j. liu

In this paper, Large Eddy Simulation (LES) is employed to investigate the evolution characteristics of a spiral jet mill. This study aims to provide a theoretical reference for the numerical simulation and design optimization of spiral jet mills. To evaluate the influence of grids on simulation accuracy, grid convergence index (GCI) analysis was carried out on three sets of non-structural grids with equal proportion refinement. The visualization results demonstrate that the feeding gas traction and jet impact attenuation contribute to momentum conversion from the edge to the central domain, facilitating the development of the central swirl. The cross-scale chamber structure makes the turbulent coherent structure in the swirl evolution tend to be complex and disordered. A large-scale annular swirl is formed by stacking and winding multiple strip vortices. By comparing with the steady-state solution calculated using the k-epsilon model, it is confirmed that the aerodynamic characteristics in the micronization chamber stabilize at 400 ms. At this time, the combined action of the radial and tangential velocity forms a spiral airflow trajectory.

The research aims to construct a nomograph model for predicting distant metastasis of nasopharyngeal carcinoma after radiotherapy, and to evaluate the differentiation and consistency of the model.

292 nasopharyngeal carcinoma patients are selected and broken into a modeling group (204 cases) and a validation group (88 cases). The modeling group patients are further divided into a distant metastasis group (n=45) and a non-distant metastasis group (n=159). Logistic regression analysis is used to analyze the risk factors for distant metastasis of nasopharyngeal carcinoma after radiotherapy. Radiation therapy is performed on each group of patients and their lactate dehydrogenase, serum albumin, carcinoembryonic antigen are compared.

The proportion of age ≥ 60 years old, lymph node cystic invasion, laryngeal lymph node metastasis, T3-T4 staging, and N2-N3 staging in the distant metastasis group were higher than those in the non-distant metastasis group (P<0.05). Multiple logistic regression analysis denoted that age ≥ 60 years old, lymph node cystic invasion, laryngeal lymph node metastasis, T3-T4 stage, N2-N3 stage were risk factors for distant metastasis of nasopharyngeal carcinoma after radiotherapy (P<0.05). The Hosmer Limeshow goodness of fit test showed that the modeling group 2=5.489, P=0.601; Validation group 2=5.231, P=0.733. The areas under the receiver operating characteristic curves of the modeling group and the validation group were 0.828 and 0.822, respectively.

The model constructed in this study for forecasting the risk of distant metastasis of nasopharyngeal carcinoma after radiotherapy has high prediction accuracy, good consistency, differentiation, and clinical applicability.

To explore computerized tomography (CT) imaging features of pulmonary fungal infection (PFI) in patients with acute leukemia (AL) after chemotherapy.

Totally 116 AL patients who received chemotherapy in our hospital from June 2016 to April 2023 participated into this study, and the pulmonary fungal infection was confirmed by laboratory examination and clinical antifungal treatment. The CT image signs, lesion distribution, CT concomitant signs and main types of fungal infection were analyzed.

CT image signs of two main types, nodule/mass type and mixed type were recorded, with76 cases of nodular/mass type and 40 cases of mixed type. There were 372 lesions in nodules/mass cases, mainly in the upper lung (46.24%). In these 372 lesions, 113 micro-tubercle, 138 small nodules, 115 nodules and 6 masses were included. There were 88 cases of halo sign, 26 cases of cavity, and 25 cases of air crescent sign. Candida albicans was the most common pathogenic fungal strain, followed by aspergillus, candida tropicalis, candida glabrata, candida parapsilosis, cryptococcus, candida dubliniensis, mucor, candida krusei and candida rugosa.

The CT manifestations of AL complicated with pulmonary fungal infection after chemotherapy were various, most of which had no characteristics, but the “halo sign” and “air crescent sign” had certain specificity. The combined CT and clinical manifestations can narrow the range of differential diagnosis. When the diagnosis still cannot be confirmed, diagnostic therapy or early diagnosis by fungal culture and histological examination can be performed.

We aimed to analyze the value of volume rendering (VR) in diagnosing different solitary pulmonary nodules (SPNs) with diameter less than 1.0 cm and assessing invasion depth in lung adenocarcinoma.

In total, 908 patients with SPN that was confirmed by postoperative pathology were included, followed by an analysis of the imaging characteristics (including microvascular sign, vascular convergence, lobulation, and spiculation) of malignant and benign SPN based on VR. Moreover, the detection rates of imaging signs of three types of malignant SPNs (pure ground grass nodule, pGGN; part-solid nodule; and solid nodule) classified by SPN density and three invasion depths of adenocarcinoma (pre-invasion lesion, PIL; micro invasive adenocarcinoma, MIA; and invasive adenocarcinoma, IAC) were also analyzed.

The microvascular sign detection rate was higher while vascular convergence and spiculation detection rates were lower in malignant SPN than in benign SPN. The microvascular sign possessed high sensitivity (82%) and specificity (72%) in predicting malignant and benign SPNs. The microvascular sign detection rate decreased while vascular convergence, lobulation, and spiculation detection increased with the rising density of malignant SPN. Furthermore, the detection rates of the four imaging signs all increased with the adenocarcinoma invasion depth. Microvascular sign showed good detecting ability in low density SPNs pGGN (81.8%), part-solid nodules (95.8%), and in all three invasion depths of adenocarcinoma (PIL [68.2%], MIS [95.3%], and IAC [87.2%]).

These imaging features distinguished by VR exhibited an excellent differential diagnostic ability of various SPNs as well as invasion depth of lung adenocarcinoma.

This study aimed to determine the diagnostic value of ground-glass opacities on computed tomography combined with computed tomography re-examination in patients with suspected novel coronavirus pneumonia.

Suspected cases of novel coronavirus pneumonia were identified retrospectively between January 23 and February 18, 2020. Computed tomography examination was conducted for all patients. For all suspected cases, real-time reverse transcription-polymerase chain reaction detection of novel coronavirus nucleic acid was conducted. Computed tomography re-examination in the short term was also performed.

Among 92 patients suspected with novel coronavirus pneumonia, 15 were diagnosed with coronavirus disease 2019. There were ground-glass opacities on chest computed tomography in 34 patients, and 8 of these patients were confirmed to have novel coronavirus pneumonia. In total, 30 patients showed no absorption on computed tomography re-examination, of which 10 (10/30) were diagnosed with novel coronavirus pneumonia. Additionally, 20 patients had non-absorption of lesions when ground-glass opacities on initial and follow-up computed tomography were combined, and 13 of these patients were confirmed to have novel coronavirus pneumonia. For ground-glass opacities on computed tomography combined with non-absorption of lesions on computed tomography re-examination, the sensitivity and specificity for the diagnosis of the novel coronavirus were 86.7% and 90.1%, respectively.

Among suspected patients with novel coronavirus pneumonia, combining ground-glass opacities on computed tomography with a computed tomography re-examination might improve the accuracy of diagnosis.

Preoperative assessment of lymph node metastasis (LNM) status is the basis of individual treatment for rectal cancer (RC). However, conventional imaging methods are not accurate enough.

We collected 282 RC patients who were divided into the training dataset (n=225) and the test dataset (n=57) with an 8:2 scale. A large number of deep learning (DL) features and hand-crafted radiomics (HCR) features of primary tumors were extracted from the arterial and venous phases of the computed tomography (CT) images. Three machine learning models, including support vector machine (SVM), k-nearest neighbor (KNN),and multi-layer perceptron (MLP) were utilized to predict LNM status in RC patients. A stacking nomogram was constructed by selecting optimal machine learning models for arterial and venous phases, respectively, combined with predictive clinical features.

The stacking nomogram performed well in predicting LNM status, with an area under the curve (AUC) of 0.914 [95% confidence interval (CI): 0.874-0.953] in the training dataset, and an AUC of 0.942 (95%CI: 0.886-0.997) in the test dataset. The AUC of the stacking nomogram were higher than those of CT_reported_N_status, ASVM, and VSVM model in the training dataset (P <0.05). However, in the test dataset, although the AUC of the stacking nomogram was higher than the VSVM, the difference was not obvious (P =0.1424).

The developed deep learning radiomics stacking nomogram showed to be effective in predicting the preoperative LNM status in RC patients.

To investigate whether features of 5-mm peritumoral regions could significantly improve the predictive efficacy of a radiomics model based on solid pulmonary tumors at distinguishing lung adenocarcinoma(LAC) from granuloma(GR).

We retrospectively evaluated 167 lung tumors pathologically proven to be LAC (96) or GR (71) and divided them into training group (116) and testing (51) group. We delineated each tumor with three different measures using the tumor and its 5-mm peritumoral region. Then, we extracted 465 features from each volume of interest(VOI) and chose the optimal features to build the diagnostic models. We built four different models using different methods. Finally, we compared the performance of the four models in the test set.

The area under the curve(AUC) of each model in the test group was 0.765 (95% confidence interval(CI): 0.620–0.909), 0.797 (95%CI: 0.670–0.924), and 0.784 (95%CI: 0.647–0.920), respectively. Results of the DeLong test showed that the differences between model 2, model 3, and model 1 were not significant. Results of net reclassification improvement(NRI) showed that model 2 and model 3 had better differential diagnostic efficacy than model 1, with accuracies(ACCs) of 0.784, 0.745, and 0.686, respectively, but the differences were not significant (P>0.05). Moreover, the nomogram had good diagnostic and predictive abilities, with an AUC of 0.848 (95%CI: 0.736–0.961) and an ACC of 0.804.

Features of 5-mm peritumoral regions improved the predictive ability of the radiomics model based on the solid pulmonary tumor, but the difference was not significant.

The predatory Bdellovibrio is considered one of the most promising probiotics in aquaculture. Yet the effect of dietary Bdellovibrio probiotics on Chinese mitten crab Eriocheir sinensis has never been evaluated. In the present study, a fifty-day feeding trial was conducted to assess the effects of dietary Bdellovibrio powder at a recommended final dose of 7.5 g kg-1 diets on non-specific immunity, antioxidant ability and disease resistance of E. sinensis. The results indicated that compared with the control, the activities of lysozyme, superoxide dismutase, catalase, acid phosphatase, and alkaline phosphatase were significantly increased in the serum and hepatopancreas of E. sinensis fed with Bdellovibrio powder-supplemented diets (p<0.05). Besides, a significant reduction of malondialdehyde level was also observed in the serum and hepatopancreas of Bdellovibrio powder-fed crabs (p<0.05). In addition, the test crabs fed diets with Bdellovibrio powder for fifty days exhibited significantly (p<0.05) higher protection against aeromonasis, showing a relative percentage survival of 81.25% against Aeromonas veronii challenge for seven days. To conclude, dietary supplementation of Bdellovibrio powder for fifty days can increase immunity, antioxidant capability and resistance of E. sinensis to A. veronii infection.

The purpose of this work isto investigate transient aerodynamic characteristics of the coach under the crosswind in straight-line situations with different uniform speeds and uniform accelerations. The transient aerodynamics caused by different speed changes are analyzed using the real-time interaction between aerodynamic simulation and dynamic simulation. The target model is a simplified coach on a full scale. The SST (Menter) K-Omega Improved Delayed Detached Eddy Simulation and overset mesh technique are used to predict the transient aerodynamic loads. The accuracy of the turbulence model is verified by a wind tunnel experiment of the 1/7th scaled coach model. The present results show that the transient aerodynamic loads have different locations of maximum side force and the holding duration of yaw moment for different constant speeds. The speed becomes larger, and the position where the side force is maximum becomes farther away. The holding duration of the top yaw moment is larger simultaneously. Moreover, proper acceleration for low initial driving speed and crosswind of small influence range could build up stability. High speed driving in gust wind is not suggested for unskilled drivers.