Successful neoadjuvant treatment of EGFR exon 19 deletion combined with TP53 mutation in non-small cell lung cancer using aumolertinib after osimertinib-induced myocardial damage: a case report and literature review.

The development of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) represents a paradigm shift in the treatment of lung cancer with EGFR mutations. Aumolertinib has been shown to be a safe agent in the registry study. However, successful rechallenge with aumolertinib following osimertinib-induced myocardial damage has not been reported. In this article, a case of neoadjuvant therapy for lung adenocarcinoma is retrospectively analyzed, and the relevant literature is reviewed. The patient was diagnosed with stage IIIA lung adenocarcinoma, and genetic testing revealed EGFR exon 19 deletion mutation combined with Tumor Protein p53 (TP53) mutation. The mutation abundance is 33.5 and 14%, respectively. One month after osimertinib treatment, the patient developed myocardial damage, and abnormal indicators such as myocardial enzyme spectrum showed abnormalities and cardiac insufficiency, followed by pulmonary hypertension and pulmonary edema. Aumolertinib was subsequently used for treatment, following which the myocardial enzyme spectrum returned to normal, and the symptoms of bilateral interstitial edema disappeared. In addition to the disappearance of adverse reactions, the therapeutic effect was excellent; the lung lesions and mediastinal lymph nodes were significantly reduced, and the operation was successfully conducted. This is the first report of successful neoadjuvant treatment of EGFR exon 19 deletion combined with TP53 mutation in NSCLC using aumolertinib after osimertinib-induced myocardial damage. The results suggested that aumolertinib had fewer adverse reactions in patients with EGFR exon 19 deletion combined with TP53 mutation, and aumolertinib may be a potential neoadjuvant therapy for stage IIIA lung cancer.

Kaempferol induces mitochondrial dysfunction and mitophagy by activating the LKB1/AMPK/MFF pathway in breast precancerous lesions.

Kaempferol has been suggested to be an effective anticancer agent in several malignant tumors. However, its function and mechanisms in breast precancerous lesions remain largely elusive. Here, we showed that kaempferol induced excessive mitochondrial fission and mitochondrial damage with activated mitochondrial fission factor (MFF)-mediated dynamin-related protein (DRP) 1 mitochondrial translocation. As a result, the PTEN-induced putative kinase 1 (PINK1)/Parkin signaling pathway was activated, accompanied by excessive mitophagy and reduced mitochondrial mass in cells. We also revealed that kaempferol-induced lethal mitophagy contributed to inhibiting breast precancerous lesion growth in vitro and in vivo. Furthermore, we verified serine/threonine kinase 11 (STK11/LKB1)/AMP-activated protein kinase (AMPK) pathway deficiency in breast precancerous lesions. Moreover, LKB1/AMPK pathway reactivation by kaempferol was required for excessive mitochondrial fission and lethal mitophagy. Taken together, our findings shed new light on the molecular mechanisms related to breast cancer prevention by kaempferol and provide evidence for its potential clinical application.

Radiomics under 2D regions, 3D regions, and peritumoral regions reveal tumor heterogeneity in non-small cell lung cancer: a multicenter study.

PURPOSE: Lung cancer has significant genetic and phenotypic heterogeneity, leading to poor prognosis. Radiomic features have emerged as promising predictors of the tumor phenotype. However, the role of underlying information surrounding the cancer remains unclear. MATERIALS AND METHODS: We conducted a retrospective study of 508 patients with NSCLC from three institutions. Radiomics models were built using features from six tumor regions and seven classifiers to predict three prognostically significant tumor phenotypes. The models were evaluated and interpreted by the mean area under the receiver operating characteristic curve (AUC) under nested cross-validation and Shapley values. The best-performing predictive models corresponding to six tumor regions and three tumor phenotypes were identified for further comparative analysis. In addition, we designed five experiments with different voxel spacing to assess the sensitivity of the experimental results to the spatial resolution of the voxels. RESULTS: Our results demonstrated that models based on 2D, 3D, and peritumoral region features yielded mean AUCs and 95% confidence intervals of 0.759 and [0.747-0.771] for lymphovascular invasion, 0.889 and [0.882-0.896] for pleural invasion, and 0.839 and [0.829-0.849] for T-staging in the testing cohort, which was significantly higher than all other models. Similar results were obtained for the model combining the three regional features at five voxel spacings. CONCLUSION: Our study revealed the predictive role of the developed methods with multi-regional features for the preoperative assessment of prognostic factors in NSCLC. The analysis of different voxel spacing and model interpretability strengthens the experimental findings and contributes to understanding the biological significance of the radiological phenotype.

To explore immune synergistic function of Quercetin in inhibiting breast cancer cells.

BACKGROUND: The precancerous disease of breast cancer is an inevitable stage in the tumorigenesis and development of breast neoplasms. Quercetin (Que) has shown great potential in breast cancer treatment by inhibiting cell proliferation and regulating T cell function. γδ T cells are a class of nontraditional T cells that have long attracted attention due to their potential in immunotherapy. In this study, we revealed the immunomodulatory function of Que through regulation of the JAK/STAT1 signaling pathway, which was followed by the synergistic killing of breast cancer cells. METHODS: In the experimental design, we first screened target genes with or without Que treatment, and we intersected the Que target with the disease target by functional enrichment analysis. Second, MCF-10A, MCF-10AT, MCF-7 and MDA-MB-231 breast cancer cell lines were treated with Que for 0 h, 24 h and 48 h. Then, we observed the expression of its subsets by coculturing Que and γδ T cells and coculturing Que and γδ T cells with breast tumor cells to investigate their synergistic killing effect on tumor cells. Finally, Western blotting was used to reveal the changes in proteins related to the JAK/STAT1 signaling pathway after Que treatment in MCF-10AT and MCF-7 cells for 48 h. RESULTS: The pathway affected by Que treatment was the JAK/STAT1 signaling pathway and was associated with precancerous breast cancer, as shown by network pharmacology analysis. Que induced apoptosis of MCF-10AT, MCF-7 and MDA-MB-231 cells in a time- and concentration-dependent manner (P < 0.05). Most importantly, Que promoted the differentiation of γδ T cells into the Vδ2 T cell subpopulation. The best ratio of effector cells to target cells (E/T) was 10:1, the killing percentages of γδ T cells against MCF-10A, MCF-10AT, MCF-7, and MDA-MB-231 were 61.44 ± 4.70, 55.52 ± 3.10, 53.94 ± 2.74, and 53.28 ± 1.73 (P = 0.114, P = 0.486, and P = 0.343, respectively), and the strongest killing effect on precancerous breast cancer cells and breast cancer cells was found when the Que concentration was 5 µM and the E/T ratio was 10:1 (64.94 ± 3.61, 64.96 ± 5.45, 55.59 ± 5.98, and 59.04 ± 5.67, respectively). In addition, our results showed that Que increased the protein levels of IFNγ-R, p-JAK2 and p-STAT1 while decreasing the protein levels of PD-L1 (P < 0.0001). CONCLUSIONS: In conclusion, Que plays a synergistic role in killing breast cancer cells and promoting apoptosis by regulating the expression of IFNγ-R, p-JAK2, p-STAT1 and PD-L1 in the JAK/STAT1 signaling pathway and promoting the regulation of γδ T cells. Que may be a potential drug for the prevention of precancerous breast cancer and adjuvant treatment of breast cancer.

Structure-activity relationship, in vitro and in vivo evaluation of novel dienyl sulphonyl fluorides as selective BuChE inhibitors for the treatment of Alzheimer's disease.

To discover novel scaffolds as leads against dementia, a series of δ-aryl-1,3-dienesulfonyl fluorides with α-halo, α-aryl and α-alkynyl were assayed for ChE inhibitory activity, in which compound A10 was identified as a selective BuChE inhibitor (IC50 = 0.021 µM for eqBChE, 3.62 µM for hBuChE). SAR of BuChE inhibition showed: (i) o- > m- > p-; -OCH3 > -CH3 > -Cl (-Br) for δ-aryl; (ii) α-Br > α-Cl, α-I. Compound A10 exhibited neuroprotective, BBB penetration, mixed competitive inhibitory effect on BuChE (Ki = 29 nM), and benign neural and hepatic safety. Treatment with A10 could almost entirely recover the Aß1-42-induced cognitive dysfunction to the normal level, and the assessment of total amount of Aß1-42 confirmed its anti-amyloidogenic profile. Therefore, the potential BuChE inhibitor A10 is a promising effective lead for the treatment of AD.

Current Situation and Mental Health of Pregnant Women During the Prevention and Control of Novel Coronavirus Infection: A Cross-Sectional Study on the Investigation of Influencing Factors.

Background: COVID-19 is a highly contagious respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which became a global public health crisis. In the past 3 years, the COVID-19 pandemic has resulted in a dramatic increase in the occurrence of psychological symptoms such as depression, anxiety, and stress in global populations. Therefore, it is important to help pregnant women cope with major public emergencies and improve their physical and mental health. Objective: To investigate the status and influencing factors of anxiety, insomnia, and psychological stress disorder in pregnant women with COVID-19 to provide a theoretical basis for psychological intervention in pregnant women in the case of public health emergency events. Patients and methods: A cross-sectional survey was conducted with 435 pregnant women from multiple tertiary hospitals in Zhengzhou from November 6 to December 6, 2022. The questionnaire contents included the general information of pregnant women, insomnia scale, generalized anxiety scale, and the revised version of the Accident Impact Scale. Results: There are 251 pregnant women with anxiety (57.7%, 95% CI: (53.0%-62.4%).There are 166 pregnant women with insomnia.(38.2%, 95% CI: 33.6%-42.7%), There are 314 pregnant women with stress disorder.(72.2%, 95% CI: 68.0%-76.4%). During the epidemic prevention and control period, whether pregnant women had a history of adverse pregnancy had a statistically significant difference in anxiety, insomnia and stress disorders. Conclusion and Recommendation: During the COVID-19 pandemic, pregnant women appeared to generally have anxiety, insomnia, and stress disorders. Poor pregnancy history is a protective factor for pregnant women with anxiety, insomnia, and post-traumatic stress disorder. In the case of similar public health emergencies, attention bias modification (ABM) may be a potential intervention measure to provide potentially new ideas for alleviating the psychological disorders of pregnant women during this special period.

Exploring non-invasive precision treatment in non-small cell lung cancer patients through deep learning radiomics across imaging features and molecular phenotypes.

BACKGROUND: Accurate prediction of tumor molecular alterations is vital for optimizing cancer treatment. Traditional tissue-based approaches encounter limitations due to invasiveness, heterogeneity, and molecular dynamic changes. We aim to develop and validate a deep learning radiomics framework to obtain imaging features that reflect various molecular changes, aiding first-line treatment decisions for cancer patients. METHODS: We conducted a retrospective study involving 508 NSCLC patients from three institutions, incorporating CT images and clinicopathologic data. Two radiomic scores and a deep network feature were constructed on three data sources in the 3D tumor region. Using these features, we developed and validated the 'Deep-RadScore,' a deep learning radiomics model to predict prognostic factors, gene mutations, and immune molecule expression levels. FINDINGS: The Deep-RadScore exhibits strong discrimination for tumor molecular features. In the independent test cohort, it achieved impressive AUCs: 0.889 for lymphovascular invasion, 0.903 for pleural invasion, 0.894 for T staging; 0.884 for EGFR and ALK, 0.896 for KRAS and PIK3CA, 0.889 for TP53, 0.895 for ROS1; and 0.893 for PD-1/PD-L1. Fusing features yielded optimal predictive power, surpassing any single imaging feature. Correlation and interpretability analyses confirmed the effectiveness of customized deep network features in capturing additional imaging phenotypes beyond known radiomic features. INTERPRETATION: This proof-of-concept framework demonstrates that new biomarkers across imaging features and molecular phenotypes can be provided by fusing radiomic features and deep network features from multiple data sources. This holds the potential to offer valuable insights for radiological phenotyping in characterizing diverse tumor molecular alterations, thereby advancing the pursuit of non-invasive personalized treatment for NSCLC patients.

Non-invasive decision support for clinical treatment of non-small cell lung cancer using a multiscale radiomics approach.

BACKGROUND: Selecting therapeutic strategies for cancer patients is typically based on key target-molecule biomarkers that play an important role in cancer onset, progression, and prognosis. Thus, there is a pressing need for novel biomarkers that can be utilized longitudinally to guide treatment selection. METHODS: Using data from 508 non-small cell lung cancer (NSCLC) patients across three institutions, we developed and validated a comprehensive predictive biomarker that distinguishes six genotypes and infiltrative immune phenotypes. These features were analyzed to establish the association between radiological phenotypes and tumor genotypes/immune phenotypes and to create a radiological interpretation of molecular features. In addition, we assessed the sensitivity of the models by evaluating their performance at five different voxel intervals, resulting in improved generalizability of the proposed approach. FINDINGS: The radiomics model we developed, which integrates clinical factors and multi-regional features, outperformed the conventional model that only uses clinical and intratumoral features. Our combined model showed significant performance for EGFR, KRAS, ALK, TP53, PIK3CA, and ROS1 mutation status with AUCs of 0.866, 0.874, 0.902, 0.850, 0.860, and 0.900, respectively. Additionally, the predictive performance for PD-1/PD-L1 was 0.852. Although the performance of all models decreased to different degrees at five different voxel space resolutions, the performance advantage of the combined model did not change. CONCLUSIONS: We validated multiscale radiomic signatures across tumor genotypes and immunophenotypes in a multi-institutional cohort. This imaging-based biomarker offers a non-invasive approach to select patients with NSCLC who are sensitive to targeted therapies or immunotherapy, which is promising for developing personalized treatment strategies during therapy.

Prognostic analyses of genes associated with anoikis in breast cancer.

Breast cancer (BRCA) is the most diagnosed cancer worldwide and is responsible for the highest cancer-associated mortality among women. It is evident that anoikis resistance contributes to tumour cell metastasis, and this is the primary cause of treatment failure for BRCA. However, anoikis-related gene (ARG) expression profiles and their prognostic value in BRCA remain unclear. In this study, a prognostic model of ARGs based on The Cancer Genome Atlas (TCGA) database was established using a least absolute shrinkage and selection operator analysis to evaluate the prognostic value of ARGs in BRCA. The risk factor graph demonstrated that the low-risk group had longer survival than the high-risk group, implying that the prognostic model had a good performance. We identified 11 ARGs that exhibited differential expression between the two risk groups in TCGA and Gene Expression Omnibus databases. Through Gene Ontology and Kyoto Encyclopaedia of Genes and Genomes enrichment analyses, we revealed that the screened ARGs were associated with tumour progression and metastasis. In addition, a protein-protein interaction network showed potential interactions among these ARGs. Furthermore, gene set enrichment analysis suggested that the Notch and Wnt signalling pathways were overexpressed in the high-risk group, and gene set variation analysis revealed that 38 hallmark genes differed between the two groups. Moreover, Kaplan-Meier survival curves and receiver operating characteristic curves were used to identify five ARGs (CD24, KRT15, MIA, NDRG1, TP63), and quantitative polymerase chain reaction was employed to assess the differential expression of these ARGs. Univariate and multivariate Cox regression analyses were then performed for the key ARGs, with the best prediction of 3 year survival. In conclusion, ARGs might play a crucial role in tumour progression and serve as indicators of prognosis in BRCA.

Modulation of expression of p16 and her2 in rat breast tissues of mammary hyperplasia model by external use of rupifang extract.

OBJECTIVE: To observe the effect of Rupifang Extract in external use on expression of proto-oncogenes her2 and tumor suppression genes p16 in rat breast tissues of mammary hyperplasia model. To explore the mechanisms of Rupifang Extract in external use for preventing and treating mammary hyperplasia. METHODS: Thirty virginal female Wistar rats were randomized into 5 groups, 6 in each, A: blank control group; B: model group; C: the low dose group of Rupifang; D: the middle dose group of Rupifang; and E: The high dose group of Rupifang. The mammary hyperplasia rat models were produced by injecting estradiol benzoate and progesterone and irritating by tail nipping. Drug intervention was also launched during the model formation. After 30 days, the expression of her2 and p16 in breast tissues of rats in each group were detected by the SP immunohistochemical method. RESULTS: Compared with Blank control group, the expression of her2 in breast tissues in Model group was higher, and the expression of p16 was lower (P < 0.05 or P < 0.01). After intervention with Rupifang Extract, compared with Model group, the expression of her2 in breast tissues in Rupifang groups was lower, and the expression of p16 higher (P < 0.05 or P < 0.01). CONCLUSION: The mechanisms of Rupifang Extract in external application for preventing and treating mammary hyperplasia may be reducing the expression of proto-oncogenes her2 and increasing the expression of tumor suppression genes p16.

Emotional Contagion in Physical-Cyber Integrated Networks: The Phase Transition Perspective.

Understanding the emotional contagion process in the crowd will help to take measures in advance to avoid the large-scale spread of negative emotions in emergencies and reduce the loss of lives and properties. Studying the phase transition phenomenon is fundamental to analyzing and evaluating the crowd emotional contagion. However, it is a challenging issue since most people participate in both the physical and cyber networks at the same time. In this article, we focus on the emotional contagion in physical-cyber integrated networks from the phase transition perspective. To achieve this, we first construct a physical-cyber integrated network model to describe the interactions between physical and cyber networks. Second, we build an emotional contagion model to capture the characteristics of emotional contagion in the physical and cyber integrated networks accurately. Finally, we study the phase transition phenomenon of emotional contagion and identify the critical threshold by mapping the emotional contagion to the joint site/bond percolation model. Numerical simulations and experiments further support and enrich our conclusions. The proposed method is expected to provide guidance for controlling emotional contagion in emergencies.

Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential.

The high-throughput extraction of quantitative imaging features from medical images for the purpose of radiomic analysis, i.e., radiomics in a broad sense, is a rapidly developing and emerging research field that has been attracting increasing interest, particularly in multimodality and multi-omics studies. In this context, the quantitative analysis of multidimensional data plays an essential role in assessing the spatio-temporal characteristics of different tissues and organs and their microenvironment. Herein, recent developments in this method, including manually defined features, data acquisition and preprocessing, lesion segmentation, feature extraction, feature selection and dimension reduction, statistical analysis, and model construction, are reviewed. In addition, deep learning-based techniques for automatic segmentation and radiomic analysis are being analyzed to address limitations such as rigorous workflow, manual/semi-automatic lesion annotation, and inadequate feature criteria, and multicenter validation. Furthermore, a summary of the current state-of-the-art applications of this technology in disease diagnosis, treatment response, and prognosis prediction from the perspective of radiology images, multimodality images, histopathology images, and three-dimensional dose distribution data, particularly in oncology, is presented. The potential and value of radiomics in diagnostic and therapeutic strategies are also further analyzed, and for the first time, the advances and challenges associated with dosiomics in radiotherapy are summarized, highlighting the latest progress in radiomics. Finally, a robust framework for radiomic analysis is presented and challenges and recommendations for future development are discussed, including but not limited to the factors that affect model stability (medical big data and multitype data and expert knowledge in medical), limitations of data-driven processes (reproducibility and interpretability of studies, different treatment alternatives for various institutions, and prospective researches and clinical trials), and thoughts on future directions (the capability to achieve clinical applications and open platform for radiomics analysis).

Prospective clinical research of radiomics and deep learning in oncology: A translational review.

Radiomics and deep learning (DL) hold transformative promise and substantial and significant advances in oncology; however, most methods have been tested in retrospective or simulated settings. There is considerable interest in the biomarker validation, clinical utility, and methodological robustness of these studies and their deployment in real-world settings. This review summarizes the characteristics of studies, the level of prospective validation, and the overview of research on different clinical endpoints. The discussion of methodological robustness shows the potential for independent external replication of prospectively reported results. These in-depth analyses further describe the barriers limiting the translation of radiomics and DL into primary care options and provide specific recommendations regarding clinical deployment. Finally, we propose solutions for integrating novel approaches into the treatment environment to unravel the critical process of translating AI models into the clinical routine and explore strategies to improve personalized medicine.

Guidewire-Assisted Reduction Technology Combined with Postural Reduction Improves the Success Rate of Internal Vein Catheterisation.

Objective: To investigate the value of guidewire-assisted reduction technology (which increases the stiffness of a catheter through the use of a guidewire, thereby protecting the puncture point and distal vein from breakage) combined with postural reduction for malpositioned catheters in the internal jugular vein during peripherally inserted central venous catheter catheterisation. Methods: From January 2015 to August 2020, we used ultrasound to perform guided puncture and monitoring. We identified the tip of the catheter as malpositioned in the internal jugular vein in 99 patients during the catheterisation process. These patients were divided randomly into a control group and an experimental group. In the control group, 43 cases received guidewire-assisted reduction technology, while in the experimental group, 56 patients received guidewire-assisted reduction technology combined with an upright posture. This study compared the efficacy of these two methods. Results: The results showed that 30 catheters were reduced successfully in the control group, with a success rate of 69.8%. In the experimental group, 53 cases were successfully reduced, with a success rate of 94.6%. The catheter reduction success rate in the experimental group was significantly higher than in the control group; this was a statistically significant difference (P=0.001). Conclusion: Guidewire-assisted reduction technology combined with postural reduction can improve the success rate of the reduction of malpositioned catheters in the internal jugular vein.

Effects of Naltrexone on Expression of Lipid Metabolism-Related Proteins in Liver Steatosis Induced by Endoplasmic Reticulum Stress in Mice.

This study aimed to explore the effect of naltrexone on the expression of lipid metabolism-related proteins in liver steatosis induced by endoplasmic reticulum stress in mice. Thirty inbred mice (C57BL/6J) were divided into three groups: group A (normal control group), group B (model control), and group C (naltrexone group). The male mice in group A were fed a regular diet, and the mice in groups B and C were fed a high-fat diet. Liver steatosis was observed by histopathological sections. Mouse liver (alanine aminotransferase (ALT) and triglyceride (TC)) content (glucose regulatory protein (GRP78), endoplasmic reticulum transmembrane protein kinase-1α (IRE-1α), C/EBP source protein (CHOP), cysteine-containing aspartate proteolytic enzyme 12 (caspase-12), B lymphoma-2 (Bcl-2), and cell death mediator (Bim)) was detected. Compared with group A, bodyweight, fat weight, ALT, TG, and hepatic steatosis were significantly increased in B and C groups (P < 0.05); compared with group B, group C showed a significant decrease in bodyweight, fat weight, ALT, TG, and hepatic steatosis (P < 0.05). Compared with group A, the expression levels of GRP78, IRE-1α, CHOP, caspase-12, and Bim in liver tissue of groups B and C mice were increased. Bcl-2 decreased (P < 0.05). Compared with group B and group C after naltrexone intervention, the expression levels of GRP78, IRE-1α, CHOP, caspase-12, and Bim decreased significantly, and Bcl-2 increased significantly (P < 0.05). Naltrexone can effectively reduce bodyweight and adipose tissue accumulation, reduce liver fat lesions, improve the expression of lipid metabolism-related proteins and endoplasmic reticulum stress, reduce liver lipid synthesis, and protect liver cells.

ß-Boswellic Acid Suppresses Breast Precancerous Lesions via GLUT1 Targeting-Mediated Glycolysis Inhibition and AMPK Pathway Activation.

Breast carcinoma is a multistep progressive disease. Precancerous prevention seems to be crucial. ß-Boswellic acid (ß-BA), the main component of the folk medicine Boswellia serrata (B. serrata), has been reported to be effective in various diseases including tumors. In this work, we demonstrated that ß-BA could inhibit breast precancerous lesions in rat disease models. Consistently, ß-BA could suppress proliferation and induce apoptosis on MCF-10AT without significantly influencing MCF-10A. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that ß-BA may interfere with the metabolic pathway. Metabolism-related assays showed that ß-BA suppressed glycolysis and reduced ATP production, which then activated the AMPK pathway and inhibited the mTOR pathway to limit MCF-10AT proliferation. Further molecular docking analysis suggested that GLUT1 might be the target of ß-BA. Forced expression of GLUT1 could rescue the glycolysis suppression and survival limitation induced by ß-BA on MCF-10AT. Taken together, ß-BA could relieve precancerous lesions in vivo and in vitro through GLUT1 targeting-induced glycolysis suppression and AMPK/mTOR pathway alterations. Here, we offered a molecular basis for ß-BA to be developed as a promising drug candidate for the prevention of breast precancerous lesions.

The Chinese Herbal Formula Ruyan Neixiao Cream Inhibits Angiogenesis of Precancerous Breast Lesions via Regulation of Ras/Raf/MEK/ERK Signaling Pathway.

Ruyan Neixiao Cream (RUc) is a traditional Chinese herbal formula which can effectively inhibit the angiogenesis of breast precancerous lesions. In order to reveal the specific mechanism, we carried out experiments in vitro and in vivo. We found that the conditioned medium of MCF-10AT cells treated with RUc transdermal solution (RUt) could significantly inhibit the proliferation, migration, invasion, tube formation of HUVECs and the capillary formation of rat aortic rings. RUt may down-regulate the expression of VEGF, MMP2, and MMP9 in MCF-10AT medium by down-regulating miR-21 and up-regulating TIMP-3 and RECK. We further confirmed in rats that the microvascular density of precancerous lesions decreased significantly after external use of RUc, which may be related to the inhibition of Ras/Raf/MEK/ERK signaling pathway related proteins. Presumptively, RUc may inhibit the angiogenesis of breast precancerous lesions by inhibiting Ras/Raf/MEK/ERK signaling pathway, thus relieving the inhibition of miR-21 on TIMP-3 and RECK, then down-regulating the secretion of angiogenic factors.

Feedback loop between hepatocyte nuclear factor 1α and endoplasmic reticulum stress mitigates liver injury by downregulating hepatocyte apoptosis.

Hepatocyte nuclear factor alpha (HNF1α), endoplasmic reticulum (ER) stress, and hepatocyte apoptosis contribute to severe acute exacerbation (SAE) of liver injury. Here, we explore HNF1α-ER stress-hepatocyte apoptosis interaction in liver injury. LO2, HepG2 and SK-Hep1 cells were treated with thapsigargin (TG) or tunicamycin (TM) to induce ER stress. Carbon tetrachloride (CCl4) was used to induce acute liver injury in mice. Low-dose lipopolysaccharide (LPS) exacerbated liver injury in CCl4-induced mice. Significant apoptosis, HNF1α upregulation, and nuclear factor kappa B (NF-κB) activation were observed in human-derived hepatocytes during ER stress. Knockdown of Rela, NF-κB p65, inhibited the HNF1α upregulation. Following CCl4 treatment ER stress, apoptosis, HNF1α expression and RelA phosphorylation were significantly increased in mice. HNF1α knockdown reduced activating transcription factor 4 (ATF4) expression, and aggravated ER stress as well as hepatocyte apoptosis in vivo and in vitro. The double fluorescent reporter gene assay confirmed that HNF1α regulated the transcription of ATF4 promoter. LPS aggravated CCl4-induced liver injury and reduced HNF1α, and ATF4 expression. Therefore, in combination, HNF1α and ER stress could be mutually regulated forming a feedback loop, which helps in protecting the injured liver by down-regulating hepatocyte apoptosis. Low-dose LPS aggravates hepatocyte apoptosis and promotes the SAE of liver injury by interfering with the feedback regulation of HNF1α and ER stress in acute liver injury.

Depression and Related Factors in Patients with Parkinson's Disease at High Altitude.

PURPOSE: Depression seems to aggravate progression of Parkinson's disease (PD). Hypoxia stress may be one of the pathogenic factors leading to PD. We investigated the characteristics of PD and factors related to Parkinson's disease depression (PDD) at high altitude (mean altitude ≥2300 m). PATIENTS AND METHODS: Totally 221 PD patients of three different nationalities (Han, Hui, and Tibetan) were recruited in a high-altitude hospital. Depression was present in 55.6% of them. Patient data were examined, including demographic information, medical history, disease duration and family history. Psychopathological characteristics and motor signs were assessed by the Hamilton Depression scale (HAMD) and scales for motor and non-motor symptoms in the Unified Parkinson's Disease Rating Scale (UPDRS). Progression of PD was evaluated by the modified Hoehn and Yahr (H-Y) staging system. RESULTS: Mean age (47.1% men) was 68.25±13.67 years old, with disease duration of 4.18±5.13 years and median H-Y scores 2.07±0.97 points. Among three different nationalities, PD rate was 69.2% in Han nationals, 17.6% in Hui nationals and 13.1% in Tibetans of 221 PD patients. Compared with the non-depressed PD group, female, no-smoking and living alone rates, and dysphagia, pain, H-Y stage, ADL, UPDRS-I, UPDRS-III, HAMA, and PSQI scores were significantly increased in the PDD group, while MMSE scores were significantly decreased (P<0.05 or P<0.01). PD patients of Han and Hui nationalities had increased depression rates compared with Tibetan individuals (P<0.05). Compared with the mild depression group, the moderate and severe depression groups had significantly increased salivation, dysphagia, H-Y stage, UPDRS-I, UPDRS-III, HAMA, and PSQI scores (P<0.05 or P<0.01). Living alone rates and ADL scores were increased in the severe depression group (P<0.05). Logistic regression analysis showed that living alone (OR=19.833, 95% CI: 2.758-142.624, P<0.01), UPDRS-III score (OR=1.079, 95% CI: 1.009-1.153, P<0.05), and PSQI score (OR=1.538, 95% CI: 1.347-1.755, P<0.001) were risk factors for PDD. Male gender (OR=0.292, 95% CI: 0.112-0.763, P<0.05) was a protective factor in PDD. CONCLUSION: PDD is associated with gender, ethnicity, loneliness, non-motor symptoms (NMSs), motor symptoms, and disease severity, and depression severity. Living alone, dyskinesia, and sleep disorder are risk factors for PDD at high altitude. A relative protection against depression was observed in the Tibetan population.