A novel framework for uncovering the coordinative spectrum-effect correlation of the effective components of Yangyin Tongnao Granules on cerebral ischemia-reperfusion injury in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Ischemic stroke is currently a major public health hazard.Yangyin Tongnao Granules (YYTN), a traditional Chinese medicinal prescription, exerts potential therapeutic effects on subsequent cerebral ischemia-reperfusion injury (CIRI) after ischemic stroke. However, further studies are required to comprehend the underlying mechanism of YYTN for treating CIRI and the associated spectrum-effect mechanisms. AIM OF THE STUDY: To investigate the coordinated correlation between the fingerprint and the pharmacodynamic indexes of the effective components (total flavonoids, total saponins, total alkaloids, and total phenolic acids) in YYTN for treating CIRI in rats. METHODS: The fingerprints of five specific components (ligustrazine, puerarin, ferulic acid, calycosin, and formononetin) of YYTN in rats with middle cerebral artery occlusion (MCAO) were established using high-performance liquid chromatography (HPLC), and their peak areas were quantified in plasma samples. The pharmacodynamic indexes of tumor necrosis factor-alpha (TNF-α), cytochrome c (Cyt-C), and total superoxide dismutase (T-SOD) were integrated using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to create a comprehensive evaluation index. Spectrum-effect correlation was analyzed by performing gray relation analysis (GRA), correlation analysis (CA), and partial least squares regression (PLSR). The Borda method was then applied to integrate the obtained results. RESULTS: In MCAO rats, the effective components of YYTN reduced TNF-α and Cyt-C and increased T-SOD, which indicates their anti-inflammatory, antiapoptotic, and antioxidant effects. Spectrum-effect CA revealed certain associations between the chromatographic peaks of the five main components and the comprehensive pharmacodynamic evaluation index. Of these components, formononetin displayed the highest correlation, whereas ferulic acid exhibited the lowest correlation. All components showed a positive correlation. Using the Borda method, the components were ranked as follows based on correlation: formononetin > calycosin > ligustrazine > puerarin > ferulic acid. CONCLUSIONS: The effective components of YYTN exhibited synergistic effects in the treatment of MCAO rats, which could potentially be attributed to their multitarget and multipathway mechanisms. The Borda method-based spectrum-effect correlation analysis provides a coordinated approach to investigate the relationship between fingerprint and pharmacodynamics of traditional Chinese medicine (TCM).

Using a genetic backpropagation neural network model for credit risk assessment in the micro, small and medium-sized enterprises.

In China, with the "Double Carbon" goal within reach, Micro, Small and Medium-sized Enterprises (MSMEs) emerge as pivotal contributors to economic advancement. However, they are now confronted with the imperative of transitioning towards green and low-carbon practices. To facilitate the attainment of peak carbon dioxide emissions and carbon neutrality, a refined approach is imperative. This entails precise capital allocation, enhanced financial services, streamlined management, and robust risk mitigation strategies. Consequently, conducting thorough credit risk assessments for MSMEs becomes a crucial endeavor. However, obtaining substantial loans for them proves challenging due to their elusive credit ratings and potential defaults. To address this issue, this study leverages machine learning and intelligent optimization algorithms to construct a classification model for default and credit ratings of MSMEs, utilizing their daily invoice data. Specifically, twelve indicators pertaining to default and credit ratings are extracted. Subsequently, Principal Component Analysis is employed to reduce dimensionality and synthesize all pertinent information. Following this, the Genetic Algorithm-based Back Propagation Neural Network (GA-BPNN) is utilized to delineate the relationship between indicators and default, as well as credit rating, respectively. The results indicate a prediction accuracy of 0.92 for default risk and 0.86 for credit rating. This underscores the efficacy of GA-BPNN in effectively classifying the underlying default risk and credit ratings of MSMEs, offering a promising approach for decision-making.

UPLC-MS/MS determination of 71 neuropsychotropic drugs in human serum.

In this study, a UPLC-MS/MS method was developed for the rapid detection of 71 neuropsychotropic drugs in human serum for drug concentration monitoring and toxicity screening. The analytes were separated from the biological matrix by protein precipitation using a methanol-acetonitrile solvent mixture. The chromatographic separation was performed on a Kromasil ClassicShell C18 column (2.1*50 mm, 2.5 µ m) with gradient elution using acetonitrile-0.2 % acetic acid and 10 mM ammonium acetate as the mobile phases (flow rate 0.4 mL/min, column temperature 40 °C, injection volume 5 µL). An electrospray ion source in both positive and negative ion modes with multiple ion monitoring was used. The total run time was 6 min. All compounds were quantified using the isotope internal standard method. Totally, 71 drugs were detected within their linear ranges with correlation coefficients greater than 0.990. The intra- and inter-batch precision relative standard deviations (RSDs) for the low, medium, and high concentration points were less than 15 %, with an accuracy of 90%-110 %. All compounds except Moclobemide N-oxindole are stabilised within 7 days. The relative matrix effect results for each analyte were within ±20 % of the requirements. The method is validated according to Clinical and Laboratory Standards Institute guidelines, easy to use, and has a low cost.

Efficacy of Astragalus membranaceus-Carthamus tinctorius in cerebral ischemia/reperfusion injury: Insights from metabolomics and mass spectrometry imaging.

BACKGROUND: The combination of Astragalus membranaceus and Carthamus tinctorius (AC) exhibits significant therapeutic effects in cerebral ischemia/reperfusion injury (CIRI). Understanding the metabolic characteristics of brain microregions and disturbances in tissues and systemic circulation is crucial for elucidating the mechanisms of CIRI and the therapeutic benefits of AC. However, in situ metabolic regulation of the complex brain structure has not been adequately studied, and the therapeutic mechanism of AC requires immediate clarification. PURPOSE: The present study aimed to unveil the specific metabolic reprogramming of CIRI at systemic and microregional levels, identify key metabolic pathways and metabolites, and elucidate the therapeutic mechanisms of AC. METHODS: Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI), a newly developed technique, was used to investigate metabolites in brain microregions. Hematoxylin-eosin, Nissl, and immunofluorescence staining were performed to visualize the microscopic changes associated with spatial metabolism. A comprehensive metabolomics study was conducted on serum, brain tissue, and microregions, along with neurological assessments, cerebral infarction measurements, and Evans blue experiments, to assess the systemic and local metabolic effects of AC treatment for CIRI. RESULTS: AC significantly reduced neurological damage, minimized infarct size, and repaired blood-brain barrier damage in CIRI rats. AFADESI-MSI demonstrated that the metabolic imbalance caused by CIRI primarily occurs in the cerebral cortex, hippocampus, caudate putamen, thalamus, cerebellar cortex, and fiber tract regions. Significant changes in 16 metabolites were observed in these regions, corresponding to neuron damage, glial cell activation, and neural repair. 20 metabolites from serum and 4 from brain tissue varied significantly with the sham group. Comprehensive metabolomics analysis indicated a close relationship among serum, tissue, and microregional metabolism. CIRI-induced systemic and localized metabolic disorders involve 14 metabolic pathways. AC conferred therapeutic benefits in CIRI by reversing various metabolic imbalances. CONCLUSION: AFADESI-MSI efficiently visualized brain microregion metabolism. Comprehensive metabolomics analysis revealed detailed insights into the specific metabolic reprogramming in CIRI and the therapeutic impacts of AC. AC demonstrated significant clinical potential as an adjunct therapy to existing CIRI treatments.

Research progress on immune-related therapeutic targets of brain injury caused by cerebral ischemia.

Stroke is the second leading cause of death worldwide and a leading cause of disability. The innate immune response occurs immediately after cerebral ischemia, resulting in adaptive immunity. More and more experimental evidence has proved that the immune response caused by cerebral ischemia plays an important role in early brain injury and later the recovery of brain injury. Innate immune cells and adaptive cells promote the occurrence of cerebral ischemic injury but also protect brain cells. A large number of studies have shown that cytokines and immune-related substances also have dual functions of promoting injury, reducing injury, or promoting injury recovery in the later stage of cerebral ischemia. They can be an important target for treating cerebral ischemic recovery. Therefore, this study discussed the immune cells, cytokines, and immune-related substances with dual roles in cerebral ischemia and summarized the therapeutic targets of cerebral ischemia. To explore more effective methods to treat cerebral ischemia, promote the recovery of brain function, and improve the prognosis of patients.

High-performance prediction of epilepsy surgical outcomes based on the genetic neural networks and hybrid iEEG marker.

Accurately identification of the seizure onset zone (SOZ) is pivotal for successful surgery in patients with medically refractory epilepsy. The purpose of this study is to improve the performance of model predicting the epilepsy surgery outcomes using genetic neural network (GNN) model based on a hybrid intracranial electroencephalography (iEEG) marker. We extracted 21 SOZ related markers based on iEEG data from 79 epilepsy patients. The least absolute shrinkage and selection operator (LASSO) regression was employed to integrated seven markers, selected after testing in pairs with all 21 biomarkers and 7 machine learning models, into a hybrid marker. Based on the hybrid marker, we devised a GNN model and compared its predictive performance for surgical outcomes with six other mainstream machine-learning models. Compared to the mainstream models, underpinning the GNN with the hybrid iEEG marker resulted in a better prediction of surgical outcomes, showing a significant increase of the prediction accuracy from approximately 87% to 94.3% (P = 0.0412). This study suggests that the hybrid iEEG marker can improve the performance of model predicting the epilepsy surgical outcomes, and validates the effectiveness of the GNN in characterizing and analyzing complex relationships between clinical data variables.

Uncovering Mechanism and Efficacy of Salvia Miltiorrhiza-Safflower in Cerebral Ischemia-Reperfusion Injury.

Cerebral ischemia (CI) is the main cause of stroke morbidity and disability. This study aims to identify the early molecular regulation responsible for the therapeutic effectiveness of the Herb pair Danshen-Honghua (DH) for CI. The major targets of DH were identified by searching the public database of traditional Chinese medicine (TCM). In addition, GeneCards, Disgenet, and GeneMap databases in OMIM were used to determine the disease targets of CI. A total of 88 common targets of DH and CI were selected, a protein-protein interaction (PPI) network was established by Cytoscape, and 19 core targets were screened. These genes were primarily enriched in biological processes including wound healing, reaction to oxidative stress, and response to peptides, lipid and atherosclerosis, Age-rage signaling pathway, and TNF signaling pathway by KEGG and GO enrichments. The effective components of DH had stable binding to these key targets by molecular docking. Finally, it was verified that the mechanism of DH on CI treatment may be related to the activation of the TNF-α/JNK signaling pathway by establishing the middle cerebral artery occlusion (MCAO) rat model.

Drift velocity saturation in field-effect transistors based on single CdSe nanowires.

Field-effect transistors (FETs) based on semiconductor nanowires (NWs) have been extensively investigated and used for constructing novel nanoelectronic and optoelectronic devices in the past two decades. High electric field transport characteristics in FETs are of significance in both physics and applications. However, some specific physics phenomena at high electric field, such as drift velocity saturation, have rarely been reported in semiconductor NW FETs. In this work, the high electric field transport characteristics in FETs based on CdSe NWs were investigated. In the output characteristic curves, the current saturation phenomenon at high electric field caused by drift velocity saturation was observed. Typical values of saturation drift velocity and low electric field mobility in CdSe NW FETs were obtained. The low electric field mobility is in the range of 265.2 to 388.0 cm2 V-1 s-1. The saturation drift velocity is in the range of 5.1 × 105 to 7.0 × 105 cm s-1 and decreases monotonically with the increase of charge density, indicating that the electron-phonon scattering mechanism dominates at high electric field. Saturation drift velocity is an important figure-of-merit which characterizes the high electric field transport performance in FETs. As far as we know, this is the first experimental report on saturation drift velocity in CdSe NW FETs, which may provide valuable guidance for the design of nanoelectronic and optoelectronic devices based on CdSe NWs in the future.

A comparative study of the protective effects of Guhong injection and its component on cerebral ischemia-reperfusion injury based on the oxidation index.

Guhong injection (GHI), a compound preparation of Chinese and Western medicine, is composed of safflower water extract and aceglutamide, and has a certain therapeutic effect on cerebral ischemia diseases. In this study, we investigated and compared the protective effects of GHI, Honghua injection (HHI), and aceglutamide (ACG) on cerebral ischemia-reperfusion injury in Sprague-Dawley (SD) rats randomly assigned to the following 5 groups: Sham, MCAO, MCAO + GHI, MCAO + HHI, and MCAO + ACG. The results revealed that GHI, HHI, and ACG improved neurological functions and reduced the infarct volume, the contents of HIF-1α, PKC, and EPO, and the expression of NOX-4 and HIF-1α mRNA. The protein expression of HIF-1α and iNOS treated with GHI, HHI, and ACG was decreased, while that of PHD2 was increased. Meanwhile, the BrdU+/NeuN+ cell counts of SGZ and SVZ areas in the brain tissues of the GHI, HHI, and ACG groups were greater than those of the MCAO rats. Thus, GHI, HHI, and ACG can confer protection against cerebral ischemia-reperfusion injury, possibly through antioxidation. Our research findings may provide evidence for the effectiveness of the combination of traditional Chinese and Western medicine.

Prioritizing non-communicable diseases in the post-pandemic era based on a comprehensive analysis of the GBD 2019 from 1990 to 2019.

This study aimed to assess the burden of communicable diseases (CDs) and non-communicable diseases (NCDs) globally, regionally, and nationally from 1990 to 2019, and propose global strategies to transform the public health policy. Using data from the Global Burden of Disease Study (GBD) 2019, we analyzed CDs and NCDs across various factors such as sex, age, year, and location, and evaluate the temporal trends of these diseases with joinpoint analysis. We also examined the differences between regions based on their socio-demographic index (SDI). In 2019, there were 7,862,907 (95% uncertainty interval [UI], 7,183,475 to 8,654,104) deaths from CDs and 42,034,124 (40,081,323 to 43,942,475) deaths from NCDs recorded worldwide. The low SDI region had markedly high age-standardized death and DALY rates of CDs. Although the age-standardized incidence rate of CDs has decreased in about half of the regions since 1990, NCDs have been on the rise in most regions. Over the past 30 years, the global burden of CDs has decreased significantly, while the burden of NCDs has aggrandized to an extent. In the post-pandemic era, effective interventions and cooperation among countries should be promoted to allocate medical resources more reasonably and improve healthcare for NCD patients.

A comprehensive review of stroke-related signaling pathways and treatment in western medicine and traditional Chinese medicine.

This review provides insight into the complex network of signaling pathways and mechanisms involved in stroke pathophysiology. It summarizes the historical progress of stroke-related signaling pathways, identifying potential interactions between them and emphasizing that stroke is a complex network disease. Of particular interest are the Hippo signaling pathway and ferroptosis signaling pathway, which remain understudied areas of research, and are therefore a focus of the review. The involvement of multiple signaling pathways, including Sonic Hedgehog (SHH), nuclear factor erythroid 2-related factor 2 (Nrf2)/antioxidant response element (ARE), hypoxia-inducible factor-1α (HIF-1α), PI3K/AKT, JAK/STAT, and AMPK in pathophysiological mechanisms such as oxidative stress and apoptosis, highlights the complexity of stroke. The review also delves into the details of traditional Chinese medicine (TCM) therapies such as Rehmanniae and Astragalus, providing an analysis of the recent status of western medicine in the treatment of stroke and the advantages and disadvantages of TCM and western medicine in stroke treatment. The review proposes that since stroke is a network disease, TCM has the potential and advantages of a multi-target and multi-pathway mechanism of action in the treatment of stroke. Therefore, it is suggested that future research should explore more treasures of TCM and develop new therapies from the perspective of stroke as a network disease.

Optimization of green extraction process with natural deep eutectic solvent and comparative in vivo pharmacokinetics of bioactive compounds from Astragalus-Safflower pair.

INTRODUCTION: Natural deep eutectic solvents (NaDESs) are promising not only in componential extraction, but also in drug delivery system due to their green and safe features. In this work, NaDESs were applied to extract bioactive components from Astragalus-Safflower pair, a classic traditional Chinese medicine combination. Furthermore, ready-to-use crude extracts were administrated to SD rats. METHODS: Total 9 NaDESs composed of food grade ingredients were screened for the extraction of representative 9 components (hydroxysafflor yellow A, anhydrosafflor yellow B, eleutheroside B, calycosin-7-O-glucoside, kaempferol-3-O-rutinoside, ononin, calycosin, astraganoside, and carthamin) from Astragalus-Safflower pair. Afterwards, genetic artificial neural network (GNN) was adopted for optimizing the ultrasound-assisted extraction process. After SD rats were orally administrated with the ready-to-use crude extracts extracted under the optimized conditions, the in vivo pharmacokinetic characteristics of 5 components were evaluated comprehensively from weight, gender, solvent and modeling surgery, under a well-established UPLC-MS/MS method. RESULTS: Betaine-Lactic acid (Bet-Lac) was eventually determined as the optimal extraction solvent for subsequent experiments. The optimal ultrasound assisted extraction process was as follows: 90 min of extraction time, 65 °C of temperature, 80% of Bet-Lac content and 50 mg/ml of solid-liquid ratio. Bet-Lac enhanced to varying degrees the bioavailability of analytes in normal and cerebral ischemia/reperfusion injured (CI/RI) rats in contrast with corresponding rats administrated with water extract groups (p < 0.05). Besides, the bioavailability of active components in CI/RI rat plasma was significantly lower than that in normal rats (p < 0.05), indicating pathological damage of CI/R had a significant impact on pharmacokinetic profile of compounds in rats. However, gender and body weight had no significant effects on the pharmacokinetic profile of bioactive components. CONCLUSIONS: NaDESs exhibited higher extraction efficiency than conventional solvents. And GNN is reliable to optimize the ultrasound assisted extraction process. This study supported the potential of non-toxic NaDESs as solvents for extraction process and drug delivery systems at the same time.

An integrated strategy of spectrum-effect relationship and near-infrared spectroscopy rapid evaluation based on back propagation neural network for quality control of Paeoniae Radix Alba.

The quantitative analysis of near-infrared spectroscopy in traditional Chinese medicine has still deficiencies in the selection of the measured indexes. Then Paeoniae Radix Alba is one of the famous "Eight Flavors of Zhejiang" herbs, however, it lacks the pharmacodynamic support, and cannot reflect the quality of Paeoniae Radix Alba accurately and reasonably. In this study, the spectrum-effect relationship of the anti-inflammatory activity of Paeoniae Radix Alba was established. Then based on the obtained bioactive component groups, the genetic algorithm, back propagation neural network, was combined with near-infrared spectroscopy to establish calibration models for the content of the bioactive components of Paeoniae Radix Alba. Finally, three bioactive components, paeoniflorin, 1,2,3,4,6-O-pentagalloylglucose, and benzoyl paeoniflorin, were successfully obtained. Their near-infrared spectroscopy content models were also established separately, and the validation sets results showed the coefficient of determination (R2 > 0.85), indicating that good calibration statistics were obtained for the prediction of key pharmacodynamic components. As a result, an integrated analytical method of spectrum-effect relationship combined with near-infrared spectroscopy and deep learning algorithm was first proposed to assess and control the quality of traditional Chinese medicine, which is the future development trend for the rapid inspection of traditional Chinese medicine.

Dysbiosis of the Gut Microbiota and Kynurenine (Kyn) Pathway Activity as Potential Biomarkers in Patients with Major Depressive Disorder.

With increasing attention paid to the concept of the microbiota-gut-brain axis, mounting evidence reveals that the gut microbiota is involved in a variety of neurological and psychiatric diseases. However, gut microbiota changes in major depressive disorder (MDD) patients and their association with disease mechanisms remain undefined. Fifty MDD patients and sixty healthy controls were recruited from the Shanghai Healthy Mental Center, China. Fecal samples were collected, and the compositional characteristics of the intestinal flora were determined in MDD patients by MiSeq sequencing. Venous blood was collected for the detection of plasma indoleamine-2,3-dioxygenase (Ido), kynurenine (Kyn) and tryptophan (Trp) levels. Stool samples of bacterial 16S sequencing was carried out. A total of 2,705,809 optimized sequences were obtained, with an average of 54,116 per sample. More unique OTUs were observed at the family, genus and species levels in the control group compared with the MDD cases. Further analysis showed significant changes in the α- and ß-diversities and relative abundance levels of gut microbial entities in MDD patients, as well as elevated amounts of Ido and Kyn indicating Kyn pathway activation, KEGG bacterial 16S function prediction analysis shows a variety of amino acids and metabolic (including Ido, Trp and Kyn) changes in the body of patients with MDD. These may result in increased neurotoxic metabolites and reduced generation of serotonin in the disease process. These changed factors may potentially be utilized as biomarkers for MDD in the future, playing more important roles in the disease course.

An efficient five-lncRNA signature for lung adenocarcinoma prognosis, with AL606489.1 showing sexual dimorphism.

Background: Lung adenocarcinoma (LUAD) is a sex-biased and easily metastatic malignant disease. A signature based on 5 long non-coding RNAs (lncRNAs) has been established to promote the overall survival (OS) prediction effect on LUAD. Methods: The RNA expression profiles of LUAD patients were obtained from The Cancer Genome Atlas. OS-associated lncRNAs were identified based on the differential expression analysis between LUAD and normal samples followed by survival analysis, univariate and multivariate Cox proportional hazards regression analyses. OS-associated lncRNA with sex dimorphism was determined based on the analysis of expression between males and females. Functional enrichment analysis of the Gene Ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was performed to explore the possible mechanisms of 5-lncRNA signatures. Results: A 5-lncRNA signature (composed of AC068228.1, SATB2-AS1, LINC01843, AC026355.1, and AL606489.1) was found to be effective in predicting high-risk LUAD patients as well as applicable to female and male subgroups and <65-year and ≥65-year age subgroups. The forecasted effect of the 5-lncRNA signature was more efficient and stable than the TNM stage and other clinical risk factors (such as sex and age). Functional enrichment analysis revealed that the mRNA co-expressed with these five OS-related lncRNAs was associated with RNA regulation within the nucleus. AL606489.1 demonstrated a sexual dimorphism that may be associated with microtubule activity. Conclusion: Our 5-lncRNA signature could efficaciously predict the OS of LUAD patients. AL606489.1 demonstrated gender dimorphism, which provides a new direction for mechanistic studies on sexual dimorphism.

Optimization of smashing tissue and ultrasonic extraction of tanshinones and their neuroprotective effect on cerebral ischemia/reperfusion injury by inhibiting parthanatos.

A green smashing tissue and ultrasonic (STU) extraction method, which combines smashing tissue and ultrasonic-assisted extraction, was developed for the first time. The extraction of tanshinones from Salvia miltiorrhiza Bunge (SM) was taken as an example to discuss the practicability of this method. Taking the total yield of eight tanshinones as an evaluation index, response surface methodology (RSM) and artificial neural network (ANN) models were used to optimize the extraction parameters, and these two models were also compared by investigating the extract yield of tanshinones and the antioxidant activity of the obtained SM extract. The optimal STU conditions by ANN were as follows: an ethanol concentration of 73%, a liquid/solid ratio of 30 mL g-1, a smashing tissue time of 97 s and an ultrasonic time of 40 min. Under these optimal conditions, the yield of the eight components was 0.30% ± 0.12, which was greater than 0.28% ± 0.03 optimized by RSM. The IC50 values of 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,2'-azinobis-(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) of the obtained extract were 55.25 ± 3.72 µg mL-1 and 67.33 ± 2.62 µg mL-1, respectively, which were better than those of 75.49 ± 4.33 µg mL-1 and 112.10 ± 5.98 µg mL-1, respectively, optimized by RSM. Furthermore, the SM extract was found to exert neuroprotective effects by inhibiting parthanatos in middle cerebral artery occlusion/reperfusion (MCAO/R)-induced rats. The results supported the use of the SM extract, which was obtained by STU, as a potential product in the cosmetics, medicine, and food industries.

Molecular Mechanisms of Parthanatos and Its Role in Diverse Diseases.

Differential evolution of apoptosis, programmed necrosis, and autophagy, parthanatos is a form of cell death mediated by poly(ADP-ribose) polymerase 1 (PARP1), which is caused by DNA damage. PARP1 hyper-activation stimulates apoptosis-inducing factor (AIF) nucleus translocation, and accelerates nicotinamide adenine dinucleotide (NAD+) and adenosine triphosphate (ATP) depletion, leading to DNA fragmentation. The mechanisms of parthanatos mainly include DNA damage, PARP1 hyper-activation, PAR accumulation, NAD+ and ATP depletion, and AIF nucleus translocation. Now, it is reported that parthanatos widely exists in different diseases (tumors, retinal diseases, neurological diseases, diabetes, renal diseases, cardiovascular diseases, ischemia-reperfusion injury...). Excessive or defective parthanatos contributes to pathological cell damage; therefore, parthanatos is critical in the therapy and prevention of many diseases. In this work, the hallmarks and molecular mechanisms of parthanatos and its related disorders are summarized. The questions raised by the recent findings are also presented. Further understanding of parthanatos will provide a new treatment option for associated conditions.

Simultaneous optimization of the extraction process of Yangyin Yiqi Huoxue prescription with natural deep eutectic solvents for optimal extraction yield and antioxidant activity: A comparative study of two models.

INTRODUCTION: Natural deep eutectic solvents (NaDESs) are green and effective solvents that are used to extract 3 flavonoids from Yangyin Yiqi Huoxue prescription, a traditional Chinese prescription. METHODS: A total of 6 types of NaDESs were systematically screened and evaluated for the total extraction yield of puerarin, calycosin, and formononetin by high-performance liquid chromatography. Then, a 4-factor-three-level experimental scheme designed by the Box-Benhnken Design was applied on the basis of a single experiment to determine the extraction yield and the antioxidant property. Finally, the extraction process was optimized through response surface methodology (RSM) and the genetic neural network (GNN), respectively. RESULTS: The use of betaine-lactic acid as an extractant displayed significant advantages in the screening process. The optimum extraction parameters provided by GNN were as follows: water content 25% (v/v), liquid to material ratio 190 mg/ml, extraction time 37 min, and extraction temperature 63 °C. Under this condition, the average experimental comprehensive evaluation values of the extraction yield and antioxidant properties were 3.12 mg/g and 86.27%, and the relative deviations to the predicted values were 0.30% and 1.44%, respectively. In addition, the experimental results of GNN were better than those of RSM (p < 0.01). CONCLUSIONS: We found the application of GNN to be effective and credible for bi-objective optimization of extraction yields and antioxidant activity in this study. Moreover, our results provide a reference and a theoretical basis for experimental and future industrial extraction for multi-objective situations.

Construction and Validation of an Immune-Related Risk Score Model for Survival Prediction in Glioblastoma.

Background: As one of the most important brain tumors, glioblastoma (GBM) has a poor prognosis, especially in adults. Immune-related genes (IRGs) and immune cell infiltration are responsible for the pathogenesis of GBM. This study aimed to identify new tumor markers to predict the prognosis of patients with GBM. Methods: The Cancer Genome Atlas (TCGA) database and ImmPort database were used for model construction. The Wilcoxon rank-sum test was applied to identify the differentially expressed IRGs (DEIRGs) between the GBM and normal samples. Univariate Cox regression analysis and Kaplan-Meier analysis was performed to investigate the relationship between each DEIRG and overall survival. Next, multivariate Cox regression analysis was exploited to further explore the prognostic potential of DEIRGs. A risk-score model was constructed based on the above results. The area under the curve (AUC) values were calculated to assess the effect of the model prediction. Furthermore, the Chinese Glioma Genome Atlas (CGGA) dataset was used for model validation. STRING database and functional enrichment analysis were used for exploring the gene interactions and the underlying functions and pathways. The CIBERSORT algorithm was used for correlation analysis of the marker genes and the tumor-infiltrating immune cells. Results: There were 198 DEIRGs in GBM, including 153 upregulated genes and 45 downregulated genes. Seven marker genes (LYNX1, PRELID1P4, MMP9, TCF12, RGS14, RUNX1, and CCR2) were filtered out by sequential screening for DEIRGs. The regression coefficients (0.0410, 1.335, 0.005, -0.021, 0.123, 0.142, and -0.329) and expression data of the marker genes were used to construct the model. The AUC values for 1, 2, and 3 years were 0.744, 0.737, and 0.749 in the TCGA-GBM cohort and 0.612, 0.602, and 0.594 in the CGGA-GBM cohort, respectively, which indicated a high predictive power. The results of enrichment analysis revealed that these genes were enriched in the activation of T cell and cytokine receptor interaction pathways. The interaction network map demonstrated a close relationship between the marker genes MMP9 and CCR2. Infiltration analysis of the immune cells showed that dendritic cells (DCs) could identify GBM, while LYNX1, RUNX1, and CCR2 were significantly positively correlated with DCs expression. Conclusion: This study analyzed the expression of IRGs in GBM and identified seven marker genes for the construction of an immune-related risk score model. These marker genes were found to be associated with DCs and were enriched in similar immune response pathways. These findings are likely to provide new insights for the immunotherapy of patients with GBM.

Consensus on potential biomarkers developed for use in clinical tests for schizophrenia.

Background: Schizophrenia is a serious mental illness affecting approximately 20 million individuals globally. Both genetic and environmental factors contribute to the illness. If left undiagnosed and untreated, schizophrenia results in impaired social function, repeated hospital admissions, reduced quality of life and decreased life expectancy. Clinical diagnosis largely relies on subjective evidence, including self-reported experiences, and reported behavioural abnormalities followed by psychiatric evaluation. In addition, psychoses may occur along with other conditions, and the symptoms are often episodic and transient, posing a significant challenge to the precision of diagnosis. Therefore, objective, specific tests using biomarkers are urgently needed for differential diagnosis of schizophrenia in clinical practice. Aims: We aimed to provide evidence-based and consensus-based recommendations, with a summary of laboratory measurements that could potentially be used as biomarkers for schizophrenia, and to discuss directions for future research. Methods: We searched publications within the last 10 years with the following keywords: 'schizophrenia', 'gene', 'inflammation', 'neurotransmitter', 'protein marker', 'gut microbiota', 'pharmacogenomics' and 'biomarker'. A draft of the consensus was discussed and agreed on by all authors at a round table session. Results: We summarised the characteristics of candidate diagnostic markers for schizophrenia, including genetic, inflammatory, neurotransmitter, peripheral protein, pharmacogenomic and gut microbiota markers. We also proposed a novel laboratory process for diagnosing schizophrenia in clinical practice based on the evidence summarised in this paper. Conclusions: Further efforts are needed to identify schizophrenia-specific genetic and epigenetic markers for precise diagnosis, differential diagnosis and ethnicity-specific markers for the Chinese population. The development of novel laboratory techniques is making it possible to use these biomarkers clinically to diagnose disease.