate SlBAM3 transcription, as revealed by yeast one-hybrid and dual LUC assays. In addition, the suppression of MYC2 resulted in increased starch accumulation, decreased soluble sugar content, and reduced tolerance to cold stress in tomato plants. Taken together, these findings demonstrate that JA positively regulates ß-amylase-associated starch degradation through the MYC2-SlBAM3 module in tomato during cold stress. The results of the present work expand our understanding of the mechanisms underlying BAM gene activation and starch catabolism under cold stress. The regulatory module of SlBAM3 can be further utilized to breed tomato cultivars with enhanced cold tolerance.

Survival and neurological function in patients treated with extracorporeal membrane oxygenation and therapeutic hypothermia: a protocol for updating a systematic review.

INTRODUCTION: The widespread application of extracorporeal membrane oxygenation (ECMO) has enhanced clinical outcomes for patients experiencing cardiac arrest. However, its effectiveness is still limited and falls short of the desired level. Therapeutic hypothermia, which maintains body temperatures between 32°C and 36°C in cardiac arrest patients treated with ECMO, has been proposed as a potential means of neuroprotection and increased survival rates. Nevertheless, it remains controversial, and its impact on patient complications has yet to be fully understood. Thus, this paper aims to update the protocol for a systematic review of patients treated with ECMO and therapeutic hypothermia, in order to explore its effects on survival and neurological function. METHOD AND ANALYSIS: This protocol has been developed in compliance with the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols 2015. The following databases will be systematically searched: PubMed, Web of Science, Cochrane Library, Embase, Ovid, CNKI, Wanfang and China Biology Medicine Disc. The database search strategy will use a combination of subject terms and free-text keywords. The search will encompass articles from the inception of each database up to 15 June 2023. Inclusion criteria encompass randomised controlled trials, cohort studies, case-control studies and quasi-experimental studies. Two researchers will independently review articles and extract relevant data based on these criteria. Any disagreements will be resolved through discussion. Data analysis will be performed using Review Manager software. ETHICS AND DISSEMINATION: Since no patient data were collected in this study, ethical approval was not required. Research findings will be released in a peer-reviewed journal. PROSPERO REGISTRATION NUMBER: CRD42023435353.

Fabrication of a Coculture Organoid Model in the Biomimetic Matrix of Alginate to Investigate Breast Cancer Progression in a TAMs-Leading Immune Microenvironment.

The current research models of breast cancer are usually limited in their capacity to recapitulate the tumor microenvironment in vitro. The lack of an extracellular matrix (ECM) oversimplifies cell-cell or cell-ECM cross-talks. Moreover, the lack of tumor-associated macrophages (TAMs), that can comprise up to 50% of some solid neoplasms, poses a major problem for recognizing various hallmarks of cancer. To address these concerns, a type of direct breast cancer cells (BCCs)-TAMs coculture organoid model was well developed by a sequential culture method in this study. Alginate cryogels were fabricated with appropriate physical and mechanical properties to serve as an alternative ECM. Then, our previous experience was leveraged to polarize TAMs inside of the cryogels for creating an in vitro immune microenvironment. The direct coculture significantly enhanced BCCs organoid growth and cancer aggressive phenotypes, including the stemness, migration, ECM remodeling, and cytokine secretion. Furthermore, transcriptomic analysis and protein-protein interaction networks implied certain pathways (PI3K-Akt pathway, MAPK signaling pathway, etc.) and targets (TNF, PPARG, TLR2, etc.) during breast cancer progression in a TAM-leading immune microenvironment. Future studies to advance treatment strategies for BCC patients may benefit from using this facile model to reveal and target the interactions between cancer signaling and the immune microenvironment.

HCT: Chinese Medical Machine Reading Comprehension Question-Answering via Hierarchically Collaborative Transformer.

Chinese medical machine reading comprehension question-answering (cMed-MRCQA) is a critical component of the intelligence question-answering task, focusing on the Chinese medical domain question-answering task. Its purpose enable machines to analyze and understand the given text and question and then extract the accurate answer. To enhance cMed-MRCQA performance, it is essential to possess a profound comprehension and analysis of the context, deduce concealed information from the textual content and, subsequently, precisely determine the answer's span. The answer span has predominantly been defined by language items, with sentences employed in most instances. However, it is worth noting that sentences may not be properly split to varying degrees in various languages, making it challenging for the model to predict the answer zone. To alleviate this issue, this paper presents a novel architecture called HCT based on a Hierarchically Collaborative Transformer. Specifically, we presented a hierarchical collaborative method to locate the boundaries of sentence and answer spans separately. First, we designed a hierarchical encoding module to obtain the local semantic features of the corpus; second, we proposed a sentence-level self-attention module and a fused interaction-attention module to get the global information about the text. Finally, the model is trained by combining loss functions. Extensive experiments were conducted on the public dataset CMedMRC and the reconstruction dataset eMedicine to validate the effectiveness of the proposed method. Experimental results showed that the proposed method performed better than the state-of-the-art methods. Using the F1 metric, our model scored 90.4% on the CMedMRC and 73.2% on eMedicine.

Depression-associated gut microbes, metabolites and clinical trials.

Depression is one of the most prevalent mental disorders today. Over the past decade, there has been considerable attention given to the field of gut microbiota associated with depression. A substantial body of research indicates a bidirectional communication pathway between gut microbiota and the brain. In this review, we extensively detail the correlation between gut microbiota, including Lactobacillus acidophilus and Bifidobacterium longum, and metabolites such as short-chain fatty acids (SCFAs) and 5-hydroxytryptamine (5-HT) concerning depression. Furthermore, we delve into the potential health benefits of microbiome-targeted therapies, encompassing probiotics, prebiotics, and synbiotics, in alleviating depression. Lastly, we underscore the importance of employing a constraint-based modeling framework in the era of systems medicine to contextualize metabolomic measurements and integrate multi-omics data. This approach can offer valuable insights into the complex metabolic host-microbiota interactions, enabling personalized recommendations for potential biomarkers, novel drugs, and treatments for depression.

mTOR inhibitor introduce disitamab vedotin (RC48-ADC) rechallenge microtubule-chemotherapy resistance in HER2-low MBC patients with PI3K mutation.

This study aimed to explore the efficacy and potential mechanisms of rechallenge therapy with microtubule-targeting agents (MTAs) in patients with HER2-low metastatic breast cancer (MBC). We performed a systematic review to investigate the rechallenge treatment concept in the field of HER2-low MBC treatment and utilized a series of cases identified in the literature to illustrate the concept. Here we reported two clinical cases of HER2-low MBC patients whose disease progressed after prior treatment with MTAs such as docetaxel and vincristine. When rechallenged with disitamab vedotin ((RC48-antibody-drug conjugate (ADC), a monomethyl auristatin (MMAE) MTA)), both patients achieved a partial response and the final progression-free survival (PFS) was 13.5 and 9 months, respectively. Genomic profiling detected a PIK3CA H1047R mutation in the patients. The patients were treated with everolimus before being rechallenged with RC48, which may lead to a better response. This study further summarizes and analyzes the potential mechanism of the PI3K-AKT signaling pathway in MTA resistance and reveals that the PIK3CA H1047R mutation may be a potential molecular marker for the efficacy prediction of mTOR inhibitors, providing new insights and potential therapeutic strategies for the application of MTAs to MBC patients.

Abscisic acid-induced transcription factor PsMYB306 negatively regulates tree peony bud dormancy release.

Bud dormancy is a crucial strategy for perennial plants to withstand adverse winter conditions. However, the regulatory mechanism of bud dormancy in tree peony (Paeonia suffruticosa) remains largely unknown. Here, we observed dramatically reduced and increased accumulation of abscisic acid (ABA) and bioactive gibberellins (GAs) GA1 and GA3, respectively, during bud endodormancy release of tree peony under prolonged chilling treatment. An Illumina RNA sequencing study was performed to identify potential genes involved in the bud endodormancy regulation in tree peony. Correlation matrix, principal component, and interaction network analyses identified a downregulated MYB transcription factor gene, PsMYB306, the expression of which positively correlated with 9-CIS-EPOXYCAROTENOID DIOXYGENASE 3 (PsNCED3) expression. Protein modeling analysis revealed 4 residues within the R2R3 domain of PsMYB306 to possess DNA binding capability. Transcription of PsMYB306 was increased by ABA treatment. Overexpression of PsMYB306 in petunia (Petunia hybrida) inhibited seed germination and plant growth, concomitant with elevated ABA and decreased GA contents. Silencing of PsMYB306 accelerated cold-triggered tree peony bud burst and influenced the production of ABA and GAs and the expression of their biosynthetic genes. ABA application reduced bud dormancy release and transcription of ENT-KAURENOIC ACID OXIDASE 1 (PsKAO1), GA20-OXIDASE 1 (PsGA20ox1), and GA3-OXIDASE 1 (PsGA3ox1) associated with GA biosynthesis in PsMYB306-silenced buds. In vivo and in vitro binding assays confirmed that PsMYB306 specifically transactivated the promoter of PsNCED3. Silencing of PsNCED3 also promoted bud break and growth. Altogether, our findings suggest that PsMYB306 negatively modulates cold-induced bud endodormancy release by regulating ABA production.

Qingda granule alleviates cerebral ischemia/reperfusion injury by inhibiting TLR4/NF-κB/NLRP3 signaling in microglia.

ETHNOPHARMACOLOGICAL RELEVANCE: Qingda granule (QDG) is effective for treating hypertension and neuronal damage after cerebral ischemia/reperfusion. However, the anti-neuroinflammatory effect of QDG on injury due to cerebral ischemia/reperfusion is unclear. AIM OF THE STUDY: The objective was to evaluate the effectiveness and action of QDG in treating neuroinflammation resulting from cerebral ischemia/reperfusion-induced injury. MATERIALS AND METHODS: Network pharmacology was used to predict targets and pathways of QDG. An in vivo rat model of middle cerebral artery occlusion/reperfusion (MCAO/R) as well as an in vitro model of LPS-stimulated BV-2 cells were established. Magnetic resonance imaging (MRI) was used to quantify the area of cerebral infarction, with morphological changes in the brain being assessed by histology. Immunohistochemistry (IHC) was used to assess levels of the microglial marker IBA-1 in brain tissue. Bioplex analysis was used to measure TNF-α, IL-1ß, IL-6, and MCP-1 in sera and in BV-2 cell culture supernatants. Simultaneously, mRNA levels of these factors were examined using RT-qPCR analysis. Proteins of the TLR4/NF-κB/NLRP3 axis were examined using IHC in vivo and Western blot in vitro, respectively. While NF-κB translocation was assessed using immunofluorescence. RESULTS: The core targets of QDG included TNF, NF-κB1, MAPK1, MAPK3, JUN, and TLR4. QDG suppressed inflammation via modulation of TLR4/NF-κB signaling. In addition, our in vivo experiments using MCAO/R rats demonstrated the therapeutic effect of QDG in reducing brain tissue infarction, improving neurological function, and ameliorating cerebral histopathological damage. Furthermore, QDG reduced the levels of TNF-α, IL-1ß, IL-6, and MCP-1 in both sera from MCAO/R rats and supernatants from LPS-induced BV-2 cells, along with a reduction in the expression of the microglia biomarker IBA-1, as well as that of TLR4, MyD88, p-IKK, p-IκBα, p-P65, and NLRP3 in MCAO/R rats. In LPS-treated BV-2 cells, QDG downregulated the expression of proinflammatory factors and TLR4/NF-κB/NLRP3 signaling-related proteins. Additionally, QDG reduced translocation of NF-κB to the nucleus in both brains of MCAO/R rats and LPS-induced BV-2 cells. Moreover, the combined treatment of the TLR4 inhibitor TAK242 and QDG significantly reduced the levels of p-P65, NLRP3, and IL-6. CONCLUSIONS: QDG significantly suppressed neuroinflammation by inhibiting the TLR4/NF-κB/NLRP3 axis in microglia. This suggests potential for QDG in treating ischemia stroke.

Effects of Phase â Cardiac Rehabilitation Combined with Cognitive Behavioural Therapy on Cardiac Function, Exercise Capacity and Mental Health in Patients after Aortic Valve Replacement: A Retrospective Study.

OBJECTIVE: To explore the application effect of phase Ⅰ cardiac rehabilitation (CR-Ⅰ) combined with cognitive behavioural therapy (CBT) on patients after aortic valve replacement (AVR). METHODS: This study retrospectively analysed the data of 441 patients after AVR in our hospital from January 2020 to May 2023. A total of 38 patients who did not meet the inclusion criteria were excluded. A total of 403 patients were included. In accordance with different postoperative management schemes, the included patients were divided into the reference group (n = 202, received CR-Ⅰ) and the observation group (n = 201, received CR-Ⅰ+CBT). The cardiac function, exercise capacity and mental health of the two groups were compared. RESULTS: Before management, both groups had no significant differences in left ventricular end diastolic diameter (LVEDD), left ventricular end systolic dimension (LVESD), left ventricular ejection fraction (LVEF) and six-minute walking test (6MWT) scores (p > 0.05). At discharge and 3 months after discharge, the observation group had significantly lower LVEDD and LVESD and remarkably higher LVEF and 6MWT scores than the reference group (p < 0.001). The proportions of autonomous activity in bed within 3-4 days after surgery, autonomous out-of-bed activity within 8-10 days after surgery and autonomous walking 200 m within 12-15 days after surgery were distinctly higher (p < 0.001) and the incidence of adverse reactions was overtly lower (p < 0.001) in the observation group than in the reference group. Before management, both groups had no significant difference in their scores on the State-Trait Anxiety Inventory (STAI) (p > 0.05). At discharge and 3 months after discharge, the observation group had lower STAI scores than the reference group (p < 0.001). CONCLUSION: CR-Ⅰ combined with CBT effectively improves the cardiac function, independent exercise capacity and mental health level of patients after AVR and provides a new direction for the formulation and selection of follow-up clinical management.