Fluorescence Characteristics and Main Fluorescence Component in Burmese 'chameleon' Amber.

One special variety of Burmese amber is "chameleon" amber, named for the bluish-green colour that appears to float on its surface. This material is found in the famous Tengchong market in Yunnan Province, China's largest Burmese amber market. Its bodycolour ranges from golden brown to brownish-red or even red. When exposed to sunlight or strong white light against a black background, its surface shows a uniform green colour. This research presents the gemological properties, spectral characteristics and organic components of Burmese 'chameleon' amber. Three-dimensional (3D) fluorescence spectra showed that Burmese 'chameleon' amber had fluorescence centres near 433, 465 and 470 nm, and the excitation wavelengths of the fluorescence centres of Burmese 'chameleon' amber were shifted from the ultraviolet region (380 ± 10 nm) to the visible region (410 ± 10 nm), with the emission wavelengths concentrated at the bluish-green region. Through the colour simulation and superimposition, the phenomenon of floating bluish-green fluorescence colour of Burmese 'chameleon' amber is not only derived from bluish-green fluorescence centres, but also enhanced by the mixture of surface fluorescence and its bodycolour. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) analysis demonstrated the variety of aromatic compounds in Burmese 'chameleon' amber was related to geological process and the presence of fluorescence components. The high-performance liquid chromatography-fluorescence detector obtained some fluorescent aromatics, particularly benzo[a]anthracene with yellowish-green fluorescence, which is responsible for the fluorescence characteristics of Burmese 'chameleon' amber.

Enhancing Soybean and Maize Yields through Improved Nitrogen and Soil Water Use Efficiencies: A 40-Year Study on the Impact of Farmyard Manure Amendment in Northeast China.

The combined application of manure and chemical fertilizers has been recognized as a critical factor driving significant changes in crop yield and nutrient use efficiency, holding the potential to optimize agricultural management to achieve high yields. In this 40-year study, we investigated the effect of manure amendment on soybean and maize yields, water and nitrogen use efficiencies (WUE and NUE), and water and mineral N storage at 0-100 cm soil depths from 2017 to 2018 to explore the optimization of fertilization management strategies for soybean and maize production in Northeast China. To elucidate the impact of chemical fertilizers and manure, twelve treatments-control (CK); single N fertilizer at a low rate (N1) and that at a high rate (N2); N1, phosphorus (P), and potassium (K) fertilizer (N1PK); manure alone at 13.5 and 27 t ha-1 (M1 and M2); and those combined with N, P, or K fertilizer (M1N1, M1N2, and M1N1PK and M2N1, M2N2, and M2N1PK)-were selected and studied. The results showed that long-term amendment with manure significantly increased crop biomass and yield in the soybean-maize-maize rotation system. Combining with manure increased the WUE, the partial factor productivity of N fertilizer (PFPN), and N physiological efficiency (PEN) in both the soybean and maize seasons; conserved soil water (mainly at 40-60 cm); and increased soil N retention (in the upper 60 cm layer), which reduced the risk of N leaching, with a better effect being observed after the application of 13.5 t ha-1 manure. These results provide insight into the potential of using fertilization management strategies that include amendment with 13.5 t ha-1 manure in combination with N, P, and K fertilizer in the maize season and only chemical fertilizer in the soybean season, as these results indicate that such strategies can achieve high yields and be used to implement agricultural sustainable development in brown soil regions in Northeast China.

Association between body mass index and electrocardiogram indices: A Mendelian randomization study.

INTRODUCTION: Cardiovascular diseases (CVDs) remain a global health concern, and body mass index (BMI) is known to be associated with an increased risk of CVD, but the exact mechanisms underlying this relationship remain unclear. This study employs Mendelian randomization (MR) to investigate the causal association between BMI and electrocardiogram (ECG) indices, providing insights into potential pathways linking obesity to CVD. METHODS: We conducted a comprehensive MR study utilizing large-scale genetic and ECG data from diverse populations. Instrumental variables were selected from genome-wide association studies, ensuring their relevance to BMI. Causal relationships between BMI and ECG indices, including P wave duration, PR interval, QRS duration, and QT interval, were assessed using various MR methods, with inverse variance weighted (IVW) considered as the primary analysis. RESULTS: Our MR analysis revealed a significant positive causal association between higher BMI and P wave duration (ß = 8.078, 95% CI: 5.322 to 10.833, p < 0.001), suggesting a potential mechanism through which higher BMI may contribute to arrhythmogenic risks. However, no significant causal associations were observed between BMI and PR interval, QRS duration, or QT interval (all p > 0.005). In addition, our study also found that there is no horizontal pleiotropy between BMI and P wave duration, PR interval, QRS duration, and QT interval, suggesting that the conclusions of this study are robust. CONCLUSION: This study supports a causal relationship between elevated BMI and prolonged P wave duration, a marker of increased atrial arrhythmogenic risk. Further investigations are still needed to elucidate the underlying mechanisms.

Mesenchymal stem cells alleviate mouse liver fibrosis by inhibiting pathogenic function of intrahepatic B cells.

BACKGROUND AIMS: The immunomodulatory characteristics of mesenchymal stem cells (MSCs) make them a promising therapeutic approach for liver fibrosis (LF). Here, we postulated that MSCs could potentially suppress the pro-fibrotic activity of intrahepatic B cells, thereby inhibiting LF progression. APPROACH RESULTS: Administration of MSCs significantly ameliorated LF as indicated by reduced myofibroblast activation, collagen deposition, and inflammation. The treatment efficacy of MSCs can be attributed to decreased infiltration, activation, and pro-inflammatory cytokine production of intrahepatic B cells. Single-cell RNA sequencing revealed a distinct intrahepatic B cell atlas and a subtype of naive B cells (B-II) was identified, which were markedly abundant in fibrotic liver, displaying mature features with elevated expression of several proliferative and inflammatory genes. Transcriptional profiling of total B cells revealed that intrahepatic B cells displayed activation, proliferation, and pro-inflammatory gene profile during LF. Fibrosis was attenuated in mice ablated with B cells (µMT) or in vivo treatment with anti-CD20. Moreover, fibrosis was recapitulated in µMT after adoptive transfer of B cells, which in turn could be rescued by MSC injection, validating the pathogenic function of B cells and the efficacy of MSCs on B cell-promoted LF progression. Mechanistically, MSCs could inhibit the proliferation and cytokine production of intrahepatic B cells through exosomes, regulating the MAPK and NF-kappa B signaling pathways. CONCLUSIONS: Intrahepatic B-cell serve as a target of MSCs, play an important role in the process of MSC-induced amelioration of LF, and may provide new clues for revealing the novel mechanisms of MSC action.

Proportional feature pyramid network based on weight fusion for lane detection.

Lane detection under extreme conditions presents a highly challenging task that requires capturing each crucial pixel to predict the complex topology of lane lines and differentiate the various lane types. Existing methods predominantly rely on deep feature extraction networks with substantial parameters or the fusion of multiple prediction modules, resulting in large model sizes, embedding difficulties, and slow detection speeds. This article proposes a Proportional Feature Pyramid Network (P-FPN) through fusing the weights into the FPN for lane detection. For obtaining a more accurately detecting result, the cross refinement block is introduced in the P-FPN network. The cross refinement block takes the feature maps and anchors as inputs and gradually refines the anchors from high to low level feature maps. In our method, the high-level features are explored to predict lanes coarsely while local-detailed features are leveraged to improve localization accuracy. Extensive experiments on two widely used lane detection datasets, The Chinese Urban Scene Benchmark for Lane Detection (CULane) and the TuSimple Lane Detection Challenge (TuSimple) datasets, demonstrate that the proposed method achieves competitive results compared with several state-of-the-art approaches.

MSCs alleviate LPS-induced acute lung injury by inhibiting the proinflammatory function of macrophages in mouse lung organoid-macrophage model.

Acute lung injury (ALI) is an inflammatory disease associated with alveolar injury, subsequent macrophage activation, inflammatory cell infiltration, and cytokine production. Mesenchymal stem cells (MSCs) are beneficial for application in the treatment of inflammatory diseases due to their immunomodulatory effects. However, the mechanisms of regulatory effects by MSCs on macrophages in ALI need more in-depth study. Lung tissues were collected from mice for mouse lung organoid construction. Alveolar macrophages (AMs) derived from bronchoalveolar lavage and interstitial macrophages (IMs) derived from lung tissue were co-cultured, with novel matrigel-spreading lung organoids to construct an in vitro model of lung organoids-immune cells. Mouse compact bone-derived MSCs were co-cultured with organoids-macrophages to confirm their therapeutic effect on acute lung injury. Changes in transcriptome expression profile were analyzed by RNA sequencing. Well-established lung organoids expressed various lung cell type-specific markers. Lung organoids grown on spreading matrigel had the property of functional cells growing outside the lumen. Lipopolysaccharide (LPS)-induced injury promoted macrophage chemotaxis toward lung organoids and enhanced the expression of inflammation-associated genes in inflammation-injured lung organoids-macrophages compared with controls. Treatment with MSCs inhibited the injury progress and reduced the levels of inflammatory components. Furthermore, through the nuclear factor-κB pathway, MSC treatment inhibited inflammatory and phenotypic transformation of AMs and modulated the antigen-presenting function of IMs, thereby affecting the inflammatory phenotype of lung organoids. Lung organoids grown by spreading matrigel facilitate the reception of external stimuli and the construction of in vitro models containing immune cells, which is a potential novel model for disease research. MSCs exert protective effects against lung injury by regulating different functions of AMs and IMs in the lung, indicating a potential mechanism for therapeutic intervention.

Serum EZH2 is a novel biomarker for bladder cancer diagnosis and prognosis.

Objective: The primary objective of this study was to examine the levels of serum EZH2 in patients diagnosed with bladder cancer, and subsequently evaluate its potential as a biomarker for both the diagnosis and prognosis of bladder cancer. Methods: Blood samples were obtained from 115 bladder cancer patients and 115 healthy persons. We measured the EZH2 concentrations in the serum of these subjects via enzyme-linked immunosorbent assay (ELISA). To assess the diagnostic performance of serum EZH2 in detecting bladder cancer, we plotted receiver operating characteristic (ROC) curves and calculated their corresponding area under the curve (AUC). We also used the Cox regression model and log-rank test to investigate the correlation between EZH2 levels and clinicopathological characteristics, and survival rates of bladder cancer patients. Results: Serum EZH2 levels were significantly higher in bladder cancer patients when compared to those in healthy persons. Serum EZH2 levels exhibited a significant correlation with TNM stage, lymph node metastasis, muscle invasion, and tumor size. At a cutoff value of 8.23 ng/mL, EZH2 was able to differentiate bladder cancer patients from healthy persons, with an AUC of 0.87, a sensitivity of 81.31%, and a specificity of 78.42%. High EZH2 levels correlated with poor overall survival rates and progression-free survival rates of bladder cancer patients. Conclusions: Serum EZH2 levels were elevated in bladder cancer patients, and patients with higher serum EZH2 levels exhibited a poorer prognosis. This indicates that serum EZH2 could be a novel biomarker for bladder cancer diagnosis and prognosis. Such findings could improve the prognosis of bladder cancer patients by facilitating early detection and continuous monitoring.

Prognostic stratification of sepsis through DNA damage response based RiskScore system: insights from single-cell RNA-sequencing and transcriptomic profiling.

Background: A novel risk scoring system, predicated on DNA damage response (DDR), was developed to enhance prognostic predictions and potentially inform the creation of more effective therapeutic protocols for sepsis. Methods: To thoroughly delineate the expression profiles of DDR markers within the context of sepsis, an analytical approach utilizing single-cell RNA-sequencing (scRNA-seq) was implemented. Our study utilized single-cell analysis techniques alongside weighted gene co-expression network analysis (WGCNA) to pinpoint the genes that exhibit the most substantial associations with DNA damage response (DDR). Through Cox proportional hazards LASSO regression, we distinguished DDR-associated genes and established a risk model, enabling the stratification of patients into high- and low-risk groups. Subsequently, we carried out an analysis to determine our model's predictive accuracy regarding patient survival. Moreover, we examined the distinct biological characteristics, various signal transduction routes, and immune system responses in sepsis patients, considering different risk categories and outcomes related to survival. Lastly, we conducted experimental validation of the identified genes through in vivo and in vitro assays, employing RT-PCR, ELISA, and flow cytometry. Results: Both single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses have demonstrated a strong correlation between DNA damage response (DDR) levels and sepsis prognosis. Specific cell subtypes, including monocytes, megakaryocytes, CD4+ T cells, and neutrophils, have shown elevated DDR activity. Cells with increased DDR scores exhibited more robust and numerous interactions with other cell populations. The weighted gene co-expression network analysis (WGCNA) and single-cell analyses revealed 71 DDR-associated genes. We developed a four-gene risk scoring system using ARL4C, CD247, RPL7, and RPL31, identified through univariate COX, LASSO COX regression, and log-rank (Mantel-Cox) tests. Nomograms, calibration plots, and decision curve analyses (DCA) regarding these specific genes have provided significant clinical benefits for individuals diagnosed with sepsis. The study suggested that individuals categorized as lower-risk demonstrated enhanced infiltration of immune cells, upregulated expression of immune regulators, and a more prolific presence of immune-associated functionalities and pathways. RT-qPCR analyses on a sepsis rat model revealed differential gene expression predominantly in the four targeted genes. Furthermore, ARL4C knockdown in sepsis model in vivo and vitro caused increased inflammatory response and a worse prognosis. Conclusion: The delineated DDR expression landscape offers insights into sepsis pathogenesis, whilst our riskScore model, based on a robust four-gene signature, could underpin personalized sepsis treatment strategies.

Intestinal nontuberculous mycobacteria infection: A case report.

BACKGROUND: Intestinal nontuberculous mycobacteriosis due to nontuberculous mycobacteria infection has clinical manifestations similar to intestinal tuberculosis and inflammatory bowel disease, causing difficulties in clinical diagnosis. CASE PRESENTATION: A 42-year-old male patient was admitted to the Sino-Japanese Friendship Hospital of Jilin University in June 2021 for diarrhea and intermittent hematochezia since April 2021. He was diagnosed with inflammatory intestinal disease by colonoscopy and midtransverse colon biopsy. However, the symptoms did not relieve after 2 months of mesalazine treatment. In August 2021, the patient was admitted to the outpatient department for suspected "intestinal tuberculosis." A diagnosis of intestinal nontuberculous mycobacteriosis was confirmed based on pathology and nucleotide-based matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS). After 2 weeks of antimycobacterial therapy, the patient's diarrhea was relieved, and hematochezia no longer appeared. In November 2021, recolonoscopy revealed scattered erosions and ulcers in ileocecal valve and ascending colon, while both nucleotide-based MALDI-TOF MS and next-generation sequencing could still detect Mycobacterium intracellulare. CONCLUSION: This study reported a patient with an intestinal nontuberculous mycobacteriosis diagnosed by colonoscopy biopsy and nucleotide-based MALDI-TOF MS, and symptoms were relieved after antimycobacterial treatment.

Mediating effect of sleep quality on the association between job stress and health-related productivity loss among workers in R&D enterprises in Shanghai.

Background: Past research indicates that occupational stress negatively predicts health-related productivity. Simultaneously, sleep problem among workers may stem from job stress, subsequently leading to a decline in sleep quality and resulting in reduced health productivity. Therefore, this study aims to idenitify whether the sleep quality of employees functions as a mediator in the process through which job stress impacts health productivity. Objectives: This study aimed to assess the status and analyze differences in quality of sleep, job stress, and health-related productivity loss (HRPL) among workers in research and development (R&D) enterprises in Minhang District, Shanghai. We also assessed the mediating effect of sleep quality on the relationship between job stress and HRPL. Methods: A total of 3,216 workers in R&D firms aged between 18 and 60 years participated in this study (mean age 35.15 years; standard deviation 8.44; male-to-female ratio≈2:1). The Nakata Insomnia Questionnaire, the Chinese version of the Brief Job Stress Questionnaire revised edition, and the Chinese version of the Work Productivity and Activity Impairment Questionnaire were used in this study. And the Kruskal-Wallis test, Hierarchical Multiple Regression Analysis, and Path Analysis were utilized for data analysis in this study. Results: There were significant differences in the positive detection rate of insomnia among participants according to age, educational level, marital status, position, length of service, and level of financial difficulties (all P < 0.05). We also found significant differences in the positive detection rate of HRPL among participants according to age, marital status, length of service, and level of financial difficulties (all P < 0.05); participants with insomnia scored higher for HRPL than those without insomnia (6.00 vs. 4.20, P < 0.001). Additionally, participants with job stress problems had higher HRPL than those without these issues (7.00 vs. 4.20, P < 0.001). Our findings suggest that sleep quality plays a mediating role between job stress and HRPL (all P < 0.05). Conclusions: Occupational health professionals must pay particular attention to job stress, sleep quality, and their influencing factors to positively influence the wellbeing of workers while improving productivity.

MSC-derived exosomes attenuate hepatic fibrosis in primary sclerosing cholangitis through inhibition of Th17 differentiation.

Primary sclerosing cholangitis (PSC) is an autoimmune cholangiopathy characterized by chronic inflammation of the biliary epithelium and periductal fibrosis, with no curative treatment available, and liver transplantation is inevitable for end-stage patients. Human placental mesenchymal stem cell (hpMSC)-derived exosomes have demonstrated the ability to prevent fibrosis, inhibit collagen production and possess immunomodulatory properties in autoimmune liver disease. Here, we prepared hpMSC-derived exosomes (ExoMSC) and further investigated the anti-fibrotic effects and detailed mechanism on PSC based on Mdr2-/- mice and multicellular organoids established from PSC patients. The results showed that ExoMSC ameliorated liver fibrosis in Mdr2-/- mice with significant collagen reduction in the preductal area where Th17 differentiation was inhibited as demonstrated by RNAseq analysis, and the percentage of CD4+IL-17A+T cells was reduced both in ExoMSC-treated Mdr2-/- mice (Mdr2-/--Exo) in vivo and ExoMSC-treated Th17 differentiation progressed in vitro. Furthermore, ExoMSC improved the hypersecretory phenotype and intercellular interactions in the hepatic Th17 microenvironment by regulating PERK/CHOP signaling as supported by multicellular organoids. Thus, our data demonstrate the anti-fibrosis effect of ExoMSC in PSC disease by inhibiting Th17 differentiation, and ameliorating the Th17-induced microenvironment, indicating the promising potential therapeutic role of ExoMSC in liver fibrosis of PSC or Th17-related diseases.

Role of Ubiquitin-specific Proteases in Hepatocellular Carcinoma Pathogenesis.

Signaling pathways in hepatocellular carcinoma are primarily mediated by the phosphorylation and ubiquitination of post-translational proteins. In mammalian cells, ubiquitin-specific proteases (USPs) account for the majority of protein deubiquitination activities. In addition to transcriptional and post-translational regulation, ubiquitination plays an important role in the regulation of key proteins. There is a possibility that altered biological processes may lead to serious human diseases, including cancer. Recent studies have revealed the role of USPs in hepatocellular carcinoma tumorigenesis. The purpose of this review is to summarize the involvement of this class of enzymes in the regulation of cell signaling in hepatocellular carcinoma and the therapeutic development of inhibitors that target USPs, which may lead to novel therapies to treat hepatocellular carcinoma.

Learning from Human Educational Wisdom: A Student-Centered Knowledge Distillation Method.

Existing studies on knowledge distillation typically focus on teacher-centered methods, in which the teacher network is trained according to its own standards before transferring the learned knowledge to a student one. However, due to differences in network structure between the teacher and the student, the knowledge learned by the former may not be desired by the latter. Inspired by human educational wisdom, this paper proposes a Student-Centered Distillation (SCD) method that enables the teacher network to adjust its knowledge transfer according to the student network's needs. We implemented SCD based on various human educational wisdom, e.g., the teacher network identified and learned the knowledge desired by the student network on the validation set, and then transferred it to the latter through the training set. To address the problems of current deficiency knowledge, hard sample learning and knowledge forgetting faced by a student network in the learning process, we introduce and improve Proportional-Integral-Derivative (PID) algorithms from automation fields to make them effective in identifying the current knowledge required by the student network. Furthermore, we propose a curriculum learning-based fuzzy strategy and apply it to the proposed PID control algorithm, such that the student network in SCD can actively pay attention to the learning of challenging samples after with certain knowledge. The overall performance of SCD is verified in multiple tasks by comparing it with state-of-the-art ones. Experimental results show that our student-centered distillation method outperforms existing teacher-centered ones.

Genome-wide meta-analysis, functional genomics and integrative analyses implicate new risk genes and therapeutic targets for anxiety disorders.

Anxiety disorders are the most prevalent mental disorders. However, the genetic etiology of anxiety disorders remains largely unknown. Here we conducted a genome-wide meta-analysis on anxiety disorders by including 74,973 (28,392 proxy) cases and 400,243 (146,771 proxy) controls. We identified 14 risk loci, including 10 new associations near CNTNAP5, MAP2, RAB9BP1, BTN1A1, PRR16, PCLO, PTPRD, FARP1, CDH2 and RAB27B. Functional genomics and fine-mapping pinpointed the potential causal variants, and expression quantitative trait loci analysis revealed the potential target genes regulated by the risk variants. Integrative analyses, including transcriptome-wide association study, proteome-wide association study and colocalization analyses, prioritized potential causal genes (including CTNND1 and RAB27B). Evidence from multiple analyses revealed possibly causal genes, including RAB27B, BTN3A2, PCLO and CTNND1. Finally, we showed that Ctnnd1 knockdown affected dendritic spine density and resulted in anxiety-like behaviours in mice, revealing the potential role of CTNND1 in anxiety disorders. Our study identified new risk loci, potential causal variants and genes for anxiety disorders, providing insights into the genetic architecture of anxiety disorders and potential therapeutic targets.

A lightweight speech recognition method with target-swap knowledge distillation for Mandarin air traffic control communications.

Miscommunications between air traffic controllers (ATCOs) and pilots in air traffic control (ATC) may lead to catastrophic aviation accidents. Thanks to advances in speech and language processing, automatic speech recognition (ASR) is an appealing approach to prevent misunderstandings. To allow ATCOs and pilots sufficient time to respond instantly and effectively, the ASR systems for ATC must have both superior recognition performance and low transcription latency. However, most existing ASR works for ATC are primarily concerned with recognition performance while paying little attention to recognition speed, which motivates the research in this article. To address this issue, this article introduces knowledge distillation into the ASR for Mandarin ATC communications to enhance the generalization performance of the light model. Specifically, we propose a simple yet effective lightweight strategy, named Target-Swap Knowledge Distillation (TSKD), which swaps the logit output of the teacher and student models for the target class. It can mitigate the potential overconfidence of the teacher model regarding the target class and enable the student model to concentrate on the distillation of knowledge from non-target classes. Extensive experiments are conducted to demonstrate the effectiveness of the proposed TSKD in homogeneous and heterogeneous architectures. The experimental results reveal that the generated lightweight ASR model achieves a balance between recognition accuracy and transcription latency.

An improved memetic algorithm to solve the energy-efficient distributed flexible job shop scheduling problem with transportation and start-stop constraints.

In the current global cooperative production environment, modern industries are confronted with intricate production plans, demanding the adoption of contemporary production scheduling strategies. Within this context, distributed manufacturing has emerged as a prominent trend. Manufacturing enterprises, especially those engaged in activities like automotive mold production and welding, are facing a significant challenge in managing a significant amount of small-scale tasks characterized by short processing times. In this situation, it becomes imperative to consider the transportation time of jobs between machines. This paper simultaneously considers the transportation time of jobs between machines and the start-stop operation of the machines, which is the first time to our knowledge. An improved memetic algorithm (IMA) is proposed to solve the multi-objective distributed flexible job shop scheduling problem (MODFJSP) with the goal of minimizing maximum completion time and energy consumption. Then, a new multi-start simulated annealing algorithm is proposed and integrated into the IMA to improve the exploration ability and diversity of the algorithm. Furthermore, a new multiple-initialization rule is designed to enhance the quality of the initial population. Additionally, four improved variable neighborhood search strategies and two energy-saving strategies are designed to enhance the search ability and reduce energy consumption. To verify the effectiveness of the IMA, we conducted extensive testing and comprehensive evaluation on 20 instances. The results indicate that, when faced with the MODFJSP, the IMA can achieve better solutions in almost all instances, which is of great significance for the improvement of production scheduling in intelligent manufacturing.

Antioxidant and Antiproliferative Activities of Eclipta prostrata (L.) L. Extract and Isolated Compounds.

The primary objective of this study was to elucidate the chemical composition, antioxidant properties, and antiproliferative activities of Eclipta prostrata extracts. Two flavonoids, 3'-O-methylorobol and apigenin 7-sulfate, were isolated from the ethyl acetate (EtOAc) extract of E. prostrata. The total phenolic and flavonoid contents of the E. prostrata extracts, as well as their overall antioxidant activities as measured using the 2,2-diphenyl-1-picrylhydrazyl and reducing power assays, were investigated. The E. prostrata EtOAc extract exhibited significantly greater antioxidant activities in both assays and higher phenol and flavonoid contents than the other extracts. The potential antiproliferative properties of the E. prostrata extracts and isolated compounds were investigated in vitro against the AGS, A549, and HT-29 cancer cell lines and the normal human HEK-293 cell line using the MTT assay. Annexin V-FITC/PI staining analysis and quantitative real-time PCR were used to assess AGS cell apoptosis. At a concentration of 100 µg/mL, the EtOAc extract of E. prostrata reduced AGS cell viability and proliferation by inducing apoptosis through the alteration of gene expression in the apoptotic cascade. These results highlight E. prostrata as a promising source of anticancer compounds.

Non-coding RNAs: The potential biomarker or therapeutic target in hepatic ischemia-reperfusion injury.

Hepatic ischemia-reperfusion injury (HIRI) is the major complication of liver surgery and liver transplantation, that may increase the postoperative morbidity, mortality, tumor progression, and metastasis. The underlying mechanisms have been extensively investigated in recent years. Among these, oxidative stress, inflammatory responses, immunoreactions, and cell death are the most studied. Non-coding RNAs (ncRNAs) are defined as the RNAs that do not encode proteins, but can regulate gene expressions. In recent years, ncRNAs have emerged as research hotspots for various diseases. During the progression of HIRI, ncRNAs are differentially expressed, while these dysregulations of ncRNAs, in turn, have been verified to be related to the above pathological processes involved in HIRI. ncRNAs mainly contain microRNAs, long ncRNAs, and circular RNAs, some of which have been reported as biomarkers for early diagnosis or assessment of liver damage severity, and as therapeutic targets to attenuate HIRI. Here, we briefly summarize the common pathophysiology of HIRI, describe the current knowledge of ncRNAs involved in HIRI in animal and human studies, and discuss the potential of ncRNA-targeted therapeutic strategies. Given the scarcity of clinical trials, there is still a long way to go from pre-clinical to clinical application, and further studies are needed to uncover their potential as therapeutic targets.

Graph embedding based multi-label Zero-shot Learning.

Multi-label Zero-shot Learning (ZSL) is more reasonable and realistic than standard single-label ZSL because several objects can co-exist in a natural image in real scenarios. Intra-class feature entanglement is a significant factor influencing the alignment of visual and semantic features, resulting in the model's inability to recognize unseen samples comprehensively and completely. We observe that existing multi-label ZSL methods place a greater emphasis on attention-based refinement and decoupling of visual features, while ignoring the relationship between label semantics. Relying on label correlations to solve multi-label ZSL tasks has not been deeply studied. In this paper, we make full use of the co-occurrence relationship between category labels and build a directed weighted semantic graph based on statistics and prior knowledge, in which node features represent category semantics and weighted edges represent conditional probabilities of label co-occurrence. To guide the targeted extraction of visual features, node features and edge set weights are simultaneously updated and refined, and embedded into the visual feature extraction network from a global and local perspective. The proposed method's effectiveness was demonstrated by simulation results on two challenging multi-label ZSL benchmarks: NUS-WIDE and Open Images. In comparison to state-of-the-art models, our model achieves an absolute gain of 2.4% mAP on NUS-WIDE and 2.1% mAP on Open Images respectively.

Habit-DisHabit Design with a Quadratic Equation: A Better Model of the Hemodynamic Changes in Preschoolers during the Dimension Change Card Sorting Task.

General linear modeling (GLM) has been widely employed to estimate the hemodynamic changes observed by functional near infrared spectroscopy (fNIRS) technology, which are found to be nonlinear rather than linear, however. Therefore, GLM might not be appropriate for modeling the hemodynamic changes evoked by cognitive processing in developmental neurocognitive studies. There is an urgent need to identify a better statistical model to fit into the nonlinear fNIRS data. This study addressed this need by developing a quadratic equation model to reanalyze the existing fNIRS data (N = 38, Mage = 5.0 years, SD = 0.69 years, 17 girls) collected from the mixed-order design Dimensional Change Card Sort (DCCS) task and verified the model with a new set of data with the Habit-DisHabit design. First, comparing the quadratic and cubic modeling results of the mixed-order design data indicated that the proposed quadratic equation was better than GLM and cubic regression to model the oxygenated hemoglobin (HbO) changes in this task. Second, applying this quadratic model with the Habit-DisHabit design data verified its suitability and indicated that the new design was more effective in identifying the neural correlates of cognitive shifting than the mixed-order design. These findings jointly indicate that Habit-DisHabit Design with a quadratic equation might better model the hemodynamic changes in preschoolers during the DCCS task.