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White blood cell (WBC) morphology examination plays a crucial role in diagnosing many diseases. One of the most important steps in WBC morphology analysis is WBC image segmentation, which remains a challenging task. To address the problems of low segmentation accuracy caused by color similarity, uneven brightness, and irregular boundary between WBC regions and the background, a WBC image segmentation network based on U-Net combining residual networks and attention mechanism was proposed. Firstly, the ResNet50 residual block is used to form the main unit of the encoder structure, which helps to overcome the overfitting problem caused by a small number of training samples by improving the network's feature extraction capacity and loading the pretraining weight. Secondly, the SE module is added to the decoder structure to make the model pay more attention to useful features while suppressing useless ones. In addition, atrous convolution is utilized to recover full-resolution feature maps in the decoder structure to increase the receptive field of the convolution layer. Finally, network parameters are optimized using the Adam optimization technique in conjunction with the binary cross-entropy loss function. Experimental results on BCISC and LISC datasets show that the proposed approach has higher segmentation accuracy and robustness.

Most previous studies focused on the redox state of the deep water, leading to an incomplete understanding of the spatiotemporal evolution of the redox-stratified ocean during the Ediacaran-Cambrian transition. In order to decode the redox condition of shallow marine environments during the late Ediacaran, this study presents I/(Ca + Mg), carbon and oxygen isotope, major, trace, and rare earth element data of subtidal to peritidal dolomite from the Dengying Formation at Yangba, South China. In combination with the reported radiometric and biostratigraphic data, the Dengying Formation and coeval successions worldwide are subdivided into a positive δ

A significant challenge exists in obtaining chiral nanostructures that are amenable to both solution-phase self-assembly and solid-phase preservation, which enable the observation of unveiled optical responses impacted by the dynamic or static conformation and the incident excitations. Here, to meet this demand, we employed DNA origami technology to create quasi-planar chiral satellite-core nanoparticle superstructures with an intermediate geometry between the monolayer and the double layer. We disentangled the complex chiral mechanisms, which include planar chirality, 3D chirality, and induced chirality transfer, through combined theoretical studies and thorough experimental measurements of both solution- and solid-phase samples. Two distinct states of optical responses were demonstrated by the dynamic and static conformations, involving a split or nonsplit circular dichroism (CD) line shape. More importantly, our study on chiral nanoparticle superstructures on a substrate featuring both a dominant 2D geometry and a defined 3D represents a great leap toward the realization of colloidal chiral metasurfaces.

Interleukin-36 (IL-36) family is associated with several fibrosis-related disorders and connective tissue diseases. However, their expression in idiopathic pulmonary fibrosis (IPF) and connective tissue disease-interstitial lung disease (CTD-ILD) is unknown.We included 19 CTD-ILD patients, 16 IPF patients, and 27 healthy control subjects. Determination of serum concentrations of IL-36α, IL-36γ and IL-36 receptor antagonist (IL-36Ra) was performed by ELISA. The value of biomarkers for the diagnosis and assessment of ILD was assessed by lung function tests and high-resolution computed tomography.Serum concentrations of IL-36α and IL-36γ in patients with CTD-ILD and IPF were significantly higher than that in healthy controls, whereas serum IL-36Ra concentrations were not significantly different between the 3 groups. Increased IL-36 levels correlated with disease severity in IPF patients. ROC curve analysis showed that the AUC was 0.9931 for IL-36α and 0.8194 for IL-36γ in IPF group. In CTD-ILD group, the AUC was 0.9825 for IL-36α and 0.7973 for IL-36γ.We demonstrated an imbalance in the agonist and antagonist profiles of IL-36 cytokines in ILD. IL-36 cytokines may be a new diagnostic or therapeutic target in ILD, especially in IPF.

Breast cancer is the most common female cancer in the world. Breast cancer patients are currently treated with a combination of surgery, chemotherapy, radiotherapy, and targeted therapy, but the 5-year overall survival rate is still low. Therefore, we plan to explore the potential interaction mechanism between miR-622 and EYA1 in the breast cancer cells and their effect on proliferation, migration, and invasion of breast cancer, to lay a foundation for the gene therapy of breast cancer and improve the therapeutic effect. This study found that miR-622 was highly expressed in breast cancer cell lines, while EYA1 was poorly. In MCF-7 cell line, miR-622 had the highest expression level, while EYA1 had the lowest. Besides, the bioinformatics analysis showed that EYA1 possesses putative miR-622 binding sites within its 3 ′ UTR. The increased miR-622 significantly enhanced the proliferation, migration, and invasion of MCF-7 cell line and inhibited luciferase reporter activity in the 3 ′ UTR of EYA1-WT. When upregulating the expression of miR-622, the mRNA and protein expression levels of EYA1 were significantly decreased. We also found that the silencing of EYA1 promoted the proliferation, migration, and invasion of breast cancer MCF-7 cell line. These results indicate that miRNA-622 plays a tumor-promoting role in breast cancer through targeted negative regulation of EYA1, suggesting that miRNA-622 may become a potential target for breast cancer treatment.

PIDA mediated oxidative acyloxylation/azirination and sulfonyloxylation/azirination of β-enamino esters were investigated.

High-accuracy detection of vacant parking slots using visual system is a prerequisite for automatic parking, which is significant for the promotion of automatic parking. Complex visual environment such as light occlusion, intensity variations and visual accuracy raises significant challenges for vision-based system parking slot detection. To address such problems, REPSDet (Resnet50 based Parking Slot Detection) is proposed for parking slot detection and occupancy classification in this paper, which is based on deep learning. Parking slot proximity information could be fully extracted by REPSDet,which is combined with parking slot classification and location information to improve the parking slot detection effect. For parking slot detection, REPS-Net is proposed in this paper, which is an improved yolov4 parking slot detection method. In REPS-Net, marker point positioning combined with geometric clues are used to infer the precise location of parking slots. For occupancy classification, the deep convolutional network m\_DCNN is proposed in this paper. Network structure and operation performance are optimized by m_DCNN, and the accuracy of parking slot detection is further improved. Experimental results show that REPSDet achieves precision rate of 97.77% and recall rate of 99.38% on the PS2.0_A dataset, which is significantly better than compared methods.

Bromodomain-containing protein 4 (BRD4) is an attractive epigenetic target in human cancers. Inhibiting the phosphorylation of BRD4 by casein kinase 2 (CK2) is a potential strategy to overcome drug resistance in cancer therapy. The present study describes the synthesis of multiple BRD4–CK2 dual inhibitors based on rational drug design, structure–activity relationship, and in vitro and in vivo evaluations, and 44e was identified to possess potent and balanced activities against BRD4 (IC(50) = 180 nM) and CK2 (IC(50) = 230 nM). In vitro experiments show that 44e could inhibit the proliferation and induce apoptosis and autophagy-associated cell death of MDA-MB-231 and MDA-MB-468 cells. In two in vivo xenograft mouse models, 44e displays potent anticancer activity without obvious toxicities. Taken together, we successfully synthesized the first highly effective BRD4–CK2 dual inhibitor, which is expected to be an attractive therapeutic strategy for triple-negative breast cancer (TNBC).

We describe a case of Langerhans cell histiocytosis involving the bilateral pleura on FDG PET/CT. Multiple pleural nodules were detected by CT in a 38-year-old woman with chest pain and night sweats. Malignant tumors were suspected. PET/CT showed abnormal FDG uptake in those pleural lesions. No other abnormal foci were seen in the rest of the whole body. A primary pleural disease was considered. Then the histopathologic findings after biopsy confirmed the diagnosis of Langerhans cell histiocytosis.

The tripolarized MIMO system can provide one more degree of freedom and have a more compacted size over a dual-polarized MIMO system, which is attractive for high-capacity wireless communication systems. In this paper, we analyze and model channel properties for tripolarized MIMO systems based on experimental channel measurements in typical indoor and outdoor scenarios. Firstly, channel measurement campaigns in the laboratory and the Urban Micro (UMi) scenarios on sub-6 GHz bands are presented. Then, based on measured data, path loss, delay spread (DS), and cross-polarization discrimination (XPD) for 9 polarization combinations are analyzed and modeled in a statistical way. Statistical results of these channel properties are also given. It is observed that channel properties of both large-scale fading and small-scale fading depend strongly on the polarization direction. Furthermore, we evaluate the performance of tripolarized MIMO systems by analyzing the Demmel condition number and channel capacity gain (CG). For both the indoor and the outdoor scenarios, it is found that colocated tripolarized antenna can bring a nearly threefold CG with respect to the unipolarized one. These results can give good insights into the design and evaluation of tripolarized MIMO systems.

Low visibility in foggy weather can easily cause accidents and affect normal life. Accurate visibility estimate is critical to transportation, aviation, marine and other fields. For visibility esti...

Existing evidence has demonstrated that epigenetic modifications (including DNA methylation, histone modifications, and microRNAs), which are associated with the occurrence and development of tumors, can directly or indirectly regulate autophagy. In particular, nuclear events induced by several epigenetic regulators can regulate the autophagic process and expression levels of tumor-associated genes, thereby promoting tumor progression. Tumor-associated microRNAs, including oncogenic and tumor-suppressive microRNAs, are of great significance to autophagy during tumor progression. Targeting autophagy with emerging epigenetic drugs is expected to be a promising therapeutic strategy for human tumors. From this perspective, we aim to summarize the role of epigenetic modification in the autophagic process and the underlying molecular mechanisms of tumorigenesis. Furthermore, the regulatory efficacy of epigenetic drugs on the autophagic process in tumors is also summarized. This perspective may provide a theoretical basis for the combined treatment of epigenetic drugs/autophagy mediators in tumors.

We herein report the identification, structural optimization, and structure-activity relationship of thieno[2,3-d]pyrimidine derivatives as a novel kind of selective vascular endothelial growth factor receptor 3 (VEGFR3) inhibitors. N-(4-Chloro-3-(trifluoromethyl)phenyl)-4-(6-(4-(4-methylpiperazin-1-yl)phenyl)thieno[2,3-d]pyrimidin-4-yl)piperazine-1-carboxamide (38k) was the most potent VEGFR3 inhibitor (IC50 = 110.4 nM) among developed compounds. Compared with VEGFR1 and VEGFR2, VEGFR3 was approximately 100 times more selective. Here, compound 38k significantly inhibited proliferation and migration of VEGF-C-induced human dermal lymphatic endothelial cells (HDLEC), MDA-MB-231, and MDA-MB-436 cells by inactivating the VEGFR3 signaling pathway. Additionally, 38k induced cell apoptosis and a prolonged G1/S-phase in MDA-MB-231 and MDA-MB-436 cells. It also presented acceptable pharmacokinetic characteristics in Sprague-Dawley (SD) rats with an oral bioavailability of 30.9%. In the xenograft model in vivo, 38k effectively inhibited breast cancer growth by suppressing the VEGFR3 signaling pathway. 38k pronouncedly resisted the formation of pulmonary metastatic nodules in mice. Collectively, 38k may be a promising therapeutic agent of metastatic breast cancer.

Swine influenza virus (SIV) circulates worldwide, posing substantial economic loss and disease burden to humans and animals. Vaccination remains the most effective way to prevent SIV infection and transmission. In this study, we evaluated the protective efficacy of a recombinant, baculovirus-insect cell system-expressed bivalent nanoparticle SIV vaccine in mice challenged with drifted swine influenza H1N1 and H3N2 viruses. After a prime-boost immunization, the bivalent nanoparticle vaccine (BNV) induced high levels of hemagglutination inhibition (HAI) antibodies, virus-neutralization (VN) antibodies, and antigen-specific IgG antibodies in mice, as well as more efficient cytokine levels. The MF59 and CPG1 adjuvant could significantly promote both humoral and cellular immunity of BNV. The MF59 adjuvant showed a balanced Th1/Th2 immune response, and the CPG1 adjuvant tended to show a Th1-favored response. The BALB/c challenge test showed that BNV could significantly reduce lung viral loads and feces viral shedding, and showed fewer lung pathological lesions than those in PBS and inactivated vaccine groups. These results suggest that this novel bivalent nanoparticle swine influenza vaccine can be used as an efficacious vaccine candidate to induce robust immunity and provide broad protection against drifted subtypes in mice. Immune efficacy in pigs needs to be further evaluated.

White blood cell (WBC) detection plays a vital role in peripheral blood smear analysis. However, cell detection remains a challenging task due to multi-cell adhesion, different staining and imaging conditions. Owing to the powerful feature extraction capability of deep learning, object detection methods based on convolutional neural networks (CNNs) have been widely applied in medical image analysis. Nevertheless, the CNN training is time-consuming and inaccuracy, especially for large-scale blood smear images, where most of the images are background. To address the problem, we propose a two-stage approach that treats WBC detection as a small salient object detection task. In the first saliency detection stage, we use the Itti's visual attention model to locate the regions of interest (ROIs), based on the proposed adaptive center-surround difference (ACSD) operator. In the second WBC detection stage, the modified CenterNet model is performed on ROI sub-images to obtain a more accurate localization and classification result of each WBC. Experimental results showed that our method exceeds the performance of several existing methods on two different data sets, and achieves a state-of-the-art mAP of over 98.8%.

BackgroundSleep disturbance and neuropsychiatric symptoms are common clinical symptoms of cerebral small vessel disease (CSVD), but the underlying mechanism is unclear. Here, we investigated the relationship between sleep quality and neuropsychiatric performance in patients with CSVD.MethodsA total of 30 patients with CSVD and 35 healthy controls (HCs) were recruited. The 13-item Beck Depression Inventory (BDI-13), Beck Anxiety Inventory (BAI), and Symptom Check List 90 (SCL90) were used to assess depression, anxiety, and other psychological symptoms, respectively. Sleep quality was assessed using Pittsburgh Sleep Quality Index (PSQI), and cognitive function was tested using Montreal Cognitive Assessment (MoCA).ResultsWhen compared to the HC group, the patients with CSVD showed increased anxiety and neuropsychiatric symptoms, worse sleep quality, and impaired cognition (p < 0.05). The prevalence of comorbid poor sleep quality in the patients with CSVD was approximately 46%. The patients with CSVD with poor sleep quality also had more severe neuropsychiatric symptoms. After controlling for demographic variables, sex and anxiety significantly predicted sleep quality.ConclusionThis study suggests that the prevalence of CSVD with poor sleep quality is high, and that sex and anxiety are independent risk factors for CSVD comorbid sleep quality.

Industrial Internet of Things (IIoT) is an emerging area that fifth-generation (5G) mobile communication system penetrates industrial manufacturing applications. The indoor factory has larger space and there are a lot of metal machine tools distributed in it, which makes its radio propagation characteristics and corresponding channel models significantly different from those of the indoor office and indoor hotspot. To support the design and the evaluation of the IIoT techniques, the 3rd Generation Partnership Project (3GPP) released the first 5G IIoT standard model in October 2019. In this article, we give a detailed explanation of this IIoT model and compare it with other indoor models. First, we introduce the standardization of 3GPP IIoT channel model and its motivation. Second, four IIoT subscenarios, which are classified according to the clutter density and antenna height, are described. Third, the potential frequency bands of 5G IIoT are summarized. Fourth, the models of channel parameters, including the path loss and the line-of-sight (LOS) probability, the root mean-square (RMS) delay spread, and the angular spread, are given. Among them, the models of path loss and LOS probability take the antenna height and clutter density into consideration. The model of RMS delay spread changes from frequency-dependent to volume-dependent in order to catch the size variation of factories. Finally, two newly added key channel characteristics, dual mobility and absolute time of arrival, which help to describe the robot movement and positioning, are also presented.

Terahertz (THz) communication has been envisioned as a key enabling technology for sixth-generation (6G). In this paper, we present an extensive THz channel measurement campaign for 6G wireless communications from 220 GHz to 330 GHz. Furthermore, the path loss is analyzed and modeled by using two single-frequency path loss models and a multiple-frequencies path loss model. It is found that at most frequency points, the measured path loss is larger than that in the free space. But at around 310 GHz, the propagation attenuation is relatively weaker compared to that in the free space. Also, the frequency dependence of path loss is observed and the frequency exponent of the multiple-frequencies path loss model is 2.1. Moreover, the cellular performance of THz communication systems is investigated by using the obtained path loss model. Simulation results indicate that the current inter-site distance (ISD) for the indoor scenario is too small for THz communications. Furthermore, the tremendous capacity gain can be obtained by using THz bands compared to using microwave bands and millimeter wave bands. Generally, this work can give an insight into the design and optimization of THz communication systems for 6G.

In this brief, a millimeter-wave (mm-Wave) wideband frequency quadrupler is demonstrated in a 55-nm CMOS technology. It cascades two injection-locked frequency doublers (ILFD). Each of them consists of an oscillator gain stage realized by an injection-locked oscillator (ILO) and a frequency doubler implemented by a push-push pair. A tail feedback loop is proposed and applied in the second ILFD. It effectively boosts the injection current for the second ILFD. Therefore, both the operating bandwidth and output power (Pout) of the circuit are prominently improved. In addition, transformer-based high-order resonators are used to reduce the phase variation of their impedance around 0° and hence extend the locking range of ILOs. According to the measurement results, a frequency range of 30.8 ~ 40 GHz is achieved. The maximum Pout is up to -7.1 dBm without additional buffers. The circuit also attains a wide 3-dB frequency bandwidth of Pout, which is from 32 to 38.4 GHz. The harmonic rejection ratios of the frequency quadrupler are 16.5 ~ 25.9 dBc at the second-order harmonic and 31 ~ 45 dBc at the fundamental and third-order harmonics over the entire operating bandwidth. The core area occupies only 0.24 mm2.

This paper presents an empirical study of the uplink and downlink azimuth angle of arrival (AoA) in an urban micro (UMi) scenario at 28 GHz. At present, most UMi measurements are conducted in the downlink and then the uplink situation is inferred assuming channel reciprocity. Although the channel correlation coefficient of the uplink and downlink can be as high as 0.8, this does not mean that they are the same. Only a real uplink measurement can accurately describe its channel conditions, and this is what this study does. A receiver equipped with a rotatable horn antenna is mounted at the base station and the user terminal, respectively, in simulating the uplink and downlink. To improve the angular resolution, we extract the multipath components (MPCs) using the space-alternating generalized expectation-maximization algorithm. Also, a spatial lobe approach is used to cluster the MPCs in the power angular spectrum. By matching MPCs with objects in the environment, we find that direct propagation and first-order reflections are dominant in line-of-sight and non-line-of-sight cases. By comparing our measurement with those in standard channel models, we verify that the AoA of clusters follows a Gaussian distribution in the uplink and downlink. In addition, a two-dimensional Gaussian distribution for ray AoA and power is established to reflect their correlation.

Vehicle-to-vehicle (V2V) wireless communications have many envisioned applications for ensuring traffic safety and for addressing traffic congestion. However, developing suitable communication systems and standards for this purpose requires developers to have accurate models for the V2V propagation channel. Likewise, the dynamic evolution of multipath components (MPCs) in V2V channels has not been well modeled in existing models. In this paper, we propose a geometry-based stochastic channel model for a lightly built-up urban environment and then parametrize the model from measurements. The MPCs are extracted based on a high-resolution parameter estimation; they are tracked and clustered through a joint algorithm. The identified clusters are classified as line-of-sight, reflections from static scatterers, reflections from mobile scatterers, multiple-bounce reflections, and diffuse scattering. Specifically, the multiple-bounce reflections are modeled as twin clusters that follow the COST 273/COST2100 approach. The paper gives a full parameterization of the channel model and supplies a step-by-step implementation recipe. We verify the model by comparing two second-order statistics, i.e., the root-mean-square (RMS) delay spread and the angular spreads of arrival/departure derived from the channel model, to the results obtained directly from the measurements. Furthermore, we also identify several key factors that strongly impact the synthetic channel performance.

As the backbone of social development, college students’ level of physical exercise has always been the focus of research by experts and scholars. Most of the research methods are on the strength of literature data, questionnaire survey, mathematical statistics and comparative analysis. Based on the classification of college students and the influence and flow law of inter-class population, this paper establishes a differential equation system. By analyzing the existence and stability of the equilibrium of this system and the possible fold or backward bifurcations at the equilibrium, the quantitative analysis of college students’ physical exercise trends on campus is carried out. This paper aims to improve the participation of college students in physical exercise by maximizing the number of students in the third categories. The results of theoretical proof, sensitivity analysis and numerical simulation show that in the initial stage, promoting peer-to-peer communication is the most effective measure. Secondly, when the effect of peer-to-peer interaction reaches saturation point, the way to improve physical education can achieve significant results. To fundamentally improve the enthusiasm of college students to participate in sports activities, we should start from the level of consciousness and enhance students’ awareness of physical exercise from an early age.

Chirality, a fascinating property ubiquitous in nature, plays an important role in living organisms. DNA-programmed self-assembly has been extensively applied to precisely organize metal nanoparticles and/or small molecules in a chiral fashion at the nanometer scale. These assemblies exhibit significant chiroptical activities and are potential in biological detection and imaging, information processing, optical metamaterials, etc. In this review, we conclude on the DNA-enabled chiral plasmonic systems, uniquely from the perspective of the evolution of DNA programming methodology. We start by introducing a variety of natural and artificial DNA nanostructures to illustrate the fine programmability of DNA. Then we discuss the broad library of DNA-programmed chiral plasmonic nanostructures, spanning from individual nanoparticle–molecule chiral hybrids to the hierarchical chiral arrangements of nanoparticles enabled by DNA nanostructures of different complexities, which are from the primary DNA double helix to advanced architectures. Some cutting-edge applications of DNA-programmed chiral plasmonic nanostructures will also be introduced. We conclude this review with our personal perspectives on the future challenges and opportunities in this rapidly developing field. We expect this comprehensive review will inspire future studies in chiral materials at the convergence of DNA nanotechnology and chiral plasmonics.

Peste des petits ruminants (PPR) is an acute and highly contagious disease and has long been a significant threat to small ruminant productivity worldwide. However, the molecular mechanism underlying host-PPRV interactions remains unclear and the long noncoding RNAs (lncRNAs) regulation of PPR virus (PPRV) infection has rarely been reported so far. Here, we first demonstrated that PPRV infection can induce an obvious innate immune response in caprine endometrial epithelial cells (EECs) at 48 h post-infection (hpi) with an MOI of 3. Subsequently, we determined that PPRV infection is associated with 191 significantly differentially expressed (SDE) lncRNAs, namely, 137 upregulated and 54 downregulated lncRNAs, in caprine EECs compared with mock control cells at 48 hpi by using deep sequencing technology. Importantly, bioinformatics preliminarily analyses revealed that these DE lncRNAs were closely related to the immune response. Furthermore, we identified a system of lncRNAs related to the immune response and focused on the role of lncRNA 10636385 (IRF1-AS) in regulating the innate immune response. Interestingly, we found that IRF1-AS was a potent positive regulator of IFN-β and ISG production, which can significantly inhibit PPRV replication in host cells. In addition, our data revealed that IRF1-AS was positively correlated with its potential target gene, IRF1, which enhanced the activation of IRF3 and the expression of ISGs and interacted with IRF3. This study suggests that IRF1-AS could be a new host factor target for developing antiviral therapies against PPRV infection.

Dibutyl phthalate (DBP) is present in hydraulic fracturing flowback and produced water. Degradation of DBP in aqueous by means of ozonation in ultrasonic cavitation- rotational flow interaction coupled-field (UC-RF coupled-field) was studied. The effect of ozone dosage, ozone intake flow, operating temperature, initial pH, DBP initial concentration, liquid flow rate, and ultrasonic power on the DBP removal was investigated. The results indicated that the DBP degradation rate was strongly influenced by the liquid flow rate and the ultrasonic power over the range investigated. HCO 3 - and Cl - revealed an inhibitory effect on the DBP removal. SO 4 2- seems to have no effect on DBP removal. The ozone utilization efficiency in UC-RF coupled-field was 2.77 and 1.13 times higher than those of the conventional microporous aeration (CMA) and rotating-flow microbubble aeration (RFMA), respectively. The DBP degradation rate was diminished in the presence of tert-butyl alcohol (TBA) . Cavitation bubbles are consider as innumerable micro reactor s. Degradation of DBP by direct ozonation, hydroxyl radical ( · OH) oxidation, high pressure and high temperature pyrolysis . Finally, a possible degradation pathway of DBP is obtained on basis of the main reaction intermediates.

The effective potency and resistance of poly(ADP-ribose) polymerase (PARP) inhibitors limit their application. Here, we exploit a new paradigm that mimics the effects of breast cancer susceptibility genes (BRCA) mutations to trigger the possibility of synthetic lethality, based on the previous discovery of a potential synthetic lethality effect between bromodomain-containing protein 4 (BRD4) and PARP1. Consequently, the present study describes compound

Background Interstitial lung disease (ILD) is a common pulmonary complication of connective tissue disease (CTD). This study aims to evaluate the clinical diagnostic value of matrix metalloproteinase-9 (MMP-9), surfactant protein-D (SP-D), and vascular endothelial growth factor (VEGF) as potential biomarkers for CTD-ILD. Methods This research included 33 CTD-ILD patients, 31 CTD patients without ILD, and 24 healthy control subjects. Then, the value of biomarkers for the diagnosis and evaluation of CTD-ILD was assessed through high-resolution computed tomography (HRCT) findings and pulmonary function test (PFT) parameters. Results The serum MMP-9, SP-D, and VEGF levels in the CTD-ILD group were higher than those in the CTD-NILD group and healthy group. The ROC curve indicates that VEGF has good to excellent diagnostic performance in diagnosing CTD-ILD, the cut-off that best optimizes sensitivity and specificity in diagnosing CTD-ILD is 277.60 pg/ml (sensitivity, 87.9%; specificity, 83.6%), with an area under the curve (AUC) of 0.905 (95% confidence interval (CI) 0.842–0.968); The ROC curve for MMP-9 suggests this biomarker is fair for diagnosis of CTD-ILD(sensitivity, 81.8%; specificity, 81.8%), with an AUC of 0.867 (95% CI 0.784–0.950), but SP-D only provided lower specificity with higher sensitivity in diagnosing CTD-ILD(sensitivity, 90.9%; specificity, 40.0%). The different serum biomarkers are more specific and sensitive when combined to diagnose ILD. The semiquantitative score for the degree of ILD severity on HRCT was positively correlated with SP-D and VEGF levels (r = 0.461, P = 0.007; r = 0.362, P = 0.039), and serum MMP-9 levels were elevated in the UIP subgroup compared to the non-UIP subgroup. The percentage of diffusing capacity of the lung for carbon monoxide (DLco) (% predicted) had a negative correlation with the SP-D level (r = − 0.407, P = 0.044) and a statistically negative correlation between MMP-9 and the forced vital capacity (FVC) (r = − 0.451, P = 0.024). Conclusions Serum MMP-9, SP-D, and VEGF levels may have clinical value in screening and evaluating the severity of CTD-ILD.

Excessive cell proliferation due to cell cycle disorders is one of the hallmarks of breast cancer. Cyclin-dependent kinases (CDKs), which are involved in the transition of the cell cycle from G1 phase to S phase by combining CDKs with cyclin, are considered promising targets with broad therapeutic potential based on their critical role in cell cycle regulation. Pharmacological evidence has shown that abnormal cell cycle due to the overexpression of CDK6 is responsible for the hyperproliferation of cancer cells. Blocking CDK6 expression inhibits tumour survival and growth. Therefore, CDK6 can be regarded as a potential target for anticancer therapeutics. Thus, small molecules that can be considered CDK inhibitors have been developed into promising anticancer drugs. In this study, combined structure-based and ligand-based in silicon models were created to identify new chemical entities against CDK6 with the appropriate pharmacokinetic properties. The database used to screen drug-like compounds in this thesis was based on the best E-pharmacophore hypothesis and the best ligand-based drug hypothesis. As a result, 147 common compounds were identified by further molecular docking. Surprisingly, the in vitro evaluation results of 20 of those compounds showed that the two had good CDK6 inhibitory effects. The best compound was subjected to kinase panel screening, followed by molecular dynamic simulations. The 50-ns MD studies revealed the pivotal role of VAL101 in the binding of inhibitors to CDK6. Overall, the identification of two new chemical entities with CDK6 inhibitory activity demonstrated the feasibility and potential of the new method.

Discriminating between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, or LOS identification , is important for a variety of purposes in wireless systems, including localization and channel modeling. LOS identification is especially challenging in vehicle-to-vehicle (V2V) networks since a variety of physical effects that occur at different spatial/temporal scales can affect the presence of LOS. This paper investigates machine learning techniques for LOS identification in V2V networks using an extensive set of measurement data and then develops robust and efficient identification solutions. Our approach exploits several static and time-varying features of the channel impulse response (CIR), which are shown to be effective. Specifically, we develop a fast identification solution that can be trained by using the power angular spectrum. Moreover, based on the measurement data, we also compare three different machine learning methods, i.e., support vector machine, random forest, and artificial neural network, in terms of their ability to train and generate the classifier. The results of our experiments conducted under various V2V environments, which were then validated using $K$ -fold cross-validation, show that our techniques can distinguish the LOS/NLOS conditions with an error rate as low as 1%. In addition, we investigate the impact of different training and validating strategies on the identification accuracy.

Understanding the physicochemical characteristics of oil-based cuttings (OBCs) is an important foundation for subsequent treatment and management. The macro- and microscopic properties of white oil-based cuttings (WOBCs) and diesel-based cuttings (DBCs) after the different pretreatment steps have been assessed using scanning electron microscopy. The organic and inorganic compositions of OBCs have been analyzed using X-ray diffraction, Fourier-transform infrared spectrometry, and gas chromatography-mass spectrometry. Inorganic matter (SiO2, BaSO4, and CaCO3), alkanes, aromatic compounds, and water were the main components of OBCs. The organic content (26.14%) and alkane content of the WOBCs were higher than that of the DBCs, whereas for the inorganic content (70.87%), the reverse was true. The macro- and micromorphologies of OBCs were quite different because their oil and water contents were different. The oil contents of OBCs decreased in the order A1 (14.64%) > A3 (12.67%) > A2 (11.06%) and B1 (9.19%) > B3 (8.94%) > B2 (4.66%); the water contents decreased in the order A1 (2.99%) > A3 (2.19%) > A2 (1.09%) and B1 (2.30%) > B3 (1.87%) > B2 (1.09%). Moreover, a skid-mounted treatment technology for OBCs was proposed. The results can be a scientific guidance for the treatment and management of OBCs.