Cardiovascular disease is the leading cause of death worldwide, accounting for 48.0% of all deaths in Europe and 34.3% in the United States. Studies have shown that arterial stiffness takes precedence over vascular structural changes and is therefore considered to be an independent predictor of many cardiovascular diseases. At the same time, the characteristics of Korotkoff signal is related to vascular compliance. The purpose of this study is to explore the feasibility of detecting vascular stiffness based on the characteristics of Korotkoff signal. First, the Korotkoff signals of normal and stiff vessels were collected and preprocessed. Then the scattering features of Korotkoff signal were extracted by wavelet scattering network. Next, the long short-term memory (LSTM) network was established as a classification model to classify the normal and stiff vessels according to the scattering features. Finally, the performance of the classification model was evaluated by some parameters, such as accuracy, sensitivity, and specificity. In this study, 97 cases of Korotkoff signal were collected, including 47 cases from normal vessels and 50 cases from stiff vessels, which were divided into training set and test set according to the ratio of 8 : 2. The accuracy, sensitivity and specificity of the final classification model was 86.4%, 92.3% and 77.8%, respectively. At present, non-invasive screening method for vascular stiffness is very limited. The results of this study show that the characteristics of Korotkoff signal are affected by vascular compliance, and it is feasible to use the characteristics of Korotkoff signal to detect vascular stiffness. This study might be providing a new idea for non-invasive detection of vascular stiffness.
Humans ; Vascular Stiffness ; Neural Networks, Computer ; Cardiovascular Diseases/diagnosis* ; Sensitivity and Specificity

Carotid is in a high risk of atherosclerosis due to its special geometric features and complex flow characteristics. Various biomechanical parameters are practical tools for carotid risk assessment. It has beenwidely accepted that oscillatory low shear environment promotes plaque formation. Based on this, more and more biomechanical indexes have been proposed, such as time-average wall shear stress, oscillatory shear index, relative residence time and so on. In this paper, multiple biomechanical parameters were introduced from the perspectives of shear stress and its temporal and spatial variation, turbulence, platelet transport and activation, stress concentration in vascular wall, etc. The development trend of biomechanical parameters related to carotid artery risk assessment was also analyzed, so as to provide the theoretical basis for more comprehensive and rapid carotid risk assessment

Endocrine-resistance remains a major challenge in estrogen receptor α positive (ERα⁺) breast cancer (BC) treatment and constitutively active somatic mutations in ERα are a common mechanism. There is an urgent need to develop novel drugs with new mode of mechanism to fight endocrine-resistance. Given aberrant ERα activity, we herein report the identification of novel covalent selective estrogen receptor degraders (cSERDs) possessing the advantages of both covalent and degradation strategies. A highly potent cSERD 29c was identified with superior anti-proliferative activity than fulvestrant against a panel of ERα⁺ breast cancer cell lines including mutant ERα. Crystal structure of ERα‒ 29c complex alongside intact mass spectrometry revealed that 29c disrupted ERα protein homeostasis through covalent targeting C530 and strong hydrophobic interaction collied on H11, thus enforcing a unique antagonist conformation and driving the ERα degradation. These significant effects of the cSERD on ERα homeostasis, unlike typical ERα degraders that occur directly via long side chains perturbing the morphology of H12, demonstrating a distinct mechanism of action (MoA). In vivo, 29c showed potent antitumor activity in MCF-7 tumor xenograft models and low toxicity. This proof-of-principle study verifies that novel cSERDs offering new opportunities for the development of innovative therapies for endocrine-resistant BC.

Objective:To explore a fast and accurate method to diagnose children's pneumonia according to respiratory signals, so as to avoid the cancer induction caused by traditional X-ray examination.Methods:A Mach Zehnder optical fiber sensor was used to build a respiratory signals(RSPs) detection system, and the RSPs of the monitored children were extracted according to the vibration signal generated by the children's lung rales. Preprocessing methods such as the discrete cosine transform(DCT) were used to compress and denoise the RSPs. Multi-feature extraction of RSPs was conducted through signal processing methods such as the Hilbert transform and autoregressive (AR) model spectrum estimation. A support vector machine (SVM) classification model was constructed to classify the collected RSPs.Results:The accuracy rate of the proposed RSP classification of children with or without pneumonia was 94.41%, which was higher than the previous methods.Conclusions:The children's pneumonia diagnosis system based on an optical fiber sensor has a higher detection accuracy, and is expected to be widely used in clinical practice.

Neovascularization plays an important role in many physiological and pathological processes, but its mechanism is still unclear. Since vascular cells are subjected to a variety of biochemical and biomechanical stimulations in vivo and live in a complex microenvironment, it is necessary to construct the vascular model in vitro and simulate the in vivo microenvironment to explore the mechanism of neovascularization. Recently, owing to the advance of micromachining and microfluidic technology, various in vitro microvascular models have emerged. Variables such as shear stress, interstitial flow and biochemical gradient of angiogenic factors have been controlled in these models, which greatly promotes the research of neovascularization. The construction, development and biomechanical design of various microvascular models are reviewed in this paper.

Deep learning (DL) has achieved state-of-the-art performance in many digital pathology analysis tasks. Traditional methods usually require hand-crafted domain-specific features, and DL methods can learn representations without manually designed features. In terms of feature extraction, DL approaches are less labor intensive compared with conventional machine learning methods. In this paper, we comprehensively summarize recent DL-based image analysis studies in histopathology, including different tasks (e.g., classification, semantic segmentation, detection, and instance segmentation) and various applications (e.g., stain normalization, cell/gland/region structure analysis). DL methods can provide consistent and accurate outcomes. DL is a promising tool to assist pathologists in clinical diagnosis.

Microfluidic technology refers to the technique of precise fluid control by manipulating submillimeter-scale fluids. In recent years, the use of microfluidic technology has realized the construction of organ-on-chips. The organ-on-chip refers to a micro-model with physiological functions, and cultivating living cells in a continuously perfused micro-chamber to simulate the physiological functions of tissues and organs. As the physiological function of the organ-on-chip has many advantages such as definite function, controllable microenvironment, rich measurement information, low chemical consumption, low cost, promising automation and high throughput, it has a huge application prospect in the field of drug development to solve the bottleneck problems in cellular and animal experiments, which has caused a great concern in the academic community. Although the organ-on-chip is still a very young research field, some microfluidic organ-on-chips have been developed and their potential applications are explored, including drug target optimization, drug screening and toxicity tests, and biomarker identification. In this review, the progress made in microfluidic organ microchips and their potential significance in clinical research were analyzed.

Objective:To evaluate the protective immunity by vaccination of BALB/c mice with rLV-HA-GCN4,a recombinant lentivirus expressing the trimeric HA of swine H1N1 influenza virus. Methods:The female mice were randomly divided into rLV-HA-GCN4,rLV-HA,LV and PBS groups. Mice were primed with plasmid and boosted with lentivirus by the administration of intramuscular thigh injections at an interval of two weeks. At day 28 post-prime immunization,mice were inoculated intranasally with 100TCID50 of swine H1N1 influenza virus in a 50 μl volume. The immune levels were assessed by the T lymphocyte transformation test, flow cytometry,indirect ELISA and the indexes of spleen and lung. Results:The spleen lymphocyte transformation rate was 0. 3±0. 11 in the rLV-HA-GCN4 group at day 14 post-boost immunization, showing a statistical significance ( P<0. 01 ) compared to the PBS group. Meanwhile,rLV-HA-GCN4 could cause T lymphocyte response mainly based on the Th1-type CD4+ T cells. The IgG antibody titer reached to 1:8 000 at day 14 post-boost immunization and approximately 1:7 000 at day 14 post challenge. After challenge,the spleen and lung indexes of rLV-HA-GCN4 group were significantly lower than those of PBS group (P<0. 05). The body weight of rLV-HA-GCN4 group demonstrated a slight decrease before 3 days post challenge and then a gradual increase compared to the LV and PBS groups (P<0. 05). Conclusion:rLV-HA-GCN4 can effectively induce cellular and humoral immune response in BALB/c mice against swine H1N1 influenza virus.

Currently,the toxicity study of traditional Chinese medicine is faced with the following problems. Firstly,the evaluation in vitro cannot fully reflect the true state of the body. Secondly,the traditional method is not sensitive enough to the early toxicity. Lastly,the toxicity evaluation indexes cannot determine whether the compatibility of traditional Chinese medicine produces toxicity or increases toxicity systematically. The paper proposed a synthesized early evaluation research method for target organ toxicity induced by traditional Chinese medicine:screening,validation,optimization and application. This method mainly inoolves early target organ toxicity biomarkers in screening,optimi?zation,validation,biological significance explanation,and application to the traditional Chinese medicine incompatibility based on the metabolic dynamic fingerprint spectrum in order to obtain biomarkers of target organ toxicity that are sensitive and precede conventional biochemical indices for early evaluation . We attempted to analyze the pattern of chang of the biomarkers for animals acted by″18 incompatible medicaments″compatibility combination. We found that Radix Aconiti Lateralis Preparata with cardiotoxicity were compatible with Rhizoma Pinelliae,and that Trichosanthes kirilowii Maxim,Fritillaria,Ampelopsis Radix and Bletilla striata without non-cardiotoxicity produced and increased cardiotoxicity systematically.

OBJECTIVETo investigate the effect of knocking-down microRNA-221 (miR-221) expression on the radiosensitivity of human colorectal carcinoma cells.

METHODSHuman colorectal carcinoma-derived cell line Caco2 was transfected with miR-221 antisense oligonucleotides (anti-miR-221) via Lipofectamine 2000. Real-time quantitative PCR was performed to detect the expression of miR-221 and PTEN mRNA in Caco2 cells. The changes in the protein expression of PTEN in the transfected cells were detected by Western blotting. The cell death after transfection and irradiation was detected by flow cytometry.

RESULTSTransfection with anti-miR-221 caused a significant reduction in miR-221 expression (P<0.05) and up-regulated PTEN protein expression (P<0.05) in Caco2 cells. The percentage of cell death was significantly increased in anti-miR-221 group and anti-miR-221 with irradiation group (P<0.01). Anti-miR-221 significantly enhanced the radiosensitivity of Caco2 cells, which was partially reversed by PTEN-siRNA.

CONCLUSIONAnti-miR-221 can enhance the radiosensitivity of colorectal carcinoma cells by up-regulating the expression of PTEN.

Caco-2 Cells ; radiation effects ; Colorectal Neoplasms ; genetics ; metabolism ; Humans ; MicroRNAs ; genetics ; metabolism ; PTEN Phosphohydrolase ; metabolism ; RNA, Messenger ; genetics ; Radiation Tolerance ; Transfection ; Up-Regulation