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The fruit of Phyllanthus emblica L. (FEPE) has a long history of use in Asian folk medicine. The main bioactive compounds in FEPE are polyphenols, known for their potent antioxidant, anti-inflammatory, and hypolipidemic activities. The present study aimed to investigate the intervention effect of FEPE (100 and 200 mg/kg) on hyperlipidemia for 8 weeks and preliminarily explored the potential mechanism by microbiome-metabolome analysis. The results showed that a high-dose FEPE (200 mg/kg) effectively alleviated dyslipidaemic symptoms and body weight gain in hyperlipidemic mice induced by a high-fat diet (HFD). Microbiome analysis showed that FEPE altered the structure of the intestinal microbiota, which included an increase in specific probiotics (such as Akkermansia, Anaerovorax, and Bacteroides) and a decrease in harmful bacteria (including A2, Acetitomaculum, Candidatus_Arthromitus, Lachnospiraceae_NK4A136_group, Lachnospiraceae_NK4B4_group, Rikenella, and Streptococcus), as well as a reduction in the level of short-chain fatty acids (SCFAs). In addition, significant changes in the hepatic metabolome were observed, and eight key metabolites associated with betaine metabolism, lysine degradation, methionine metabolism, and fatty acid metabolism pathways were primarily filtered. The correlated analysis identified several key “microbiota-metabolite” axes in the treatment of hyperlipidemia by FEPE extract. In conclusion, the present study is expected to provide a basis for treating hyperlipidemia with FEPE from the perspective of the microbiome-liver metabolome axis.

A light field (LF) camera captures both spatial and angular information of the real world, and the intertwined nature of these dimensions presents a pressing challenge in effectively disentangling meaningful LF information for depth estimation. This paper introduces a feature extraction network based on LF decoupling, which ingeniously separates the LF. Furthermore, given the extensive volume of input data inherent in LF images, a novel reparameterizable Residual-Densely Branched Leaky-ReLU Block(Res-DBLB) architecture was developed to replace conventional residual structures and multibranch architectures and enhance inference efficiency. Incorporating an attention mechanism further refines the network, effectively addressing the computational intensity and time-consuming nature of LF depth estimation, thus furthering the advancement of this technology. Our model was applied to widely used datasets as well as the latest LF datasets, namely HCI and UrbanLF, showing superior performance over six other popular models across four evaluation metrics.

Supersaturation is a promising strategy to improve gastrointestinal absorption of poorly water-soluble drugs. Supersaturation is a metastable state and therefore dissolved drugs often quickly precipitate again. Precipitation inhibitors can prolong the metastable state. Supersaturating drug delivery systems (SDDS) are commonly formulated with precipitation inhibitors, hence the supersaturation is effectively prolonged for absorption, leading to improved bioavailability. This review summarizes the theory of and systemic insight into supersaturation, with the emphasis on biopharmaceutical aspects. Supersaturation research has developed from the generation of supersaturation (pH-shift, prodrug and SDDS) and the inhibition of precipitation (the mechanism of precipitation, the character of precipitation inhibitors and screening precipitation inhibitors). Then, the evaluation approaches to SDDS are discussed, including in vitro, in vivo and in silico studies and in vitro–in vivo correlations. In vitro aspects involve biorelevant medium, biomimetic apparatus and characterization instruments; in vivo aspects involve oral absorption, intestinal perfusion and intestinal content aspiration and in silico aspects involve molecular dynamics simulation and pharmacokinetic simulation. More physiological data of in vitro studies should be taken into account to simulate the in vivo environment. The supersaturation theory should be further completed, especially with regard to physiological conditions.

Context Processing with vinegar could enhance the efficacy and reduce the toxicity of Curcuma phaeocaulis Valeton. (Zingiberaceae), a Chinese herbal medicine with anti-inflammatory and antitumor activities. Objective This study investigated the vinegar processing effects by evaluating anti-angiogenic effect and toxicity of C. phaeocaulis through zebrafish and rat models. Materials and methods Zebrafish embryos (AB and FLk-GFP strain) were applied to evaluate toxicity, cardiotoxicity and anti-angiogenic activity of volatile oil, and water decoction of the raw and vinegar-processed C. phaeocaulis. Meanwhile, a blood stasis syndrome rat model was applied to study the toxicity by measuring the ovarian and uterine coefficient. Results Curcuma phaeocaulis volatile oil and its vinegar-processed products in zebrafish had an LC50 of 67.315 and 95.755 μg/mL, respectively. Curcuma phaeocaulis water decoction and its vinegar-processed products had an LC50 of 161.440 and 206.239 μg/mL, respectively. The toxicity of vinegar-processed products was significantly lower than the raw, and the development characteristic of zebrafish embryos at different times confirmed these results. The volatile oil of vinegar-processed products could inhibit the growth of intersegmental blood vessels at the dose of 20 μg/mL, while the raw materials did not exhibit such effect at the same concentration. The rat experiment also confirmed that the volatile oil could reduce toxicity of ovarian and uterine. Discussion and conclusions The study indicated that processing using vinegar could decrease toxicity and increase anti-angiogenic activity of C. phaeocaulis, which could be applied for clinical treatment. Further in-depth study on the synergism and detoxification mechanism of vinegar processing technology is needed.

Huaganjian decoction (HGJD) was first recorded in the classic “Jing Yue Quan Shu” during the Ming dynasty, and it has been extensively applied in clinical practice to treat liver diseases for over 300 years in China. However, its bioactive constituents and relevant pharmacological mechanism are still unclear. In this study, a strategy integrating network analysis and metabolomics was applied to reveal mechanism of HGJD in treating cholestatic hepatic injury (CHI). Firstly, we observed the therapeutic effect of HGJD against CHI with an alpha-naphthylisothiocyanate (ANIT) induced CHI rat model. Then, we utilized UPLC-Q-Exactive MS/MS method to analyze the serum migrant compounds of HGJD in CHI rats. Based on these compounds, network analysis was conducted to screen for potential active components, and key signaling pathways interrelated to therapeutic effect of HGJD. Meanwhile, serum metabolomics was utilized to investigate the underlying metabolic mechanism of HGJD against CHI. Finally, the predicted key pathway was verified by western blot and biochemical analysis using rat liver tissue from in vivo efficacy experiment. Our results showed that HGJD significantly alleviated ANIT induced CHI. Totally, 31 compounds originated from HGJD have been identified in the serum sample. PI3K/Akt/Nrf2 signaling pathway related to GSH synthesis was demonstrated as one of the major pathways interrelated to therapeutic effect of HGJD against CHI. This research supplied a helpful strategy to determine the potential bioactive compounds and mechanism of traditional Chinese medicine.

Cancer is a fatal disease with high mortality and low survival rate worldwide. At present, there is still no known cure for most cancers. Traditional Chinese medicine (TCM) represents a noteworthy reservoir for anticancer agents in drug discovery and development. Curcumae Rhizoma (called Ezhu in Chinese) is widely prescribed in TCM for anticancer therapy owing to its broad-spectrum antineoplastic activities. Especially, the terpenoids isolated from the essential oil of Curcumae Rhizoma form an integral part of cancer research and are well established as a potential anticancer agent. For example, β-elemene has been developed into a new drug for the treatment of solid tumors in China, and is currently undergoing clinical trials in the United States. The review aims to systematically summarize the recent advances on the anticancer effects and related molecular mechanisms of Curcumae Rhizoma, and its terpenoids (β-elemene, Furanodiene, Furanodienone, Germacrone, Curcumol, Curdione). In addition, we evaluated and compared the anticancer efficacy and clinical use of the terpenoids with combination therapies and traditional therapies. Therefore, this review provides sufficient evidence for the anticancer therapeutic potential of Curcumae Rhizoma and its terpenoids, and will contribute to the development of potential anticancer drugs.

Curcumin, the medically active component from Curcuma longa (Turmeric), is widely used to treat inflammatory diseases. Protein interaction network (PIN) analysis was used to predict its mechanisms of molecular action. Targets of curcumin were obtained based on ChEMBL and STITCH databases. Protein–protein interactions (PPIs) were extracted from the String database. The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology (GO) enrichment analysis based on molecular complex detection (MCODE). A PIN of curcumin with 482 nodes and 1688 interactions was constructed, which has scale-free, small world and modular properties. Based on analysis of these function modules, the mechanism of curcumin is proposed. Two modules were found to be intimately associated with inflammation. With function modules analysis, the anti-inflammatory effects of curcumin were related to SMAD, ERG and mediation by the TLR family. TLR9 may be a potential target of curcumin to treat inflammation.

The importance of the “gut–liver axis” in the pathogenesis of liver diseases has been revealed recently; which promotes the process of developing preventive and therapeutic strategies. However, considering that there are still many challenges in the medical treatment of liver diseases, potential preventive dietary intervention may be a good alternative choice. Plant-based foods have received much attention due to their reported health-promoting effects in targeting multiple pathways involved in the pathogenesis of liver diseases as well as the relative safety for general use. Based on the PubMed and Web of Science databases, this review emphatically summarizes the plant-based foods and their chemical constituents with reported effects to impact the LPS/TLR4 signaling pathway of gut–liver axis of various liver diseases, reflecting their health benefits in preventing/ alleviating liver diseases. Moreover, some plant-based foods with potential gut–liver effects are specifically analyzed from the reported studies and conclusions. This review intends to provide readers an overview of the current progress in the field of this research topic. We expect to see more hepatoprotective measures for alleviating the current prevalence of liver diseases. [ABSTRACT FROM AUTHOR]

Due to the subwavelength lithography, manufacturing sub-90-nm feature sizes require intensive use of resolutionenhancement techniques, among which optical proximity correction (OPC) is the most popular technique in industry. Considering the OPC effects during routing can significantly alleviate the cost of postlayout OPC operations. In this paper, we present an efficient, accurate, and economical analytical formula for intensity computation and develop the first modeling of postlayout OPC based on a quasi-inverse lithography technique. The technique provides key insights into a new direction for postlayout OPC modeling during routing. Extensive simulations with SPLAT, the golden lithography simulator in academia and industry, show that our intensity formula has high fidelity. Incorporating the OPC costs computed by the quasi-inverse lithography technique for our postlayout OPC modeling into a router, the router can be guided to maximize the effects of the correction. Compared with a rule-based OPC method, the experimental results show that our approach can achieve 15% and 16% reductions in the maximum and average layout distortions, respectively [ABSTRACT FROM AUTHOR]

Abstract Background The diagnostic process for fibrotic interstitial lung disease (F-ILD) is notably intricate, necessitating a multidisciplinary discussion to achieve consensus based on both clinical and radiological features. This study investigated the shared and distinctive long-term mortality predictors among the two primary phenotypes of F-ILD, namely idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated interstitial lung disease (CTD-ILD). Methods We included patients with F-ILD diagnosed from December 2018 to December 2019 and conducted follow-up assessments until February 2023. Age, gender, usual interstitial pneumonia (UIP) pattern, gender–age–physiology (GAP) score, modified Medical Research Council (mMRC) dyspnea score, antifibrotic agent use, pulmonary function test parameters, and six-minute walking test (6MWT) parameters were recorded at baseline and used as mortality predictors in a multivariate Cox regression model. Results We enrolled 104 ILD patients. The survival rate of non-IPF patients was more than twice that of IPF patients (78.9% vs. 34%, p 2 (93.2% vs. 36.6%, p 2 (hazard ratio [HR]:16.7; 95% confidence interval [CI] 3.28–85.14; p = 0.001) and definite UIP pattern (HR: 4.08; 95% CI 1.07–15.5; p = 0.039) were significantly associated with overall mortality. Conclusion The long-term mortality rate of IPF patients was higher than that of CTD-ILD patients. The GAP score and UIP patterns were significant mortality predictors for both IPF and CTD-ILD patients.

Abstract Background Idiopathic pulmonary fibrosis (IPF) stands out as one of the most aggressive forms of interstitial lung diseases (ILDs), currently without a definitive cure. Multidisciplinary discussion (MDD) is now considered a cornerstone in diagnosing and differentiating ILD subtypes. The Gender-Age-Physiology (GAP) score, developed to assess IPF prognosis based on sex, age, forced vital capacity, and diffusion capacity for carbon monoxide (DLCO), is limited in not considering dyspnea and functional impairment during the walking test. We proposed a MDD-based clinical score for mortality prediction among those patients. Methods From December 2018 to December 2019, we enrolled ILD patients with IPF and non-IPF and followed-up them till December 2020. Based on DLCO, modified Medical Research Council (mMRC) Dyspnea Scale, and six-minute walking test (6MWT) distance, a functional score was developed for mortality prediction. Results We enrolled 104 ILD patients, 12 (11.5%) died by the one-year follow-up. In receiver operating characteristic (ROC) curve analysis, DLCO (% predicted) was the most accurate variable predicting one-year mortality with an area under curve (AUC) of 0.88 (95% confidence interval [CI] = 0.80–0.94), followed by mMRC Dyspnea Score (AUC = 0.82 [95% CI = 0.73–0.89]), 6MWT distance (AUC = 0.80 [95% CI = 0.71–0.88]), and GAP score (AUC = 0.77 [95% CI = 0.67–0.84]). Only the GAP score (hazard ratio [HR] = 1.55, 95% CI = 1.03–2.34, p = 0.0.37) and functional score (HR = 3.45, 95% CI = 1.11–10.73, p = 0.032) were significantly associated with one-year mortality in multivariable analysis. Conclusion The clinical score composite of DLCO, mMRC Dyspnea Scale, and 6MWT distance could provide an accurate prediction for long-term mortality in ILD patients, laying out a helpful tool for managing and following these patients.

Abstract To investigate the impact of an electronic medical record management system (EMRMS) on disease activity and the frequency of outpatient visits among patients with ankylosing spondylitis (AS). We identified 652 patients with AS who were followed up for at least 1 year before and after the first Ankylosing Spondylitis Disease Activity Score (ASDAS) assessment and compared the number of outpatient visits and average visit time within 1 year before and after the initial ASDAS assessment. Finally, we analyzed 201 patients with AS who had complete data and received ≥ 3 continuous ASDAS assessments at an interval of 3 months, and we compared the results of the second and third ASDAS assessments with those of the first. The number of annual outpatient visits increased after ASDAS assessment (4.0 (4.0, 7.0) vs. 4.0 (4.0, 8.0), p

ObjectivesThe Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) has been widely utilized to evaluate disease activity in patients with ankylosing spondylitis (AS) by an arbitrary cut-off of ≥4 to indicate high disease activity and initiate biological therapy. The Ankylosing Spondylitis Disease Activity Score (ASDAS) is a new composite index to assess AS disease activity states that have been defined and validated. ASDAS ≥2.1 was selected as a criterion to start biological therapy. The purpose of this study was to estimate the corresponding BASDAI and ASDAS cut-off in a Taiwanese AS cohort.MethodsFrom November 2016 to October 2018, we assessed the ASDAS and the BASDAI regularly and recorded demographic data for 489 AS patients in Taichung Veterans General hospital (TCVGH) using an electronic patient-reported data system linked to electronic medical records. We used receiver operating characteristic curves with Youden's J statistic to determine the BASDAI values that correspond to ASDAS disease activity cut-offs (i.e., 1.3, 2.1, and 3.5).ResultsIn our population, the best trade-off BASDAI values corresponding to ASDAS -C-reactive protein (CRP) 1.3, 2.1, and 3.5 were 2.1, 3.1, and 3.7, respectively. The optimal BASDAI values corresponding to ASDAS-erythrocyte sedimentation rates 1.3, 2.1, and 3.5 were 2.0, 2.6, and 4.8, respectively.ConclusionWe propose a revised BASDAI cut-off based on our data, as BASDAI scores are commonly used globally. A more reasonable, lower BASDAI cut-off to initiate or change biological therapy will bring us closer to better decisions to treat AS patients.