Recombinant Human Endostatin Endostar Inhibits Tumor Growth and Metastasis in a Mouse Xenograft Model of Colon Cancer

To investigate the effects of recombinant human endostatin Endostar on metastasis and angiogenesis and lymphangiogenesis of colorectal cancer cells in a mouse xenograft model. Colon cancer cells SW620 were injected subcutaneously into the left hind flank of nude mice to establish mouse xenograft models. The mice were treated with normal saline or Endostar subcutaneously every other day. The growth and lymph node metastasis of tumor cells, angiogenesis and lymphangiogenesis in tumor tissue were detected. Apoptosis and cell cycle distribution were studied by flow cytometry. The expression of VEGF-A, -C, or -D in SW620 cells was determined by immunoblotting assays. Endostar inhibited tumor growth and the rate of lymph node metastasis (P < 0.01). The density of blood vessels in or around the tumor area was 12.27 ± 1.21 and 22.25 ± 2.69 per field in Endostar-treated mice and controls (P < 0.05), respectively. Endostar also decreased the density of lymphatic vessels in tumor tissues (7.84 ± 0.81 vs. 13.83 ± 1.08, P < 0.05). Endostar suppresses angiogenesis and lymphangiogenesis in the lymph nodes with metastases, simultaneously. The expression of VEGF-A, -C and -D in SW620 cells treated with Endostar was substantially lower than that of controls. Endostar inhibited growth and lymph node metastasis of colon cancer cells by inhibiting angiogenesis and lymphangiogenesis in a mouse xenograft model of colon cancer

Fast Face Tracking-by-Detection Algorithm for Secure Monitoring

This work proposes a fast face tracking-by-detection (FFTD) algorithm that can perform tracking, face detection and discrimination tasks. On the basis of using the kernelized correlation filter (KCF) as the basic tracker, multitask cascade convolutional neural networks (CNNs) are used to detect the face, and a new tracking update strategy is designed. The update strategy uses the tracking result modified by detector to update the filter model. When the tracker drifts or fails, the discriminator module starts the detector to correct the tracking results, which ensures the out-of-view object can be tracked. Through extensive experiments, the proposed FFTD algorithm is shown to have good robustness and real-time performance for video monitoring scenes

Deep Learning with Transformer or Convolutional Neural Network in the Assessment of Tumor-Infiltrating Lymphocytes (TILs) in Breast Cancer Based on US Images: A Dual-Center Retrospective Study

This study aimed to explore the feasibility of using a deep-learning (DL) approach to predict TIL levels in breast cancer (BC) from ultrasound (US) images. A total of 494 breast cancer patients with pathologically confirmed invasive BC from two hospitals were retrospectively enrolled. Of these, 396 patients from hospital 1 were divided into the training cohort (n = 298) and internal validation (IV) cohort (n = 98). Patients from hospital 2 (n = 98) were in the external validation (EV) cohort. TIL levels were confirmed by pathological results. Five different DL models were trained for predicting TIL levels in BC using US images from the training cohort and validated on the IV and EV cohorts. The overall best-performing DL model, the attention-based DenseNet121, achieved an AUC of 0.873, an accuracy of 79.5%, a sensitivity of 90.7%, a specificity of 65.9%, and an F1 score of 0.830 in the EV cohort. In addition, the stratified analysis showed that the DL models had good discrimination performance of TIL levels in each of the molecular subgroups. The DL models based on US images of BC patients hold promise for non-invasively predicting TIL levels and helping with individualized treatment decision-making

Deep Learning with Transformer or Convolutional Neural Network in the Assessment of Tumor-Infiltrating Lymphocytes (TILs) in Breast Cancer Based on US Images: A Dual-Center Retrospective Study

This study aimed to explore the feasibility of using a deep-learning (DL) approach to predict TIL levels in breast cancer (BC) from ultrasound (US) images. A total of 494 breast cancer patients with pathologically confirmed invasive BC from two hospitals were retrospectively enrolled. Of these, 396 patients from hospital 1 were divided into the training cohort (n = 298) and internal validation (IV) cohort (n = 98). Patients from hospital 2 (n = 98) were in the external validation (EV) cohort. TIL levels were confirmed by pathological results. Five different DL models were trained for predicting TIL levels in BC using US images from the training cohort and validated on the IV and EV cohorts. The overall best-performing DL model, the attention-based DenseNet121, achieved an AUC of 0.873, an accuracy of 79.5%, a sensitivity of 90.7%, a specificity of 65.9%, and an F1 score of 0.830 in the EV cohort. In addition, the stratified analysis showed that the DL models had good discrimination performance of TIL levels in each of the molecular subgroups. The DL models based on US images of BC patients hold promise for non-invasively predicting TIL levels and helping with individualized treatment decision-making

Analysis of Chemical Constituents of Melastoma dodecandrum Lour. by UPLC-ESI-Q-Exactive Focus-MS/MS

The ethnic drug Melastoma dodecandrum Lour. (MDL) is widely distributed throughout South China, and is the major component of Gong Yan Ping Tablets/Capsules and Zi Di Ning Xue San. Although the pharmacological effects of MDL have been well documented, its chemical profile has not been fully determined. In this study, we have developed a rapid and sensitive UPLC-ESI-Q-Exactive Focus-MS/MS method to characterize the chemical constituents of MDL in the positive and negative ionization modes. A comparison of the chromatographic and spectrometric data obtained using this method with data from databases, the literature and reference standards allowed us to identify or tentatively characterize 109 compounds, including 26 fatty acids, 26 organic acids, 33 flavonoids, six tannins, 10 triterpenoids, two steroids and six other compounds. Notably, 55 of the compounds characterized in this study have never been detected before in this plant. The information obtained in this study therefore enriches our understanding of the chemical composition of MDL and could be used in quality control, pharmacological research and the development of drugs based on MDL. In addition, this study represents the first reported comprehensive analysis of the chemical constituents of MDL

Retrospective clinical study of eighty-one cases of intracranial mucormycosis

Background: Fungal infections of the central nervous system, especially cerebral mucormycosis or brain abscess are very rare.Cerebral mucormycosis is a rare disease. It is not an independent disease, but a secondary opportunistic infectious disease. Materials and methods: This study has collected the data of 81 cases of intracranial mucormycosis from 28 Chinese hospitals, within 37 years, as well as reviewed the literatures and retrospectively analyzed and summarized this disease′s background, clinical classifications, risk factors, pathology, clinical manifestations, diagnosis, treatment, and prognosis. Results: The 81 IM cases were aged between 15 days (the youngest) and 79 years (oldest), with a mean age of 41.6 years. Among them, 12 cases were 14 years old (the adult group ). 45 cases were male and 36 were female, with a male/female ratio of 1.25:1.0. The shortest duration of the disease was three days, and the longest was 248 days. Conclusions: This study helped to realize an early diagnosis and treatment, improve the cure rate, and reduce mortality

EIF4A3-induced circular RNA MMP9 (circMMP9) acts as a sponge of miR-124 and promotes glioblastoma multiforme cell tumorigenesis

Abstract Background Circular RNAs (circRNAs) have been found to play critical roles in the development and progression of various cancers. However, little is known about the effects of the circular RNA network on glioblastoma multiforme (GBM). Methods A microarray was used to screen circRNA expression in GBM. Quantitative real-time PCR was used to detect the expression of circMMP9. GBM cells were transfected with a circMMP9 overexpression vector or siRNA, and cell proliferation, migration and invasion, as well as tumorigenesis in nude mice, were assessed to examine the effect of circMMP9 in GBM. Biotin-coupled miRNA capture, fluorescence in situ hybridization and luciferase reporter assays were conducted to confirm the relationship between circMMP9 and miR-124. Results In this study, we screened differentially expressed circRNAs and identified circMMP9 in GBM. We found that circMMP9 acted as an oncogene, was upregulated in GBM and promoted the proliferation, migration and invasion abilities of GBM cells. Next, we verified that circMMP9 served as a sponge that directly targeted miR-124; circMMP9 accelerated GBM cell proliferation, migration and invasion by targeting miR-124. Furthermore, we found that cyclin-dependent kinase 4 (CDK4) and aurora kinase A (AURKA) were involved in circMMP9/miR-124 axis-induced GBM tumorigenesis. Finally, we found that eukaryotic initiation factor 4A3 (eIF4A3), which binds to the MMP9 mRNA transcript, induced circMMP9 cyclization and increased circMMP9 expression in GBM. Conclusions Our findings indicate that eIF4A3-induced circMMP9 is an important underlying mechanism in GBM cell proliferation, invasion and metastasis through modulation of the miR-124 signaling pathway, which could provide pivotal potential therapeutic targets for the treatment of GBM. Graphical abstrac

Effects of Anthropogenic Disturbances and Climate Change on Riverine Dissolved Inorganic Nitrogen Transport

Abstract Nitrogen (N) transport from land to rivers, estuaries, and coastal marine systems has been markedly altered by anthropogenic and climatic drivers over recent decades. In this study, a riverine N transport scheme considering anthropogenic N discharge and water regulation was incorporated into the Land Surface Model of the Chinese Academy of Sciences (CAS‐LSM). Seven groups of simulations using the developed model at the global scale for the period of 1981–2010 were conducted to investigate the effects of anthropogenic disturbances and climate change on riverine dissolved inorganic nitrogen (DIN) transport. It was shown that fertilization and point source pollution have enhanced the DIN fluxes in rivers across the world, especially in western Europe and eastern China. The DIN exports were significantly reduced due to retention by reservoirs and the withdrawal of surface water and groundwater, with a retention efficiency of 50–70%. Climate variability and trends increased or decreased the riverine DIN fluxes depending on the specific hydroclimatic conditions. We further analyzed the contributions of climatic and anthropogenic changes to the riverine DIN changes in four major rivers. The riverine DIN exports in the Mississippi River Basin were affected primarily by fertilization, while the changes in DIN exports of the Danube were dominated by point source pollution and water regulation. The Yangtze River in China was seriously affected by both fertilization and point source pollution, and water regulation played a significant role in reducing DIN exports. Climate variability was the primary factor explaining the interannual variability of DIN exports

Antibacterial and Antifungal Properties of a Novel Antimicrobial Peptide GK-19 and Its Application in Skin and Soft Tissue Infections Induced by MRSA or Candida albicans

The increasing resistance of human pathogens promotes the development of novel antimicrobial agents. Due to the physical bactericidal mechanism of membrane disruption, antimicrobial peptides are considered as potential therapeutic candidates without inducing microbial resistance. Scorpion venom-derived peptide, Androctonus amoreuxi Antimicrobial Peptide 1 (AamAP1), has been proved to have broad-spectrum antimicrobial properties. However, AamAP1 can induce hemolysis and shows strong toxicity against mammalian cells. Herein, the antimicrobial activity and mechanism of a novel synthetic antimicrobial peptide, GK-19, derived from AamAP1 and its derivatives, was evaluated. Five bacteria and three fungi were used to evaluate the antimicrobial effects of GK-19 in vitro. Scalded mice models combined with skin and soft tissue infections (SSTIs) were used to evaluate its applicability. The results indicated that GK-19 could not only inhibit Gram-positive and Gram-negative bacterial growth, but also kill fungi by disrupting the microbial cell membrane. Meanwhile, GK-19 showed negligible toxicity to mammalian cells, low hemolytic activity and high stability in plasma. Furthermore, in scalded mice models combined with SSTIs induced by either Methicillin-Resistant Staphylococcus aureus (MRSA) or Candida albicans, GK-19 showed significant antimicrobial and healing effects. Overall, it was demonstrated that GK-19 might be a promising drug candidate in the battle against drug-resistant bacterial and fungal infections