ß-Hydroxybutyrate suppresses colorectal cancer.

Colorectal cancer (CRC) is among the most frequent forms of cancer, and new strategies for its prevention and therapy are urgently needed1. Here we identify a metabolite signalling pathway that provides actionable insights towards this goal. We perform a dietary screen in autochthonous animal models of CRC and find that ketogenic diets exhibit a strong tumour-inhibitory effect. These properties of ketogenic diets are recapitulated by the ketone body ß-hydroxybutyrate (BHB), which reduces the proliferation of colonic crypt cells and potently suppresses intestinal tumour growth. We find that BHB acts through the surface receptor Hcar2 and induces the transcriptional regulator Hopx, thereby altering gene expression and inhibiting cell proliferation. Cancer organoid assays and single-cell RNA sequencing of biopsies from patients with CRC provide evidence that elevated BHB levels and active HOPX are associated with reduced intestinal epithelial proliferation in humans. This study thus identifies a BHB-triggered pathway regulating intestinal tumorigenesis and indicates that oral or systemic interventions with a single metabolite may complement current prevention and treatment strategies for CRC.

MuSiC2: cell-type deconvolution for multi-condition bulk RNA-seq data.

Cell-type composition of intact bulk tissues can vary across samples. Deciphering cell-type composition and its changes during disease progression is an important step toward understanding disease pathogenesis. To infer cell-type composition, existing cell-type deconvolution methods for bulk RNA sequencing (RNA-seq) data often require matched single-cell RNA-seq (scRNA-seq) data, generated from samples with similar clinical conditions, as reference. However, due to the difficulty of obtaining scRNA-seq data in diseased samples, only limited scRNA-seq data in matched disease conditions are available. Using scRNA-seq reference to deconvolve bulk RNA-seq data from samples with different disease conditions may lead to a biased estimation of cell-type proportions. To overcome this limitation, we propose an iterative estimation procedure, MuSiC2, which is an extension of MuSiC, to perform deconvolution analysis of bulk RNA-seq data generated from samples with multiple clinical conditions where at least one condition is different from that of the scRNA-seq reference. Extensive benchmark evaluations indicated that MuSiC2 improved the accuracy of cell-type proportion estimates of bulk RNA-seq samples under different conditions as compared with the traditional MuSiC deconvolution. MuSiC2 was applied to two bulk RNA-seq datasets for deconvolution analysis, including one from human pancreatic islets and the other from human retina. We show that MuSiC2 improves current deconvolution methods and provides more accurate cell-type proportion estimates when the bulk and single-cell reference differ in clinical conditions. We believe the condition-specific cell-type composition estimates from MuSiC2 will facilitate the downstream analysis and help identify cellular targets of human diseases.

Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing data.

Allelic expression imbalance (AEI), quantified by the relative expression of two alleles of a gene in a diploid organism, can help explain phenotypic variations among individuals. Traditional methods detect AEI using bulk RNA sequencing (RNA-seq) data, a data type that averages out cell-to-cell heterogeneity in gene expression across cell types. Since the patterns of AEI may vary across different cell types, it is desirable to study AEI in a cell-type-specific manner. Although this can be achieved by single-cell RNA sequencing (scRNA-seq), it requires full-length transcript to be sequenced in single cells of a large number of individuals, which are still cost prohibitive to generate. To overcome this limitation and utilize the vast amount of existing disease relevant bulk tissue RNA-seq data, we developed BSCET, which enables the characterization of cell-type-specific AEI in bulk RNA-seq data by integrating cell type composition information inferred from a small set of scRNA-seq samples, possibly obtained from an external dataset. By modeling covariate effect, BSCET can also detect genes whose cell-type-specific AEI are associated with clinical factors. Through extensive benchmark evaluations, we show that BSCET correctly detected genes with cell-type-specific AEI and differential AEI between healthy and diseased samples using bulk RNA-seq data. BSCET also uncovered cell-type-specific AEIs that were missed in bulk data analysis when the directions of AEI are opposite in different cell types. We further applied BSCET to two pancreatic islet bulk RNA-seq datasets, and detected genes showing cell-type-specific AEI that are related to the progression of type 2 diabetes. Since bulk RNA-seq data are easily accessible, BSCET provides a convenient tool to integrate information from scRNA-seq data to gain insight on AEI with cell type resolution. Results from such analysis will advance our understanding of cell type contributions in human diseases.

Correlation between lipoprotein(a) and recurrent ischemic events post-cerebral vascular stent implantation.

BACKGROUND AND AIM: The association of Lipoprotein(a) (Lp[a]) with recurrent ischemic events in stented patients remains uncertain. So, this research aimed to investigate the impact of elevated Lp(a) levels on the occurrence of ischemic events in this specific patient population. METHODS: Totally 553 patients who underwent intracranial or extracranial artery stent implantation were included. Baseline data were collected and postoperative ischemic outcomes were followed up. Cox regression analysis was used to investigate the association between Lp(a) and outcomes, while accounting for confounding factors. Finally, we established prediction models based on nomogram. RESULTS: Of total 553 patients, a number of 107 (19.3%) experienced outcomes. These included 46 cases (34.7%) in group with elevated Lp(a) levels (>30 mg/dL) and 61 cases (18.4%) in non-elevated group (χ2=6.343, p=0.012). The group with elevated Lp(a) was 1.811 times more likely to experience ischemic events than the non-elevated group, each 1 mg/dL increase in Lp(a) resulted in a 1.008-fold increase in the recurrence rate of ischemic events. In addition, sex (male), previous history of coronary heart disease, decreased albumin, elevated very low density lipoprotein cholesterol and poorly controlled risk factors (including blood pressure and blood sugar) were also associated with a high risk of recurrent ischemic events after stent implantation. CONCLUSION: Lp(a) elevation was a significant risk factor for ischemic events in symptomatic patients who underwent intracranial or extracranial artery stenting.

Effect of ionic conductivity of electrolyte on printed planar and vertical organic electrochemical transistors.

Conducting polymers with mixed electronic/ionic transport are attracting a great deal of interest for applications in organic electrochemical transistors (OECTs). Ions play a crucial role in OECT performance. The concentration and mobility of ions in the electrolyte influence the current flow in the OECT and its transconductance. This study examines the electrochemical properties and ionic conductivity of two semi-solid electrolytes, iongels, and organogels, with diverse ionic species and properties. Our results indicate that the organogels exhibited higher ionic conductivities than the iongels. Furthermore, the geometry of OECTs plays an important role in determining their transconductance. Thus, this study employs a novel approach for fabricating vertical-configuration OECTs with significantly shorter channel lengths planar devices. This is achieved through a printing method that offers advantages, such as design versatility, scalability, expedited production time, and reduced cost relative to traditional microfabrication methods. The transconductance values obtained for the vertical OECTs were significantly (approximately 50 times) higher than those of the planar devices because of their shorter channel lengths. Finally, the impact of different gating media on the performance of both planar and vertical OECTs was studied, and devices gated by organogels demonstrated improved transconductance and switching speed (almost two times higher) than those gated by iongels.

Protective effect of vitamin B6 against doxorubicin-induced cardiotoxicity by modulating NHE1 expression.

Doxorubicin (DOX) has been used to treat various types of cancer, but its application is limited due to its heart toxicity as well as other drawbacks. Chronic inhibition of Na+ /H+ exchanger (NHE1) reduces heart failure and reduces the production of reactive oxygen species (ROS); vitamin B6 (VitB6 ) has been demonstrated to have a crucial role in antioxidant mechanism. So, this study was designed to explore the effect of VitB6 supplement on the DOX-induced cardiotoxicity and to imply whether NHE1 is involved. Ultrasonic cardiogram analysis revealed that VitB6 supplement could alleviate DOX-induced cardiotoxicity; hematoxylin and eosin (HE) and Masson's staining further confirmed this effect. Furthermore, VitB6 supplement exhibited significant antioxidative stress and antiapoptosis effect, which was evidenced by decreased serum malondialdehyde (MDA) content and increased serum superoxide dismutase (SOD) content, and decreased Bcl-2-associated X protein/B-cell lymphoma-2 ratio, respectively. Collectively, VitB6 supplement may exert antioxidative and antiapoptosis effects to improve cardiac function by decreasing NHE1 expression and improve DOX-induced cardiotoxicity.

The unmet needs of patients in the early rehabilitation stage after lung cancer surgery: a qualitative study based on Maslow's hierarchy of needs theory.

PURPOSE: This study aimed to explore the unmet needs of lung cancer patients in early rehabilitation, based on Maslow's hierarchy of needs theory. METHODS: Information on the experiences of 20 patients was collected through semi-structured interviews. The interviews were conducted in the surgical nursing clinic within 1 week of discharge from hospital. The data were analysed using a combination of deductive (theory-driven) and inductive (data-driven) methods, using Maslow's Hierarchy of Needs as a framework for identifying and organising themes. RESULTS: Patients had a mean age of 50.92 years (SD 11.88); n = 11 (55%) were female. Major themes aligned with the dimensions of Maslow's hierarchy of needs model. Five major themes with 12 corresponding sub-themes emerged: (1) physiological needs, including "self-care and independence in life", "return to pre-operative status as soon as possible", "increase exercise under specialist guidance" and "reduce cough and pain and improve sleep quality"; (2) safety and security needs, such as "symptom management", "regulation of the emotions of worry and fear" and "access accurate treatment information"; (3) love and belonging needs, including "accompany family members" and "chat with friends";(4)Esteem needs: "live with dignity";(5) Self-actualization, such as "accept and submit to the reality of cancer" and "live meaningfully". CONCLUSIONS: The findings of this study indicated that there were many unmet needs for patients during the early recovery period after lung cancer surgery. An overview of the different areas of need identified in this study may guide future research and development of interventions to improve patients' quality of life during the home rehabilitation phase.

ASEP: Gene-based detection of allele-specific expression across individuals in a population by RNA sequencing.

Allele-specific expression (ASE) analysis, which quantifies the relative expression of two alleles in a diploid individual, is a powerful tool for identifying cis-regulated gene expression variations that underlie phenotypic differences among individuals. Existing methods for gene-level ASE detection analyze one individual at a time, therefore failing to account for shared information across individuals. Failure to accommodate such shared information not only reduces power, but also makes it difficult to interpret results across individuals. However, when only RNA sequencing (RNA-seq) data are available, ASE detection across individuals is challenging because the data often include individuals that are either heterozygous or homozygous for the unobserved cis-regulatory SNP, leading to sample heterogeneity as only those heterozygous individuals are informative for ASE, whereas those homozygous individuals have balanced expression. To simultaneously model multi-individual information and account for such heterogeneity, we developed ASEP, a mixture model with subject-specific random effect to account for multi-SNP correlations within the same gene. ASEP only requires RNA-seq data, and is able to detect gene-level ASE under one condition and differential ASE between two conditions (e.g., pre- versus post-treatment). Extensive simulations demonstrated the convincing performance of ASEP under a wide range of scenarios. We applied ASEP to a human kidney RNA-seq dataset, identified ASE genes and validated our results with two published eQTL studies. We further applied ASEP to a human macrophage RNA-seq dataset, identified genes showing evidence of differential ASE between M0 and M1 macrophages, and confirmed our findings by results from cardiometabolic trait-relevant genome-wide association studies. To the best of our knowledge, ASEP is the first method for gene-level ASE detection at the population level that only requires the use of RNA-seq data. With the growing adoption of RNA-seq, we believe ASEP will be well-suited for various ASE studies for human diseases.

Identification of a ferroptosis-related gene pair biomarker with immune infiltration landscapes in ischemic stroke: a bioinformatics-based comprehensive study.

BACKGROUND: Ischemic stroke (IS) is a principal contributor to long-term disability in adults. A new cell death mediated by iron is ferroptosis, characterized by lethal aggregation of lipid peroxidation. However, a paucity of ferroptosis-related biomarkers early identify IS until now. This study investigated potential ferroptosis-related gene pair biomarkers in IS and explored their roles in immune infiltration. RESULTS: In total, we identified 6 differentially expressed ferroptosis-related genes (DEFRGs) in the metadata cohort. Of these genes, 4 DEFRGs were incorporated into the competitive endogenous RNA (ceRNA) network, including 78 lncRNA-miRNA and 16 miRNA-mRNA interactions. Based on relative expression values of DEFRGs, we constructed gene pairs. An integrated scheme consisting of machine learning algorithms, ceRNA network, and gene pair was proposed to screen the key DEFRG biomarkers. The receiver operating characteristic (ROC) curve witnessed that the diagnostic performance of DEFRG pair CDKN1A/JUN was superior to that of single gene. Moreover, the CIBERSORT algorithm exhibited immune infiltration landscapes: plasma cells, resting NK cells, and resting mast cells infiltrated less in IS samples than controls. Spearman correlation analysis confirmed a significant correlation between plasma cells and CDKN1A/JUN (CDKN1A: r = - 0.503, P < 0.001, JUN: r = - 0.330, P = 0.025). CONCLUSIONS: Our findings suggested that CDKN1A/JUN could be a robust and promising gene-pair diagnostic biomarker for IS, regulating ferroptosis during IS progression via C9orf106/C9orf139-miR-22-3p-CDKN1A and GAS5-miR-139-5p/miR-429-JUN axes. Meanwhile, plasma cells might exert a vital interplay in IS immune microenvironment, providing an innovative insight for IS therapeutic target.

Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human.

BACKGROUND: Smooth muscle cells (SMCs) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration, and transdifferentiation into other cell types. Yet how SMCs contribute to the pathophysiology of atherosclerosis remains elusive. METHODS: To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and used pharmacological studies targeting SMC-derived cells both in vivo and in vitro. RESULTS: We found that SMCs transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC-derived intermediate cells, termed "SEM" cells (stem cell, endothelial cell, monocyte), were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return toward the SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition, and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome-wide association study signals for coronary artery disease in RA signaling target gene loci and correlation between coronary artery disease risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans RA, an anticancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden, and promoted fibrous cap stability. CONCLUSIONS: Integration of cell-specific fate mapping, single-cell genomics, and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.

The prediction of asymptomatic carotid atherosclerosis with electronic health records: a comparative study of six machine learning models.

BACKGROUND: Screening carotid B-mode ultrasonography is a frequently used method to detect subjects with carotid atherosclerosis (CAS). Due to the asymptomatic progression of most CAS patients, early identification is challenging for clinicians, and it may trigger ischemic stroke. Recently, machine learning has shown a strong ability to classify data and a potential for prediction in the medical field. The combined use of machine learning and the electronic health records of patients could provide clinicians with a more convenient and precise method to identify asymptomatic CAS. METHODS: Retrospective cohort study using routine clinical data of medical check-up subjects from April 19, 2010 to November 15, 2019. Six machine learning models (logistic regression [LR], random forest [RF], decision tree [DT], eXtreme Gradient Boosting [XGB], Gaussian Naïve Bayes [GNB], and K-Nearest Neighbour [KNN]) were used to predict asymptomatic CAS and compared their predictability in terms of the area under the receiver operating characteristic curve (AUCROC), accuracy (ACC), and F1 score (F1). RESULTS: Of the 18,441 subjects, 6553 were diagnosed with asymptomatic CAS. Compared to DT (AUCROC 0.628, ACC 65.4%, and F1 52.5%), the other five models improved prediction: KNN + 7.6% (0.704, 68.8%, and 50.9%, respectively), GNB + 12.5% (0.753, 67.0%, and 46.8%, respectively), XGB + 16.0% (0.788, 73.4%, and 55.7%, respectively), RF + 16.6% (0.794, 74.5%, and 56.8%, respectively) and LR + 18.1% (0.809, 74.7%, and 59.9%, respectively). The highest achieving model, LR predicted 1045/1966 cases (sensitivity 53.2%) and 3088/3566 non-cases (specificity 86.6%). A tenfold cross-validation scheme further verified the predictive ability of the LR. CONCLUSIONS: Among machine learning models, LR showed optimal performance in predicting asymptomatic CAS. Our findings set the stage for an early automatic alarming system, allowing a more precise allocation of CAS prevention measures to individuals probably to benefit most.

PLCε regulates metabolism and metastasis signaling via HIF-1α/MEK/ERK pathway in prostate cancer.

Phospholipase C-ε (PLCε) is frequently overexpressed in tumors and plays an important role in the regulation of tumorigenesis. Although great progress has been made in understanding biological roles of PLCε, the relevant molecular mechanisms underlying its pro-tumor activity remain largely unclear. Here, we demonstrated that PLCε knockdown reduced cell metastasis, glucose consumption and lactate production in a manner that depended on hypoxia inducible factor 1α (HIF-1α) expression in prostate cancer cells. Interestingly, our findings showed that the expression levels of PLCε were positively associated with those of HIF-1α in clinical prostate carcinoma samples. Knockdown of PLCε impaired HIF-1α levels and transcriptional activity by regulating the extracellular-signal-regulated kinase pathway, and blocking HIF-1α nuclear translocation. Furthermore, PLCε could interact with the von Hippel-Lindau E3 ligase complex to modulate the stability of HIF-1α. Collectively, our findings demonstrate that PLCε could be a crucial positive regulator of HIF-1α, which would promote PLCε-enhanced tumorigenesis.

Development of a model to predict electroencephalographic seizures in critically ill children.

OBJECTIVE: Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but ES identification with continuous electroencephalography (EEG) monitoring (CEEG) is resource-intense. We aimed to develop an ES prediction model that would enable clinicians to stratify patients by ES risk and optimally target limited CEEG resources. We aimed to determine whether incorporating data from a screening EEG yielded better performance characteristics than models using clinical variables alone. METHODS: We performed a prospective observational study of 719 consecutive critically ill children with acute encephalopathy undergoing CEEG in the pediatric intensive care unit of a quaternary care institution between April 2017 and February 2019. We identified clinical and EEG risk factors for ES. We evaluated model performance with area under the receiver-operating characteristic (ROC) curve (AUC), validated the optimal model with the highest AUC using a fivefold cross-validation, and calculated test characteristics emphasizing high sensitivity. We applied the optimal operating slope strategy to identify the optimal cutoff to define whether a patient should undergo CEEG. RESULTS: The incidence of ES was 26%. Variables associated with increased ES risk included age, acute encephalopathy category, clinical seizures prior to CEEG initiation, EEG background, and epileptiform discharges. Combining clinical and EEG variables yielded better model performance (AUC 0.80) than clinical variables alone (AUC 0.69; P < .01). At a 0.10 cutoff selected to emphasize sensitivity, the optimal model had a sensitivity of 92%, specificity of 37%, positive predictive value of 34%, and negative predictive value of 93%. If applied, the model would limit 29% of patients from undergoing CEEG while failing to identify 8% of patients with ES. SIGNIFICANCE: A model employing readily available clinical and EEG variables could target limited CEEG resources to critically ill children at highest risk for ES, making CEEG-guided management a more viable neuroprotective strategy.

PLCε knockdown overcomes drug resistance to androgen receptor antagonist in castration-resistant prostate cancer by suppressing the wnt3a/ß-catenin pathway.

Most prostate cancers (Pcas) develop into castration-resistant prostate cancer (CRPC) after receiving androgen deprivation therapy (ADT). The expression levels of PLCε and wnt3a are increased in Pca and regulate androgen receptor (AR) activity. However, the biological function and mechanisms of PLCε and wnt3a in CRPC remain unknown. In this study, we found that the expression levels of PLCε, wnt3a, and AR were significantly increased in CRPC tissues as well as bicalutamide-resistant-LNCaP and enzalutamide-resistant-LNCaP cells. In addition, PLCε knockdown partly restored the sensitivity of drug-resistant cells to bicalutamide and enzalutamide by inhibiting the activity of the wnt3a/ß-catenin/AR signaling axis. Interestingly, the resistance of LNCaP cells docetaxel is related to PLCε but not the wnt3a/ß-catenin pathway. We also found that the combination of PLCε knockdown and enzalutamide treatment synergistically suppressed cell proliferation, tumor growth, and bone metastasis using in vitro and in vivo experiments. Our study revealed that PLCε is involved in the progression of drug-resistance in CRPC and could be a new target for the treatment of CRPC.

Origins of possible synergistic effects in the interactions between metal atoms and MoS2/graphene heterostructures for battery applications.

The interactions between metals and two-dimensional materials, in particular, the adsorption energies, strongly determine the performances of rechargeable batteries. Previously, it has been demonstrated that heterostructures of two dimensional (2D) materials can lead to enhanced metal adsorptions, which were ascribed to the existence of 'synergistic' effects amongst metal atoms and two different 2D materials. However, further investigations are still required to reveal the physical mechanisms behind the contribution of these possible 'synergistic' effects for metal intercalations in 2D heterostructures. Here, we selected MoS2/graphene as a prototypical system, and we examined the adsorption and intercalation thermochemistry of monovalent atoms (Li, Na and K) and multivalent atoms (Mg, Ca and Al) using density-functional theory (DFT) calculations. The synergistic effects arising from charge polarizations in these systems were quantified using the three-body interaction energy terms. Our results show strong system dependencies whereby the interactions between the Mg or Ca atom with the MoS2/graphene heterostructures might exhibit cooperative bindings. Nevertheless, metal adsorptions on top of the graphene surface were all found to be anti-cooperative in this case. Our results suggest that enhancement of metal adsorptions using 2D heterostructures is predominantly driven by increasing dispersion interactions due to increases in the interaction surface areas.

Knockdown of Phospholipase Cε (PLCε) Inhibits Cell Proliferation via Phosphatase and Tensin Homolog Deleted on Chromosome 10 (PTEN)/AKT Signaling Pathway in Human Prostate Cancer.

BACKGROUND Phospholipase Cε (PLCε), a member of the plc family, has been extensively studied to reveal its role in the regulation of different cell functions, but understanding of the underlying mechanisms remains limited. In the present study, we explored the effects of PLCε on PTEN (phosphatase and tensin homolog deleted on chromosome 10) in cell proliferation in prostate cancer cells. MATERIAL AND METHODS We assessed PLCε and PTEN expression in human benign prostate tissues compared to prostate cancer tissues by immunohistochemistry. Lentivirus-shPLCε (LV-shPLCε) was designed to silence PLCε expression in DU145 and PC3 cell lines, and the effectiveness was tested by qRT-PCR and Western blotting. MTT assay and colony formation assay were conducted to observe cell proliferation. Western blotting and immunofluorescence assays were used to detect changed PTEN expression in DU145. RESULTS We observed that PLCε expression was reduced in human benign prostate tissues compared to prostate cancer tissues, while PTEN expression showed the opposite trend. Silencing of the PLCε gene significantly inhibited cell proliferation in DU145 and PC3 cell lines. DU145 is a PTEN-expressing cell, while PC3 is PTEN-deficient. After infection by LV-shPLCε, we noticed that PTEN expression was up-regulated in DU145 cells but not in PC3 cells. Furthermore, we found that PLCε gene knockdown decreased P-AKT protein levels, but AKT protein levels were not affected. Immunofluorescence assays showed that PTEN expression had an intracellular distribution change in the DU145 cell line, and Western blot analysis showed that PTEN was obviously up-regulated in cell nucleus and cytoplasm. CONCLUSIONS PLCε is an oncogene, and knockdown of expression of PLCe inhibits PCa cells proliferation via the PTEN/AKT signaling pathway.

[Study of cancer cell apoptosis induced by Schizonepeta tenuifolia with microfluidic chip technology].

This study was designed to elucidate the chemical composition and anti-cancer effects of Schizonepeta tenuifolia's ethanol extracts. Microfluidic technology was used in the study of Schizonepeta tenuifolia from 9 different geographic regions. The ethanol extracts were examined with HPLC to establish their Fingerprints in order to analyze the relationship between the spectrum and efficacy index through Grey Correlation software, and a rapid HPLC-Q-TOF/MS method was established. The result shows that chromatographic peaks of the 19, 6, 11, 16, 18th are the representative diosmetin, luteoloside, hesperidin, luteolin, and apigenin. The 10, 12, 20th peaks may be naringenin-7-O-glucuronide or quercitrin, rosmarinate or acetylcorynoline, and 5,7-dihydroxy-6,4-dimethoxy flavone. The major chemical composition of Schizonepeta tenuifolia was found to have the anti-lung-tumor effects. A new method was established for the quality control of traditional Chinese medicine.

[Study on relationship between efficacy against lung cancer and different parts of Schizonepeta tenuifolia based on microfluidic chip technology].

In order to further clarify the rational use of different medicinal parts of Schizonepeta, microfluidic technology was used in this study to investigate the differences in drug efficacy against lung cancer in vitro. The ethanol extracts were examined with HPLC to establish their fingerprints in order to analyze the relationship between the spectrum and efficacy index through Grey Correlation software, and a rapid HPLC-Q-TOF/MS method was established. The result in vitro shows that the effect and components of different medicinal parts had a certain differences, and apoptosis and necrosis rate from big to small in turn is leaf, flower, root, stem. The chromatographic peaks of the 26, 12, 2, 6 and 15th are the luteolin, icynaroside, rosmarinic, caffeic acid, and hesperidin, while the 20 and 10th may be dan phenolic acid L and benzoic acid. On the one hand, preliminary study reflects that the root of Schizonepeta tenuifolia may be developed into the medicinal parts in future. On the other hand, the major chemical composition of S. tenuifolia was found to have the anti-lung-tumor effects. This new method was established for the quality control and the rational use of different parts of traditional Chinese medicine.

A lysosome-targeted fluorescent probe for fluorescence imaging of hypochlorous acid in living cells and in vivo.

Lysosomes, as crucial acidic organelles in cells, play a significant role in cellular functions. The levels and distribution of hypochlorous acid (HOCl) within lysosomes can profoundly impact their biological functionality. Hence, real-time monitoring of the concentration of HOCl in lysosomes holds paramount importance for further understanding various physiological and pathological processes associated with lysosomes. In this study, we developed a bodipy-based fluorescent probe derived from pyridine and phenyl selenide for the specific detection of HOCl in aqueous solutions. Leveraging the probe's sensitive photoinduced electron transfer effect from phenyl selenide to the fluorophore, the probe exhibited satisfactory high sensitivity (with a limit of detection of 5.2 nM and a response time of 15 s) to hypochlorous acid. Further biological experiments confirmed that the introduction of the pyridine moiety enabled the probe molecule to selectively target lysosomes. Moreover, the probe successfully facilitated real-time monitoring of HOCl in cell models stimulated by N-acetylcysteine (NAC) and lipopolysaccharide (LPS), as well as in a normal zebrafish model. This provides a universal method for dynamically sensing HOCl in lysosomes.

Green synthesis of polyimide by using an ethanol solvothermal method for aqueous zinc batteries.

Polyimides (PIs) are welcomed by battery researchers because of their exceptional heat resistance, structural design versatility, and ion-bearing capabilities. However, most of the reported PIs are synthesized by using toxic and hazardous reagents, such as ethylenediamine, p-phenylenediamine, 1-methyl-2-pyrrolidone (NMP), N,N-dimethylacetamide (DMAc), N,N-dimethylformamide (DMF), etc., which are not conducive to environmentally friendly development. In this paper, we aim at employing green solvents and raw materials to prepare PIs using a facile solvothermal method. The reactants are urea and 1,4,5,8-naphthalene tetracarboxylic acid dianhydride (NTCDA). The solvents include pure water, pure ethanol, or water-ethanol mixed solvent. The volume ratio of ethanol in the mixed solvent is regulated to obtain the optimum synthesis condition. Depending on the proportion of ethanol, the polyimide products are labeled as U-PI-0, U-PI-50, U-PI-100, etc. The polymerization degree and structure of synthesized PIs are characterized by gel permeation chromatography (GPC), X-ray diffraction (XRD), scanning electron microscopy (SEM), etc. The results indicate that U-PIs exhibit diverse morphological features, including small fragmented, strip-like, and sheet-like structures, and have relative molecular weights ranging from 7500 to 83 000. Notably, the sheet-like U-PI-100 possesses the largest specific surface area, reaching up to 4.20 m2 g-1. When employed as an electrode material in aqueous zinc batteries, U-PI-100 demonstrates superior electrochemical performance compared to others. At a charge-discharge rate of 0.05C, the initial charge/discharge capacity of U-PI-100 is measured to be 314.2/443.7 mA h g-1.