Seafloor primary production in a changing Arctic Ocean.

Phytoplankton and sea ice algae are traditionally considered to be the main primary producers in the Arctic Ocean. In this Perspective, we explore the importance of benthic primary producers (BPPs) encompassing microalgae, macroalgae, and seagrasses, which represent a poorly quantified source of Arctic marine primary production. Despite scarce observations, models predict that BPPs are widespread, colonizing ~3 million km2 of the extensive Arctic coastal and shelf seas. Using a synthesis of published data and a novel model, we estimate that BPPs currently contribute ~77 Tg C y-1 of primary production to the Arctic, equivalent to ~20 to 35% of annual phytoplankton production. Macroalgae contribute ~43 Tg C y-1, seagrasses contribute ~23 Tg C y-1, and microalgae-dominated shelf habitats contribute ~11 to 16 Tg C y-1. Since 2003, the Arctic seafloor area exposed to sunlight has increased by ~47,000 km2 y-1, expanding the realm of BPPs in a warming Arctic. Increased macrophyte abundance and productivity is expected along Arctic coastlines with continued ocean warming and sea ice loss. However, microalgal benthic primary production has increased in only a few shelf regions despite substantial sea ice loss over the past 20 y, as higher solar irradiance in the ice-free ocean is counterbalanced by reduced water transparency. This suggests complex impacts of climate change on Arctic light availability and marine primary production. Despite significant knowledge gaps on Arctic BPPs, their widespread presence and obvious contribution to coastal and shelf ecosystem production call for further investigation and for their inclusion in Arctic ecosystem models and carbon budgets.

CORN-Condition Orientated Regulatory Networks: bridging conditions to gene networks.

A transcriptional regulatory network (TRN) is a collection of transcription regulators with their associated downstream genes, which is highly condition-specific. Understanding how cell states can be programmed through small molecules/drugs or conditions by modulating the whole gene expression system granted us the potential to amend abnormal cells and cure diseases. Condition Orientated Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/home) is a library of condition (small molecule/drug treatments and gene knockdowns)-based transcriptional regulatory sub-networks (TRSNs) that come with an online TRSN matching tool. It allows users to browse condition-associated TRSNs or match those TRSNs by inputting transcriptomic changes of interest. CORN utilizes transcriptomic changes data after specific conditional treatment in cells, and in vivo transcription factor (TF) binding data in cells, by combining TF binding information and calculations of significant expression alterations of TFs and genes after the conditional treatments, TRNs under the effect of different conditions were constructed. In short, CORN associated 1805 different types of specific conditions (small molecule/drug treatments and gene knockdowns) to 9553 TRSNs in 25 human cell lines, involving 204TFs. By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This study demonstrated with examples that CORN can aid the understanding of molecular pathology, pharmacology and drug repositioning, and screened drugs with high potential for cancer and coronavirus disease 2019 (COVID-19) treatments.

Integrative analysis of individual-level data and high-dimensional summary statistics.

MOTIVATION: Researchers usually conduct statistical analyses based on models built on raw data collected from individual participants (individual-level data). There is a growing interest in enhancing inference efficiency by incorporating aggregated summary information from other sources, such as summary statistics on genetic markers' marginal associations with a given trait generated from genome-wide association studies. However, combining high-dimensional summary data with individual-level data using existing integrative procedures can be challenging due to various numeric issues in optimizing an objective function over a large number of unknown parameters. RESULTS: We develop a procedure to improve the fitting of a targeted statistical model by leveraging external summary data for more efficient statistical inference (both effect estimation and hypothesis testing). To make this procedure scalable to high-dimensional summary data, we propose a divide-and-conquer strategy by breaking the task into easier parallel jobs, each fitting the targeted model by integrating the individual-level data with a small proportion of summary data. We obtain the final estimates of model parameters by pooling results from multiple fitted models through the minimum distance estimation procedure. We improve the procedure for a general class of additive models commonly encountered in genetic studies. We further expand these two approaches to integrate individual-level and high-dimensional summary data from different study populations. We demonstrate the advantage of the proposed methods through simulations and an application to the study of the effect on pancreatic cancer risk by the polygenic risk score defined by BMI-associated genetic markers. AVAILABILITY AND IMPLEMENTATION: R package is available at https://github.com/fushengstat/MetaGIM.

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 and venous thromboembolism.

BACKGROUND: A growing body of research has shown that patients with coronavirus disease 2019 (COVID-19) have significantly higher rates of venous thromboembolism (VTE) than healthy. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication. METHODS: The gene expression profiles of COVID-19 and VTE were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for COVID-19 and VTE, functional annotation, a protein-protein interactions (PPI) network, module construction, and hub gene identification were performed. Finally, we constructed a transcription factor (TF)-gene regulatory network and a TF-miRNA regulatory network for hub genes. RESULTS: A total of 42 common DEGs were selected for subsequent analyses. Functional analyses showed that biological function and signaling pathways collectively participated in the development and progression of VTE and COVID-19. Finally, 8 significant hub genes were identified using the cytoHubba plugin, including RSL24D1, RPS17, RPS27, HINT1, COX7C, RPL35, RPL34, and NDUFA4, which had preferable values as diagnostic markers for COVID-19 and VTE. CONCLUSIONS: Our study revealed the common pathogenesis of COVID-19 and VTE. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

Curcumin blunts epithelial-mesenchymal transition to alleviate invasion and metastasis of prostate cancer through the JARID1D demethylation.

Prostate cancer (PCa) is one of the most common and prevalent cancers in men worldwide. The majority of PCa-related deaths result from metastasis rather than primary tumors. Several studies have focused on the relationship between male-specific genes encoded on the Y chromosome and PCa metastasis; however, the relationship between the male specific protein encoded on the Y chromosome and tumor suppression has not been fully clarified. Here, we report a male specific protein of this type, the histone H3 lysine 4 (H3K4) demethylase JARID1D, which has the ability to inhibit the gene expression program related to cell invasion, and can thus form a phenotype that inhibits the invasion of PCa cells. However, JARID1D exhibits low expression level in advanced PCa, and which is related to rapid invasion and metastasis in patients with PCa. Curcumin, as a multi-target drug, can enhance the expression and demethylation activity of JARID1D, affect the androgen receptor (AR) and epithelial-mesenchymal transition (EMT) signaling cascade, and inhibit the metastatic potential of castration resistant cancer (CRPC). These findings suggest that using curcumin to increase the expression and demethylation activity of JARID1D may be a feasible strategy to inhibit PCa metastasis by regulating EMT and AR.

Improve the model of disease subtype heterogeneity by leveraging external summary data.

Researchers are often interested in understanding the disease subtype heterogeneity by testing whether a risk exposure has the same level of effect on different disease subtypes. The polytomous logistic regression (PLR) model provides a flexible tool for such an evaluation. Disease subtype heterogeneity can also be investigated with a case-only study that uses a case-case comparison procedure to directly assess the difference between risk effects on two disease subtypes. Motivated by a large consortium project on the genetic basis of non-Hodgkin lymphoma (NHL) subtypes, we develop PolyGIM, a procedure to fit the PLR model by integrating individual-level data with summary data extracted from multiple studies under different designs. The summary data consist of coefficient estimates from working logistic regression models established by external studies. Examples of the working model include the case-case comparison model and the case-control comparison model, which compares the control group with a subtype group or a broad disease group formed by merging several subtypes. PolyGIM efficiently evaluates risk effects and provides a powerful test for disease subtype heterogeneity in situations when only summary data, instead of individual-level data, is available from external studies due to various informatics and privacy constraints. We investigate the theoretic properties of PolyGIM and use simulation studies to demonstrate its advantages. Using data from eight genome-wide association studies within the NHL consortium, we apply it to study the effect of the polygenic risk score defined by a lymphoid malignancy on the risks of four NHL subtypes. These results show that PolyGIM can be a valuable tool for pooling data from multiple sources for a more coherent evaluation of disease subtype heterogeneity.

Targeting EGFR Exon 20 Insertion Mutations in Non-small-Cell Lung Cancer: Changes in Treatment Strategies are Coming.

Epidermal growth factor receptor (EGFR) exon 20 insertion (ex20ins) mutations are the third most frequent EGFR mutation type, following only exon 19 deletions and exon 21 L858R point mutations. EGFR ex20ins mutations are found in approximately 4%-12% of all EGFR-positive non-small cell lung cancers (NSCLCs). Unlike classical EGFR mutations, EGFR ex20ins mutations display remarkable subtype diversity and heterogeneity. Patients harboring these mutations generally have an inferior prognosis because of insensitivity to conventional treatment approaches such as immunotherapy, chemotherapy, and targeted therapy. Consequently, there remains a significant unmet medical need for efficacious treatments. Recently, amivantamab and sunvozertinib have demonstrated notable efficacy as first-line treatments, and several other promising novel targeted drugs are also challenging the status quo of traditional first-line platinum-based chemotherapy regimens. These developments are anticipated to further improve survival outcomes for NSCLC patients with EGFR ex20ins mutations. Hence, this review summarizes the epidemiology, molecular attributes, detection methodologies, and therapeutic advancements for EGFR ex20ins mutations in NSCLC, and briefly discusses the mechanisms of drug resistance.

Likelihood adaptively incorporated external aggregate information with uncertainty for survival data.

Population-based cancer registry databases are critical resources to bridge the information gap that results from a lack of sufficient statistical power from primary cohort data with small to moderate sample size. Although comprehensive data associated with tumor biomarkers often remain either unavailable or inconsistently measured in these registry databases, aggregate survival information sourced from these repositories has been well documented and publicly accessible. An appealing option is to integrate the aggregate survival information from the registry data with the primary cohort to enhance the evaluation of treatment impacts or prediction of survival outcomes across distinct tumor subtypes. Nevertheless, for rare types of cancer, even the sample sizes of cancer registries remain modest. The variability linked to the aggregated statistics could be non-negligible compared with the sample variation of the primary cohort. In response, we propose an externally informed likelihood approach, which facilitates the linkage between the primary cohort and external aggregate data, with consideration of the variation from aggregate information. We establish the asymptotic properties of the estimators and evaluate the finite sample performance via simulation studies. Through the application of our proposed method, we integrate data from the cohort of inflammatory breast cancer (IBC) patients at the University of Texas MD Anderson Cancer Center with aggregate survival data from the National Cancer Data Base, enabling us to appraise the effect of tri-modality treatment on survival across various tumor subtypes of IBC.

Efficient data integration under prior probability shift.

Conventional supervised learning usually operates under the premise that data are collected from the same underlying population. However, challenges may arise when integrating new data from different populations, resulting in a phenomenon known as dataset shift. This paper focuses on prior probability shift, where the distribution of the outcome varies across datasets but the conditional distribution of features given the outcome remains the same. To tackle the challenges posed by such shift, we propose an estimation algorithm that can efficiently combine information from multiple sources. Unlike existing methods that are restricted to discrete outcomes, the proposed approach accommodates both discrete and continuous outcomes. It also handles high-dimensional covariate vectors through variable selection using an adaptive least absolute shrinkage and selection operator penalty, producing efficient estimates that possess the oracle property. Moreover, a novel semiparametric likelihood ratio test is proposed to check the validity of prior probability shift assumptions by embedding the null conditional density function into Neyman's smooth alternatives (Neyman, 1937) and testing study-specific parameters. We demonstrate the effectiveness of our proposed method through extensive simulations and a real data example. The proposed methods serve as a useful addition to the repertoire of tools for dealing dataset shifts.

Integrating external summary information in the presence of prior probability shift: an application to assessing essential hypertension.

Recent years have witnessed a rise in the popularity of information integration without sharing of raw data. By leveraging and incorporating summary information from external sources, internal studies can achieve enhanced estimation efficiency and prediction accuracy. However, a noteworthy challenge in utilizing summary-level information is accommodating the inherent heterogeneity across diverse data sources. In this study, we delve into the issue of prior probability shift between two cohorts, wherein the difference of two data distributions depends on the outcome. We introduce a novel semi-parametric constrained optimization-based approach to integrate information within this framework, which has not been extensively explored in existing literature. Our proposed method tackles the prior probability shift by introducing the outcome-dependent selection function and effectively addresses the estimation uncertainty associated with summary information from the external source. Our approach facilitates valid inference even in the absence of a known variance-covariance estimate from the external source. Through extensive simulation studies, we observe the superiority of our method over existing ones, showcasing minimal estimation bias and reduced variance for both binary and continuous outcomes. We further demonstrate the utility of our method through its application in investigating risk factors related to essential hypertension, where the reduced estimation variability is observed after integrating summary information from an external data.

Visible-Light-Induced Photoredox 1,2-Dialkylation of Styrenes with α-Carbonyl Alkyl Bromides and Pyridin-1-ium Salts.

A visible-light-driven photoredox dialkylation of styrenes with α-carbonyl alkyl bromides and pyridin-1-ium salts for the synthesis of polysubstituted 1,4-dihydropyridines is reported. This reaction enables the formation of two new C(sp3)-C(sp3) bonds in a single reaction step and provides a strategy that employs pyridin-1-ium salts as the functionalized alkylating reagents via dearomatization to directly trap the resulting alkyl radicals from radical addition of alkenes and then terminate the alkene dialkylation.

Nickel-Catalyzed Reductive Cross-Coupling of Propargylic Acetates with Chloro(vinyl)silanes: Access to Silylallenes.

Because of their various reactivities, propargyl acetates are refined chemical intermediates that are extensively applied in pharmaceutical synthesis. Currently, reactions between propargyl acetates and chlorosilanes may be the most effective method for synthesizing silylallenes. Nevertheless, owing to the adaptability and selectivity of substrates, transition metal catalysis is difficult to achieve. Herein, nickel-catalyzed reductive cross-coupling reactions between propargyl acetates and substituted vinyl chlorosilanes for the synthesis of tetrasubstituted silylallenes are described. Therein, metallic zinc is a crucial reductant that effectively enables two electrophilic reagents to selectively construct C(sp2)-Si bonds. Additionally, a Ni-catalyzed reductive mechanism involving a radical process is proposed on the basis of deuteration-labeled experiments.

The role of microbiota in gastric cancer: A comprehensive review.

BACKGROUND: Gastric cancer (GC) continues to pose a significant global threat in terms of cancer-related fatalities. Despite notable advancements in medical research and therapies, further investigation is warranted to elucidate its underlying etiology and risk factors. Recent times have witnessed an escalated emphasis on comprehending the role of the microbiota in cancer development. METHODS: This review briefly delves into recent developments in microbiome-related research pertaining to gastric cancer. RESULTS: According to studies, the microbiota can influence GC growth by inciting inflammation, disrupting immunological processes, and generating harmful microbial metabolites. Furthermore, there is ongoing research into how the microbiome can impact a patient's response to chemotherapy and immunotherapy. CONCLUSION: The utilization of the microbiome for detecting, preventing, and managing stomach cancer remains an active area of exploration.

Impact of crosslinking agents with steric cyclic groups on the properties of polymer-dispersed liquid crystals.

As a type of intelligent dimming film, polymer-dispersed liquid crystals (PDLCs) have been widely applied in various fields, such as smart windows, light shutters and displays. The properties of PDLCs are greatly influenced by the structure of the raw materials. In this work, the impact of crosslinking agents with different cyclic or chain groups was investigated by comparing the electro-optical performance and the morphology of the polymer matrix in the as-made PDLC films. It was found that the incorporation of large steric groups into the crosslinking agents can alter the morphology of the polymer matrix and thus affect the electro-optical properties. However, the impact is distinct when the spatial structure or rigidity is different. Besides, a combination of crosslinking agents with flexible alkyl-chain structures and steric structures can further reduce the threshold voltage while keeping the high contrast ratio. After detailed comparison, an optimized combination of BDDA/TCDDA in a weight ratio of 1/1 is selected to demonstrate the enhanced properties of the as-constructed film with a thickness of 20 µm. It exhibits low threshold voltage (8.2 V), low saturation voltage (21.2 V) and a high contrast ratio (203) simultaneously. This research offers an optimizing method from the crosslinking agent perspective and is anticipated to promote the further improvement of the PDLC's performance.

Regulation of the PD-1/PD-L1 Axis and NK Cell Dysfunction by Exosomal miR-552-5p in Gastric Cancer.

OBJECTIVE: NK cells play a vital role in tumor immune resistance. Various factors affect NK cell activity. While NK cell dysfunction has been observed in numerous malignancies, the underlying mechanisms in gastric cancer remain unclear. METHOD: Flow cytometry was used to identify the phenotypic distribution and expression of activated receptors on NK cells. ELISA was used to determine the expression of cytokines. We examined the expression of NK cell-related genes and explored their association with survival and prognosis. Additionally, we conducted PCR detection of miR-552-5p expression levels in plasma exosomes of patients and investigated its correlation with phenotypic distribution and activated receptors. We used flow cytometry and ELISA to verify the role of miR-552-5p in NK cell dysfunction. Furthermore, we investigated the potential role of PD-1/PD-L1 in regulating NK cell dysfunction in patients' cells. RESULTS: We observed a significant decrease in the percentage of NKG2D and NKp30 and IFN-γ and TNF-α in patients than in healthy volunteers. Patients with low levels of CD56, CD16, NKG2D, and NKP46 exhibited poorer survival prognoses. Moreover, increased expression levels of plasma exosomal miR-552-5p in patients were negatively associated with NK cell phenotypic distribution and activated receptor expression. MiR-552-5p downregulated the secretion of perforin, granzyme, and IFN-γ as well as the expression of NKp30, NKp46, and NKG2D. Additionally, it suppressed the cytotoxicity of NK cells. The inhibitory effect of miR-552-5p, on NK cell function was reversed when anti-PD-L1 antibodies were used. CONCLUSION: Exosomal miR-552-5p targets the PD-1/PD-L1 axis, leading to impaired NK cell function.

Face recognition-driven video game for dysphagia rehabilitation in stroke patients: a pilot randomized controlled trial.

OBJECTIVE: To explore the feasibility and effectiveness of face recognition-driven video game (FR-VG) swallowing training for stroke patients with dysphagia. DESIGN: A single-blind pilot randomized controlled trial. SETTING: A rehabilitation center. PARTICIPANTS: Stroke patients with dysphagia (N=26). INTERVENTIONS: Participants in the intervention group were trained using FR-VG, while the control group used the conventional method (i.e. lip exercise, tongue exercise, and lower jaw exercise). The training was conducted five days a week over four weeks. OUTCOME MEASURES: The swallowing function and swallowing-related quality of life between the two groups were observed before and after the intervention. The acceptance of FR-VG in the intervention group and the adherence of the patients in the two groups after the intervention were analyzed. RESULTS: A total of 26 stroke patients with dysphagia were included. The results showed that after the intervention, both groups exhibited significant improvements in swallowing function and swallowing-related quality of life compared to the pre-intervention (p < 0.05). Patients in the intervention group demonstrated better swallowing function than the control group on the Gugging swallowing screen (p = 0.015) and functional oral intake scale (p = 0.004). The intervention group had high acceptance of the FR-VG training and had significantly better adherence compared to the control group (p = 0.032). CONCLUSIONS: FR-VG rehabilitation training can help improve swallowing function, swallowing-related quality of life, and training adherence in stroke patients with dysphagia. Patients have a high acceptance of FR-VG rehabilitation training, which can be used as an adjunctive method to conventional rehabilitation.

Loss of ß-arrestin2 aggravated condylar cartilage degeneration at the early stage of temporomandibular joint osteoarthritis.

OBJECTIVE: Temporomandibular joint osteoarthritis (TMJOA) is a chronic degenerative joint disorder characterized by extracellular matrix degeneration and inflammatory response of condylar cartilage. ß-arrestin2 is an important regulator of inflammation response, while its role in TMJOA remains unknown. The objective of this study was to investigate the role of ß-arrestin2 in the development of TMJOA at the early stage and the underlying mechanism. METHODS: A unilateral anterior crossbite (UAC) model was established on eight-week-old wild-type (WT) and ß-arrestin2 deficiency mice to simulate the progression of TMJOA. Hematoxylin-eosin (HE) staining and microcomputed tomography (micro-CT) analysis were used for histological and radiographic assessment. Immunohistochemistry was performed to detect the expression of inflammatory and degradative cytokines, as well as autophagy related factors. Terminal-deoxynucleotidyl transferase mediated nick end labeling (TUNEL) assay was carried out to assess chondrocyte apoptosis. RESULTS: The loss of ß-arrestin2 aggravated cartilage degeneration and subchondral bone destruction in the model of TMJOA at the early stage. Furthermore, in UAC groups, the expressions of degradative (Col-X) and inflammatory (TNF-α and IL-1ß) factors in condylar cartilage were increased in ß-arrestin2 null mice compared with WT mice. Moreover, the loss of ß-arrestin2 promoted apoptosis and autophagic process of chondrocytes at the early stage of TMJOA. CONCLUSION: In conclusion, we demonstrated for the first time that ß-arrestin2 plays a protective role in the development of TMJOA at the early stage, probably by inhibiting apoptosis and autophagic process of chondrocytes. Therefore, ß-arrestin2 might be a potential therapeutic target for TMJOA, providing a new insight for the treatment of TMJOA at the early stage.

Effects of Virtual Reality Motor-Cognitive Training for Older People With Cognitive Frailty: Multicentered Randomized Controlled Trial.

BACKGROUND: Cognitive frailty refers to a clinical syndrome in which physical frailty and mild cognitive impairment coexist. Motor-cognitive training and virtual reality (VR) have been used to launch various therapeutic modalities to promote health in older people. The literature advocates that motor-cognitive training and VR are effective in promoting the cognitive and physical function of older people. However, the effects on older people with cognitive frailty are unclear. OBJECTIVE: This study examined the effects of VR motor-cognitive training (VRMCT) on global cognitive function, physical frailty, walking speed, visual short-term memory, inhibition of cognitive interference, and executive function in older people with cognitive frailty. METHODS: This study used a multicentered, assessor-blinded, 2-parallel-group randomized controlled trial design. Participants were recruited face-to-face in 8 older adult community centers. Eligible participants were aged ≥60 years, were community dwelling, lived with cognitive frailty, had no dementia, and were not mobility restricted. In the intervention group, participants received VRMCT led by interventionists with 16 one-hour training sessions delivered twice per week for 8 weeks. In the control group, participants received the usual care provided by the older adult community centers that the investigators did not interfere with. The primary outcome was global cognitive function. The secondary outcomes included physical frailty, walking speed, verbal short-term memory, inhibition of cognitive interference, and executive function. Data were collected at baseline (T0) and the week after the intervention (T1). Generalized estimating equations were used to examine the group, time, and interaction (time × group) effects on the outcomes. RESULTS: In total, 293 eligible participants enrolled in the study. The mean age of the participants was 74.5 (SD 6.8) years. Most participants were female (229/293, 78.2%), had completed primary education (152/293, 52.1%), were married (167/293, 57.2%), lived with friends (127/293, 43.3%), and had no VR experience (232/293, 79.5%). In the intervention group, 81.6% (119/146) of participants attended >80% (13/16, 81%) of the total number of sessions. A negligible number of participants experienced VR sickness symptoms (1/146, 0.7% to 5/146, 3%). VRMCT was effective in promoting global cognitive function (interaction effect: P=.03), marginally promoting executive function (interaction effect: P=.07), and reducing frailty (interaction effect: P=.03). The effects were not statistically significant on other outcomes. CONCLUSIONS: VRMCT is effective in promoting cognitive functions and reducing physical frailty and is well tolerated and accepted by older people with cognitive frailty, as evidenced by its high attendance rate and negligible VR sickness symptoms. Further studies should examine the efficacy of the intervention components (eg, VR vs non-VR or dual task vs single task) on health outcomes, the effect of using technology on intervention adherence, and the long-term effects of the intervention on older people with cognitive frailty at the level of daily living. TRIAL REGISTRATION: ClinicalTrials.gov NCT04730817; https://clinicaltrials.gov/study/NCT04730817.

Investigating the Pharmacological Mechanisms of Total Flavonoids from Eucommia ulmoides Oliver Leaves for Ischemic Stroke Protection.

The aim of this study was to explore how the total flavonoids from Eucommia ulmoides leaves (EULs) regulate ischemia-induced nerve damage, as well as the protective effects mediated by oxidative stress. The cell survival rate was significantly improved compared to the ischemic group (p < 0.05) after treatment with the total flavonoids of EULs. The levels of reactive oxygen species (ROS), lactate dehydrogenase (LDH), and malondialdehyde (MDA) decreased, while catalase (CAT) and glutathione (GSH) increased, indicating that the total flavonoids of EULs can significantly alleviate neurological damage caused by ischemic stroke by inhibiting oxidative stress (p < 0.01). The mRNA expression level of VEGF increased (p < 0.01), which was consistent with the protein expression results. Meanwhile, the protein expression of ERK and CCND1 increased (p < 0.01), suggesting that the total flavonoids of EULs could protect PC12 cells from ischemic injury via VEGF-related pathways. MCAO rat models indicated that the total flavonoids of EULs could reduce brain ischemia-reperfusion injury. In conclusion, this study demonstrates the potential mechanisms of the total flavonoids of EULs in treating ischemic stroke and their potential therapeutic effects in reducing ischemic injury, which provides useful information for ischemic stroke drug discovery.

Robustness of the synergistic partial-denitrification, anammox, and fermentation process for treating domestic and nitrate wastewaters under fluctuating C/N ratios.

The synergistic partial-denitrification, anammox, and fermentation (SPDAF) process presents a promising solution to treat domestic and nitrate wastewaters. However, its capability to handle fluctuating C/N ratios (the ratios of COD to total inorganic nitrogen) in practical applications remains uncertain. In this study, the SPDAF process was operated for 236 days with C/N ratios of 0.7-3.5, and a high and stable efficiency of nitrogen removal (84.9 ± 7.8%) was achieved. The denitrification and anammox contributions were 6.1 ± 7.1% and 93.9 ± 7.1%, respectively. Batch tests highlighted the pivotal role of in situ fermentation at low biodegradable chemical oxygen demand (BCOD)/NO3- ratios. As the BCOD/NO3- ratios increased from 0 to 6, the NH4+ and NO3- removal rates increased, while the anammox contribution decreased from 100% to 80.1% but remained the primary pathway of nitrogen removal. The cooperation and balanced growth of denitrifying bacteria, anammox bacteria, and fermentation bacteria contributed to the system's robustness under fluctuating C/N ratios.