Associations of the circulating levels of cytokines with the risk of myeloproliferative neoplasms: a bidirectional mendelian-randomization study.

OBJECTIVE: In the pathogenesis of myeloproliferative neoplasms (MPN), inflammation plays an important role. However, it is unclear whether there is a causal link between inflammation and MPNs. We used a bidirectional, two-sample Mendelian randomization (MR) approach to investigate the causal relationship between systemic inflammatory cytokines and myeloproliferative neoplasms. METHODS: A genome-wide association study (GWAS) of 8293 European participants identified genetic instrumental variables for circulating cytokines and growth factors. Summary statistics of MPN were obtained from a GWAS including 1086 cases and 407,155 controls of European ancestry. The inverse-variance-weighted method was mainly used to compute odds ratios (OR) and 95% confidence intervals (Cl). RESULTS: Our results showed that higher Interleukin-2 receptor, alpha subunit (IL-2rα) levels, and higher Interferon gamma-induced protein 10 (IP-10) levels were associated with an increased risk of MPN (OR = 1.36,95%CI = 1.03-1.81, P = 0.032; OR = 1.55,95%CI = 1.09-2.22, P = 0.015; respectively).In addition, Genetically predicted MPN promotes expression of the inflammatory cytokines interleukin-10 (IL-10) (BETA = 0.033, 95% CI = 0.003 ~ 0.064, P = 0.032) and monokine induced by interferon-gamma (MIG) (BETA = 0.052, 95% CI = 0.002-0.102, P = 0.043) and, on activation, normal T cells express and secrete RANTES (BETA = 0.055, 95% CI = 0.0090.1, P = 0.018). CONCLUSION: Our findings suggest that cytokines are essential to the pathophysiology of MPN. More research is required if these biomarkers can be used to prevent and treat MPN.

A spider mating plug functions to protect sperm.

Mating plugs in animals are ubiquitous and are commonly interpreted to be products of mating strategies. In spiders, however, mating plugs may also take on functions beyond female remating prevention. Due to the vagaries of female genital (spermathecal) anatomy, most spiders face the problem of having to secure additional, non-anatomical, protection for transferred sperm. Here, we test the hypothesis that mating plugs, rather than (or in addition to) being adaptations for mating strategies, may serve as sperm protection mechanism. Based on a comparative study on 411 epigyna sampled from 36 families, 187 genera, 330 species of entelegyne spiders, our results confirm the necessity of a sperm protection mechanism. We divided the entelegyne spermathecae into four types: SEG, SED, SCG and SCD. We also studied detailed morphology of epigynal tracts in the spider Diphya wulingensis having the SEG type spermathecae, using 3D-reconstruction based on semi thin histological series section. In this species, we hypothesize that two distinct types of mating plug, the sperm plug and the secretion plug, serve different functions. Morphological details support this: sperm plugs are formed on a modified spermathecal wall by the spilled sperm, and function as a temporary protection mechanism to prevent sperm from leaking and desiccating, while secretion plugs function in postcopulation both as a permanent protection mechanism, and to prevent additional mating. Furthermore, with the modified spermathecal wall of S2 stalk, the problem of shunt of sperm input and output, and the possibility of female multiple mating have been resolved. Variation in spermathecal morphology also suggests that the problem of sperm protection might be resolved in different ways in spiders. Considering mating plugs of varying shapes and origins in the vast morphospace of spiders, we conclude that mating plugs might serve different purposes that relate both to mating strategies, as well as to sperm protection.

Grating-based x-ray dark-field CT for lung cancer diagnosis in mice.

BACKGROUND: The low absorption of x-rays in lung tissue and the poor resolution of conventional computed tomography (CT) limits its use to detect lung disease. However, x-ray dark-field imaging can sense the scattered x-rays deflected by the structures being imaged. This technique can facilitate the detection of small alveolar lesions that would be difficult to detect with conventional CT. Therefore, it may provide an alternative imaging modality to diagnose lung disease at an early stage. METHODS: Eight mice were inoculated with lung cancers simultaneously. Each time two mice were scanned using a grating-based dark-field CT on days 4, 8, 12, and 16 after the introduction of the cancer cells. The detectability index was calculated between nodules and healthy parenchyma for both attenuation and dark-field modalities. High-resolution micro-CT and pathological examinations were used to crosscheck and validate our results. Paired t-test was used for comparing the ability of dark-field and attenuation modalities in pulmonary nodule detection. RESULTS: The nodules were shown as a signal decrease in the dark-field modality and a signal increase in the attenuation modality. The number of nodules increased from day 8 to day 16, indicating disease progression. The detectability indices of dark-field modality were higher than those of attenuation modality (p = 0.025). CONCLUSIONS: Compared with the standard attenuation CT, the dark-field CT improved the detection of lung nodules. RELEVANCE STATEMENT: Dark-field CT has a higher detectability index than conventional attenuation CT in lung nodule detection. This technique could improve the early diagnosis of lung cancer. KEY POINTS: • Lung cancer progression was observed using x-ray dark-field CT. • Dark-field modality complements with attenuation modality in lung nodule detection. • Dark-field modality showed a detectability index higher than that attenuation in nodule detection.

A model-based direct inversion network (MDIN) for dual spectral computed tomography.

Objective. Dual spectral computed tomography (DSCT) is a very challenging problem in the field of imaging. Due to the nonlinearity of its mathematical model, the images reconstructed by the conventional CT usually suffer from the beam hardening artifacts. Additionally, several existing DSCT methods rely heavily on the information of the spectra, which is often not readily available in applications. To address this problem, in this study, we aim to develop a novel approach to improve the DSCT reconstruction performance.Approach. A model-based direct inversion network (MDIN) is proposed for DSCT, which can directly predict the basis material images from the collected polychromatic projections. The all operations are performed in the network, requiring neither the conventional algorithms nor the information of the spectra. It can be viewed as an approximation to the inverse procedure of DSCT imaging model. The MDIN is composed of projection pre-decomposition module (PD-module), domain transformation layer (DT-layer), and image post-decomposition module (ID-module). The PD-module first performs the pre-decomposition on the polychromatic projections that consists of a series of stacked one-dimensional convolution layers. The DT-layer is designed to obtain the preliminary decomposed results, which has the characteristics of sparsely connected and learnable parameters. And the ID-module uses a deep neural network to further decompose the reconstructed results of the DT-layer so as to achieve higher-quality basis material images.Main results. Numerical experiments demonstrate that the proposed MDIN has significant advantages in substance decomposition, artifact reduction and noise suppression compared to other methods in the DSCT reconstruction.Significance. The proposed method has a flexible applicability, which can be extended to other CT problems, such as multi-spectral CT and low dose CT.

Unsupervised learning-based dual-domain method for low-dose CT denoising.

Objective. Low-dose CT (LDCT) is an important research topic in the field of CT imaging because of its ability to reduce radiation damage in clinical diagnosis. In recent years, deep learning techniques have been widely applied in LDCT imaging and a large number of denoising methods have been proposed. However, One major challenge of supervised deep learning-based methods is the exactly geometric pairing of datasets with different doses. Therefore, the aim of this study is to develop an unsupervised learning-based LDCT imaging method to address the aforementioned challenges.Approach. In this paper, we propose an unsupervised learning-based dual-domain method for LDCT denoising, which consists of two stages: the first stage is projection domain denoising, in which the unsupervised learning method Noise2Self is applied to denoise the projection data with statistically independent and zero-mean noise. The second stage is an iterative enhancement approach, which combines the prior information obtained from the generative model with an iterative reconstruction algorithm to enhance the details of the reconstructed image.Main results. Experimental results show that our proposed method outperforms the comparison method in terms of denoising effect. Particularly, in terms of SSIM, the denoised results obtained using our method achieve the highest SSIM.Significance. In conclusion, our unsupervised learning-based method can be a promising alternative to the traditional supervised methods for LDCT imaging, especially when the availability of the labeled datasets is limited.

Effects of bacterial inoculation on lignocellulose degradation and microbial properties during cow dung composting.

Inoculation with exogenous microbial agents is a common method to promote organic waste degradation and improve the quality of compost. However, the biotic effects of different microbial agents are often quite different. To evaluate the potential effects of a complex bacterial agent comprised of three strains (belonging to Bacillus and Geobacillus) on lignocellulose degradation and the underlying microbial mechanisms during cow dung composting, two lab-scale composting experiments, a control and a bacterial inoculation treatment, were established. The results suggest that bacterial inoculation accelerated the rate of temperature increase and extended the thermophilic phase. Compared to those in the negative control group, cellulose, hemicellulose, and lignin degradation rates in the inoculated group increased from 53.3% to 70.0%, 50.2% to 61.3%, and 46.4% to 60.0%, respectively. The microbial community structure and diversity in the compost were clearly changed by the bacterial inoculation. Moreover, stamp analysis showed that inoculation modulated the key compost microbial functional populations linked to the degradation of lignocellulose. Correlation matrix analysis indicated that the expression of bacterial lignocellulolytic enzymes is closely related to key microbial functional populations. Overall, the results confirm the importance of bacterial inoculation, and have important implications for promoting the efficiency and quality of cow dung compost.

The effects of three Bacillus and Geobacillus strains on compost were established.Adding the complex bacterial agent increased the thermophilic phase.Inoculation promoted the abundance of key lignocellulose-degrading microbes.These findings will help promote the efficiency and quality of cow dung compost.

Multi-scale dilated dense reconstruction network for limited-angle computed tomography.

Objective.Due to the incomplete projection data, the image reconstructed by limited-angle computed tomography (CT) usually suffers from significant artifacts, by which the structural details are heavily blurred. In this study, we aim to develop a novel approach to improve the limited-angle CT reconstruction performance, especially for the narrow scanning angular range.Approach.A deep learning based iterative framework for limited-angle tomography is proposed, which is named multi-scale dilated dense reconstruction network (MSDDRNet). The MSDDRNet utilizes a multi-scale dilated dense convolution neural network (MSDD-CNN) with conventional reconstruction algorithm for predicting image from incomplete projection data. The MSDD-CNN enhances the image features in the network by merging the DenseNet-Like structure, which serves to restore invisible singularities and reduce artifacts, as well as introducing constraints on the projection domain data into the iterative process to achieve better image detail recovery. Additionally, to improve the training speed of the network, we use a strategy of pre-training and model migration.Main results.Numerical experiments demonstrate that the proposed MSDDRNet performs well in terms of artifact correction, noise reduction and structure recovery compared to existing methods with limited scan angles, and we also extend the proposed method to more general scanning condition and other application such as dental CT data.Significance.The proposed method is a general framework, which can be applied to other CT problems, such as low dose CT, sparse-data CT and spectral CT.

Mechanical stimulation on a microfluidic device to highly enhance small extracellular vesicle secretion of mesenchymal stem cells.

Small extracellular vesicles (sEVs) are recognized as promising detection biomarkers and attractive delivery vehicles, showing great potential in diagnosis and treatment of diseases. However, the applications of sEVs are usually restricted by their poor secretion amount from donor cells under routine cell culture conditions, which is especially true for mesenchymal stem cells (MSCs) due to their limited expansion and early senescence. Here, a microfluidic device is proposed for boosting sEV secretion from MSCs derived from human fetal bone marrow (BM-MSCs). As the cells rapidly pass through a microfluidic channel with a series of narrow squeezing ridges, mechanical stimulation permeabilizes the cell membrane, thus promoting them to secrete more sEVs into extracellular space. In this study, the microfluidic device demonstrates that mechanical-squeezing effect could increase the secretion amount of sEVs from the BM-MSCs by approximately 4-fold, while maintaining cellular growth state of the stem cells. Further, the secreted sEVs are efficiently taken up by immortalized human corneal epithelial cells and accelerate corneal epithelial wound healing in vitro, indicating that this technique wound not affect the functionality of sEVs and demonstrating the application potentials of this technique.

Nitratireductor luteus sp. nov. isolated from saline-alkali land.

The Gram-staining negative, oxidase and catalase negative strain KC-ST17T, isolated from saline-alkali land, was characterized using a polyphasic approach to determine its taxonomic position. Using 16S rRNA gene sequence analysis, the highest similarity of strain KC-ST17T was found with Nitratireductor pacificus CCTCC AB 209302T (97.2%). Cells are aerobic, non-motile, and rod-shaped. The isolate was found to be able to grow in NaCl concentrations of 0-4.0%. The assembled genome of strain KC-ST17T had a total length of 4.9 Mb with a G + C content of 62.7%. According to genome analysis, strain KC-ST17T encodes genes involved in the reduction of nitrate to nitrite, which may play a role in the utilization of nitrogenous compounds from the soil as an immediate source of energy. Based on the phenotypic characteristics and phylogenetic analysis, strain KC-ST17T was confirmed to represent a novel species in the Nitratireductor genus; thus, the name Nitratireductor luteus sp. nov. was proposed. The type strain of this species was KC-ST17T (= KCTC 92119T = MCCC 1K07309T).

One-Step Method for Material Quantitation Using In-Line Tomography With Single Scanning.

OBJECTIVE: Quantitative technique based on In-line phase-contrast computed tomography with single scanning attracts more attention in application due to the flexibility of the implementation. However, the quantitative results usually suffer from artifacts and noise since the phase retrieval and reconstruction are independent ("two-step") without feedback from the original data. The work aims to investigate a method for material quantitation to improve the image quality of In-line tomography within single scanning. METHOD: An iterative method based Fresnel diffraction imaging model is developed in this work, which directly reconstructs the refractive index decrement δ and imaginary ß of the object from observed data ("one-step"). Moreover, high-quality material decomposition results are obtained by using a linear approximation in the iterative process. RESULTS: Compared with the existing methods, Our method shows a higher peak signal-to-noise ratio and structural similarity in numerical experimental results. Additionally, the quantitation accuracy of the proposed method is greater than 97.2 % by calculating the equivalent atomic number of the decomposed basic material in the real experiment. CONCLUSION: We demonstrate that this one-step method greatly reduces noise and improves quantitative reconstruction and decomposition results. SIGNIFICANCE: This algorithm has the potential for quantitative imaging research using In-line tomography in future biomedical applications.

Serum metabolomics reveals the effects of accompanying treatment on fatigue in patients with multiple myeloma.

PURPOSE: The renewal and iteration of chemotherapy drugs have resulted in more frequent long-term remissions for patients with multiple myeloma (MM). MM has transformed into a chronic illness for many patients, but the cancer-related fatigue (CRF) of many MM convalescent patients experience is frequently overlooked. We investigated whether the accompanying treatment of family members would affect MM patients' CRF and explore their serum metabolomics, so as to provide clinicians with new ideas for identifying and treating CRF of MM patients. METHODS: This was a single-center study, and a total of 30 MM patients were included in the study. Patients were divided into two groups based on whether they have close family members accompanying them through the whole hospitalization treatment. These patients received regular chemotherapy by hematology specialists, and long-term follow-up was done by general practitioners. Patients' CRF assessment for several factors used the Chinese version of the Brief Fatigue Inventory (BFI-C). Face-to-face questionnaires were administered at a time jointly determined by the patient and the investigator. All questionnaires were conducted by a general practitioner. The LC-MS-based metabolomics analysis determined whether the patients' serum metabolites were related to their fatigue severity. A correlation analysis investigated the relationship between serum metabolites and clinical laboratory indicators. RESULTS: The fatigue severity of MM patients whose family members participated in the treatment process (group A) was significantly lower than patients whose family members did not participate in the treatment process (group B). There was a statistically significant difference (fatigue severity composite score: t = - 2.729, p = 0.011; fatigue interference composite score: t = - 3.595, p = 0.001). There were no differences between the two groups of patients' gender, age, regarding clinical staging, tumor burden, blood routine, biochemical, or coagulation indexes. There were 11 metabolites, including guanidine acetic acid (GAA), 1-(Methylthio)-1-hexanethiol, isoeucyl-asparagine, L-agaritine, tryptophyl-tyrosine, and betaine, which significantly distinguished the two groups of MM patients. GAA had the strongest correlation with patient fatigue, and the difference was statistically significant (fatigue severity composite score: r = 0.505, p = 0.0044; fatigue interference composite score: r = 0.576, p = 0.0009). The results showed that GAA negatively correlated with albumin (r = - 0.4151, p = 0.0226) and GGT (r = - 0.3766, p = 0.0402). Meanwhile, GAA positively correlated with PT (r = 0.385, p = 0.0473), and the difference was statistically significant. CONCLUSION: The study is the first to report that family presence throughout the whole hospitalization may alleviate CRF in MM patients. Moreover, the study evaluated serum metabolites linked to CRF in MM patients and found that CRF has a significant positive correlation with GAA. GAA may be a more sensitive biomarker than liver enzymes, PT, and serum albumin in predicting patient fatigue. While our sample may not represent all MM patients, it proposes a new entry point to help clinicians better identify and treat CRF in MM patients.

Clinical significance of N-terminal natriuretic peptide combined with inflammatory factors, oxidative stress factors and blood lipid detection in elderly patients with Type-2 diabetes complicated with coronary heart disease.

Objectives: To observe the clinical significance of N-terminal natriuretic peptide combined with inflammatory factors, oxidative stress factors and blood lipid detection in elderly patients with Type-2 diabetes complicated with CHD (CHD), and provide a theoretical basis for the diagnosis and treatment of elderly patients with Type-2 diabetes complicated with CHD. Methods: A total of 40 patients with Type-2 diabetes complicated with CHD admitted to Affiliated Hospital of Hebei University from July 2019 and July 2020 were selected as the experimental group, and 40 patients with CHD who were hospitalized in our hospital during the same period without diabetes were selected as the control group. Venous blood was taken from all patients on morning and fasting basis, and their serum inflammatory factors as well as antioxidant molecules were examined respectively. Serum inflammatory factors include serum tumor necrosis factor α (TNF-A), interleukin-6 (IL-6), and C-reactive protein. Antioxidant molecules include antioxidant molecules superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), total antioxidant capacity (TAC), catalase (CAT), glutathione reductase (GR), N-terminal natriuretic peptide (NT-proBNP), white blood cells (WBC), hemoglobin (HBG), albumin (ALB) and blood lipid levels. The differences of the above indexes between experimental group and control group were compared and analyzed. Results: The serum levels of TNF-a, CRP, and IL-6 in the experimental group were apparently higher than those in the control group, with a statistically significant difference (P=0.00); The levels of SOD, TAC and CAT in the experimental group were significantly lower than those in the control group, with a statistically significant difference (P=0.00); The level of NT-proBNP and WBC count in the experimental group were significantly higher than those in the control group, with a statistically significant difference (NT-proBNP, P=0.01; WBC, P=0.00). However, no statistically significant difference was observed in the levels of HBG and ALB between the two groups (P>0.05). The experimental group had significantly higher TC and TG levels than the control group, with statistically significant differences (TC, P=0.01; TG, P=0.02), but had a significantly lower HDL level than the control group, with a statistically significant difference (P=0.00). Conclusion: Elderly patients with Type-2 diabetes complicated with CHD showed systemic microinflammation, decreased antioxidant molecule content, as well as myocardial damage and abnormal lipid metabolism compared with patients with CHD alone. For this reason, attention should be paid to the above risk factors in clinical practice, and proactive prevention and treatment should be taken to reduce the probability of related complications.

Serum Metabolomics Coupling With Clinical Laboratory Indicators Reveal Taxonomic Features of Leukemia.

Metabolic abnormality has been considered to be the seventh characteristic in cancer cells. The potential prospect of using serum biomarkers metabolites to differentiate ALL from AML remains unclear. The purpose of our study is to probe whether the differences in metabolomics are related to clinical laboratory-related indicators. We used LC-MS-based metabolomics analysis to study 50 peripheral blood samples of leukemia patients from a single center. Then Chi-square test and T test were used to analyze the clinical characteristics, laboratory indicators and cytokines of 50 patients with leukemia. Correlation analysis was used to explore the relationship between them and the differential metabolites of different types of leukemia. Our study shows that it is feasible to better identify serum metabolic differences in different types and states of leukemia by metabolomic analysis on existing clinical diagnostic techniques. The metabolism of choline and betaine may also be significantly related to the patient's blood lipid profile. The main enrichment pathways for distinguishing differential metabolites in different types of leukemia are amino acid metabolism and fatty acid metabolism. All these findings suggested that differential metabolites and lipid profiles might identify different types of leukemia based on existing clinical diagnostic techniques, and their rich metabolic pathways help us to better understand the physiological characteristics of leukemia.

Reconstruction Algorithm-Based CT Imaging for the Diagnosis of Hepatic Ascites.

The study was aimed at exploring the diagnostic value of artificial intelligence reconstruction algorithm combined with CT image parameters on hepatic ascites, expected to provide a reference for the etiological evaluation of clinical abdominal effusion. Specifically, the adaptive iterative hard threshold (AIHT) algorithm for CT image reconstruction was proposed. Then, 100 patients with peritoneal effusion were selected as the research subjects. After 8 cases were excluded, the remaining was divided into 50 cases of the S1 group (hepatic ascites) and 42 cases of the D0 group (cancerous peritoneal effusion). Gemstone energy spectrum CT scanning was performed on all patients, and CT image parameters of the two groups were compared. It was found that CT value of mixed energy, CT value of 60-100 KeV single energy, concentration value of water (calcium), concentration value of water (iodine), and slope of energy spectrum curve in the S1 group were significantly lower than those in the D0 group (P < 0.05). The effective atomic number in the S1 group was significantly higher than that in the D0 group (P < 0.05). Of the 50 patients in the S1 group, 3 (6%) had an ascending and 47 (94%) had a descending spectral curve. Of the 42 patients in the D0 group, 37 (88.1%) had an ascending and 5 (11.9%) had a descending spectral curve. The sensitivity and specificity of water (iodine) were 0.927 and 0.836, respectively. The sensitivity and specificity of water (calcium) were 0.863 and 0.887, respectively. For different scan ranges ([0,90]; [0,120]), root mean square error (RMSE) of AIHT reconstructed image was significantly smaller than that of traditional algorithm, while peak signal-to-noise ratio (PSNR) was opposite. The differences were statistically significant (P < 0.05). In conclusion, AIHT-based CT images can better display the distribution of hepatic ascites, and the parameters of CT value, effective atomic number, water (iodine), water (calcium), and spectral curve can all provide help for the identification of hepatic ascites. Especially, water (iodine) and water (calcium) demonstrated high diagnostic performance of hepatic ascites.

Hemodialysis Arteriovenous Fistula Dysfunction: Retrospective Comparison of Post-thrombotic Percutaneous Endovascular Interventions with Pre-emptive Angioplasty.

BACKGROUND: We aimed to compare the clinical outcomes of pre-emptive angioplasty versus post-thrombotic percutaneous endovascular restoration of dysfunctional arteriovenous fistula (AVF). METHODS: This retrospective study reviewed the data from 80 patients who underwent 114 endovascular interventions for a malfunctioning AVF from July 2016 to August 2019. Stenotic AVFs were treated with pre-emptive angioplasty. Thrombosed AVFs were treated with percutaneous pharmacomechanical fibrinolysis with urokinase used only during the operation or continuously infused. The differences in patency rates were evaluated using the Kaplan-Meier method. In addition, univariate and multivariate regression Cox models were used to determine influential factors on the postintervention primary patency. RESULTS: Post-thrombotic interventions and pre-emptive angioplasty yielded statistically similar rates in clinical success (100 vs. 100%), anatomic success (94 vs. 89%; P = 0.52), complication (4 vs. 11%; P = 0.29), as well as postintervention primary, assisted primary and secondary patency (P = 0.80; 0.57; 0.57). The use of pre-emptive angioplasty was associated with reduced total cost (¥25,108 vs. ¥30,833, P < 0.001). The patients who used urokinase only during the operation prolonged both the primary and assisted primary patency (P = 0.02; 0.002), while those with continuous infusion of urokinase had worst patency rates and high costs (¥39,275 vs. ¥25,108 vs. ¥27,140, P < 0.001). Compared with the other locations, dysfunction in the anastomotic or juxta-anastomotic segment (HR = 0.41, P = 0.001) was associated with prolonged postintervention primary patency. CONCLUSIONS: No clinical outcome differences were found between the post-thrombotic percutaneous endovascular interventions and pre-emptive angioplasty. However, pre-emptive angioplasty decreased access expenditure.

Generation of three lines from multiorgan venous and lymphatic defect syndrome patients.

Multiorgan venous and lymphatic defect (MOVLD) syndrome is a unique visceral vascular malformations with complex etiologies. In this study, primary skin fibroblasts were obtained from three MOVLD patients and reprogrammed into iPSCs by Yamanaka's classical strategy. The MOVLD- iPSCs carrying the DDX24 p.Glu271Lys mutation were confirmed by Sanger sequencing. The pluripotency of MOVLD-iPSCs was verified by the specific molecular markers and gene expression, trilineage differentiation potential. The establishment of the MOVLD-iPSCs will provide a useful model for understanding the mechanisms involved the MOVLD and promoting the development of medical treatment.

New troodontid theropod specimen from Inner Mongolia, China clarifies phylogenetic relationships of later-diverging small-bodied troodontids and paravian body size evolution.

A new troodontid (LH PV39) recovered from the Upper Cretaceous Wulansuhai Formation, Inner Mongolia, China, is described, highlighting the dorsoventrally compressed sacral centra. The completely fused neurocentral junctions indicate that LH PV39 had reached adulthood at the time of death, but its size is nevertheless 20% smaller than that of the sympatric Philovenator, demonstrating that it is the second small-bodied troodontid recovered from the Wulansuhai Formation. Phylogenetic analyses scoring LH PV39 using different strategies and performed with different algorithms unambiguously recovered it as a troodontid. While the parsimony-based analysis scoring LH PV39 as an independent OTU with all of its available characteristics included recovered it as a basal troodontid, the Bayesian analysis suggests a closer relationship of LH PV39 to Almas and an unnamed troodontid from Ukhaa Tolgod, Mongolia (MPC-D100/1126+D100/3500). Body size analysis confirmed a single trend of gigantism throughout the evolution of troodontids, and suggests that the Late Cretaceous troodontids evolved in two directions: (i) several size-independent characteristics evolved while retaining the small sizes that are typical of the Early Cretaceous relatives, resulting in the Late Cretaceous small-bodied troodontids; and (ii) size-dependent characteristics (e.g., the elongation of the rostrum) evolved accompanying the size increase, resulting in large-bodied derived troodontids. The mosaic features of the Late Cretaceous small-bodied troodontids place them intermediate between their Early Cretaceous basal relatives and the Late Cretaceous large-bodied taxa in a well-resolved phylogeny, which is crucial for understanding the size and morphological evolution of troodontids.

Myocardial infarction biomarker C-reactive protein detection on nanocomposite aptasensor.

Myocardial infarction (MI) is considered as one of the major life-threatening health issues worldwide. Growing number of cases every year is demanding rapid, portable, and early detection by the sensing devices for the identification of MI. This research work introduces a modified interdigitated electrode (IDE) sensing surface constructed with single-walled carbon nanotube (SWCN) to detect the cardiac biomarker, C-reactive protein (CRP). CRP-specific aptamer was conjugated with gold nanoparticle and attached on SWCN-constructed IDE surface. This probe-modified sensing surface has reached the limit of CRP detection to 10 pM on a linear regression curve with the regression coefficient of R² = 0.9223 [y = 0.9198x - 0.4326]. Further, control molecules, such as random aptamer sequence and nontarget cardiac biomarker (Troponin I), did not show the current response, indicating the specific CRP detection. This sensing strategy helps to detect the lower level of CRP and diagnose the MI at its earlier stages.

Projection-to-image transform frame: a lightweight block reconstruction network for computed tomography.

Several reconstruction networks have been invented to solve the problem of learning-based computed tomography (CT) reconstruction. However, the application of neural networks to tomographic reconstruction remains challenging due to unacceptable memory space requirements. In this study, we present a novel lightweight block reconstruction network (LBRN), which transforms the reconstruction operator into a deep neural network by unrolling the filter back-projection (FBP) method. Specifically, the proposed network contains two main modules, which respectively correspond to the filter and back-projection of the FBP method. The first module of the LBRN decouples the relationship of the Radon transform between the reconstructed image and the projection data. Therefore, the following module, block back-projection, can use the block reconstruction strategy. Because each image block is only connected with part-filtered projection data, the network structure is greatly simplified and the parameters of the whole network are dramatically reduced. Moreover, this approach is trained end-to-end, working directly from raw projection data, and does not depend on any initial images. Five reconstruction experiments are conducted to evaluate the performance of the proposed LBRN: full angle, low-dose CT, region of interest, metal artifact reduction and a real data experiment. The results of the experiments show that the LBRN can be effectively introduced into the reconstruction process and has outstanding advantages in terms of different reconstruction problems.

Angular sensitivity of an x-ray differential phase contrast imaging system with real and virtual source images.

In this work, a novel, to the best of our knowledge, approach based on an x-ray thin lens imaging theory is proposed to predict the angular sensitivity responses of dual-phase-grating differential phase contrast (DPC) interferometers. Experimental validations have been performed to demonstrate the high accuracy of theoretical predictions using two different setups: one with real source images and the other with virtual source images. This new sensitivity calculation method is helpful to optimize the DPC imaging performance of a dual-phase-grating system.