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IntroductionMantle-derived CO2, as an important component of hydrothermal fluids, is widely distributed in petroliferous basins. While previous experimental studies have suggested that CO2 can improve sandstone reservoir quality through mineral dissolution in open fluid setting, they have overlooked its nagetive effects to sandstone reservoir quality by carbonate cementation. Additionally, the roles of various fluid environments in CO2-reservoir interactions have not been studied in detail.MethodsTo systematically investigate the influences of CO2 on sandstone reservoirs, we examine a typical mantle-derived CO2 gas reservoir, Bohai Bay Basin, China. This study employs integrated methods, including electron microscopy, scanning electron microscopy, X-ray diffraction, stable C- and O-isotope analysis, and physical property data. The aim is to investigate the evidence and mechanisms by which mantle-derived CO2 impacts sandstone reservoirs, particularly focusing on its effects in open and closed fluid environments.Results and DiscussionOur findings reveal that dawsonite and ankerite are prevalent within the mantle-derived CO2 gas reservoir, while isotopic analysis of carbonate cements indicates values (δ13C: −9.0‰ to −1.6‰; δ18O: −21.7‰ to −12.7‰) consistent with mantle-derived CO2 and hydrothermal fluids. These pieces of evidence indicate that CO2-rich hydrothermal fluids participate in water-rock interactions, thereby significantly influencing the diagenesis of reservoirs. Further, we notice that CO2 reservoirs adjacent to faults exhibit an open fluid environment, characterized by superior porosity and permeability, more quartz, but fewer feldspar, carbonate, and clay minerals compared to those in closed fluid environments. Notably, kaolinite predominates in open fluid environments, while illite/smectite (I/S) is more common in closed settings. The dual roles of mantle-derived CO2 are highlighted in our analysis: while it enhances reservoir storage and permeability through mineral dissolution, the carbonate cement generated by CO2-water-rock interaction can also adversely affect reservoir quality. In open fluid environments, CO2 facilitates the dissolution of feldspar and carbonate minerals, promoting the timely removal of dissolution by-products (clay mineral) and inhibiting carbonate cementation, thereby improving reservoir properties. Conversely, in closed fluid environments, decreasing CO2 concentrations with depth leads to diminishing dissolution effects and increased carbonate cementation, resulting in reduced reservoir porosity and permeability. Overall, the significance of this study is to correct the deviation in the impacts of CO2 on sandstone reservoirs at laboratory setting through case study of typical mantle-source CO2 gas reservoir.This work can be applied to the studies of reservoir homogeneity and sweet spots in regions with hydrothermal and mantle-derived CO2 activities. However, due to the limitation of CO2 content range (about 15%–70%) in the study case, we are unable to investigate the effects of low-concentration CO2 on sandstone reservoirs, which may affect the generalizability of this work. Besides, the formation temperature and pressure, and salinity of formation water, should be considered when dealing with other cases.

Hematoma expansion (HE) is an important risk factor for death or poor prognosis in patients with hypertensive intracerebral hemorrhage (HICH). Accurately predicting the risk of HE in patients with HICH is of great clinical significance for timely intervention and improving patient prognosis. Many imaging signs reported in literatures showed the important clinical value for predicting HE. In recent years, the development of radiomics and artificial intelligence has provided new methods for HE prediction with high accuracy. Therefore, this article reviews the latest research progress in CT imaging, radiomics, and artificial intelligence of HE, in order to help identify high-risk patients for HE in clinical practice.

Multiple types of reservoirs, including volatile oil reservoirs, condensate gas reservoirs, and dry gas reservoirs, have been discovered in ultra-deep layers buried at depths greater than 7500 m. Understanding the genetic types of natural gas is of utmost importance in evaluating oil and gas exploration potential. The cumulative proved reserves of the super deep layer in the Shuntuoguole low uplift area of the Tarim Basin exceed 1 × 108 t (oil equivalent). The origin, source, and accumulation characteristics of natural gas still remain a subject of controversy. By analyzing the composition and carbon isotope of natural gas, a detailed investigation was conducted to examine the unique geochemical and reservoir formation characteristics of the Ordovician ultra-deep natural gas within different fault zones in the middle region of the Shuntuoguole low uplift. It was determined that most of the natural gas in this area is displaying a characteristic of wet gas with a drying coefficient ranging from 0.41 to 0.99. The carbon isotope composition of methane in the gas reservoir shows relatively light values, ranging from −49.4‰ to −42‰. The carbon and hydrogen isotopes of the components are distributed in a positive order. The natural gas is oil type gas, which is derived from marine sapropelic organic matter and has a good correspondence with the lower Yuertusi formation. The maturity of natural gas in Shunbei No. 1 and No. 5 fault zones is about 1.0%, which is the associated gas of normal crude oil, while the maturity of No. 4 and No. 8 fault zones is higher than 1.0%, which is the mixture of kerogen pyrolysis gas and crude oil pyrolysis gas. The variations in the drying coefficient and carbon isotope composition of the natural gas provide evidence for the migration patterns within the Shuntuoguole low uplift central region. It indicates that the Shunbei No. 5 and No. 8 fault zones have likely migrated from south to north, while the No. 4 fault zone has migrated from the middle to both the north and south sides. These migration patterns are primarily controlled by high and steep strike-slip faults, which facilitate the vertical migration of natural gas along fault planes. Consequently, the gas accumulates in fractured and vuggy reservoirs within the Ordovician formation.

In order to investigate the effect of pre-tension on the anchoring and crack-arresting effect of rockbolts, a theoretical model of stress intensity factor at the crack tip in anchored surrounding rock was established using fracture mechanics theory. An expression for the difference in stress intensity factor due to axial force on the rockbolt was derived, exploring the influence of pre-tension on the stress intensity factor of cracks. A numerical model of anchored crack specimens was developed using UDEC (V6.0) software to simulate and analyze the mechanical performance and damage characteristics of specimens anchored with different pre-tension. The results indicate that the difference in stress intensity factor of cracks is positively correlated with pre-tension. High-pre-tensioned rockbolts can effectively reduce the stress intensity factor of cracks. Prestressed rockbolts can alter the failure mode of rock masses from shear failure along pre-existing cracks to tensile splitting failure. The application of high pre-tension significantly enhances the strength of the rock mass, reducing both the damage degree and the number of internal cracks. After anchoring with high-pre-tensioned rockbolts, the peak strength and elastic modulus of the crack specimens increased by 22.5% and 31.9%, respectively, while damage degree decreased by 17.4%, the number of shear cracks decreased by 22.6%, and the number of tensile cracks decreased by 42.9%. The pre-tensioned rockbolt method proposed in this study was applied to the support of roadway widening. Field monitoring data indicated that the axial force of the rockbolts in the test section generally exceeded 60 kN, effectively controlling the deformation of the roadway surrounding the rock. The convergence of the two sides decreased by 22%, and borehole inspections showed a significant reduction in internal cracks. The research results provide a theoretical basis for controlling the discontinuous deformation of deep broken surrounding rock roadways.

PurposeEarly and rapid diagnosis of mild cognitive impairment (MCI) has important clinical value in improving the prognosis of Alzheimer’s disease (AD). The hippocampus and parahippocampal gyrus play crucial roles in the occurrence of cognitive function decline. In this study, deep learning and radiomics techniques were used to automatically detect MCI from healthy controls (HCs).MethodThis study included 115 MCI patients and 133 normal individuals with 3D-T1 weighted MR structural images from the ADNI database. The identification and segmentation of the hippocampus and parahippocampal gyrus were automatically performed with a VB-net, and radiomics features were extracted. Relief, Minimum Redundancy Maximum Correlation, Recursive Feature Elimination and the minimum absolute shrinkage and selection operator (LASSO) were used to reduce the dimensionality and select the optimal features. Five independent machine learning classifiers including Support Vector Machine (SVM), Random forest (RF), Logistic Regression (LR), Bagging Decision Tree (BDT), and Gaussian Process (GP) were trained on the training set, and validated on the testing set to detect the MCI. The Delong test was used to assess the performance of different models.ResultOur VB-net could automatically identify and segment the bilateral hippocampus and parahippocampal gyrus. After four steps of feature dimensionality reduction, the GP models based on combined features (11 features from the hippocampus, and 4 features from the parahippocampal gyrus) showed the best performance for the MCI and normal control subject discrimination. The AUC of the training set and test set were 0.954 (95% CI: 0.929–0.979) and 0.866 (95% CI: 0.757–0.976), respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high.ConclusionThe GP classifier based on 15 radiomics features of bilateral hippocampal and parahippocampal gyrus could detect MCI from normal controls with high accuracy based on conventional MR images. Our fully automatic model could rapidly process the MRI data and give results in 1 minute, which provided important clinical value in assisted diagnosis.

BackgroundParkinson’s disease (PD) is the second most common neurodegenerative disease. An objective diagnosis method is urgently needed in clinical practice. In this study, deep learning and radiomics techniques were studied to automatically diagnose PD from healthy controls (HCs).Methods155 PD patients and 154 HCs were randomly divided into a training set (246 patients) and a testing set (63 patients). The brain subregions identification and segmentation were automatically performed with a VB-net, and radiomics features of billateral thalamus, caudatum, putamen and pallidum were extracted. Five independent machine learning classifiers [Support Vector Machine (SVM), Stochastic gradient descent (SGD), random forest (RF), quadratic discriminant analysis (QDA) and decision tree (DT)] were trained on the training set, and validated on the testing. Delong test was used to compare the performance of different models.ResultsOur VB-net could automatically identify and segment the brain into 109 regions. 2,264 radiomics features were automatically extracted from the billateral thalamus, caudatum, putamen or pallidum of each patient. After four step of features dimensionality reduction, Delong tests showed that the SVM model based on combined features had the best performance, with AUCs of 0.988 (95% CI: 0.979 ~ 0.998, specificity = 91.1%, sensitivity =100%, accuracy = 89.4% and precision = 88.2%) and 0.976 (95% CI: 0.942 ~ 1.000, specificity = 100%, sensitivity = 87.1%, accuracy = 93.5% and precision = 88.6%) in the training set and testing set, respectively. Decision curve analysis showed that the clinical benefit of the line graph model was high.ConclusionThe SVM model based on combined features could be used to diagnose PD with high accuracy. Our fully automatic model could rapidly process the MRI data and distinguish PD and HCs in one minute. It greatly improved the diagnostic efficiency and has a great potential value in clinical practice to help the early diagnosis of PD.

Abstract Objectives Rupture of intracranial aneurysm is very dangerous, often leading to death and disability. In this study, deep learning and radiomics techniques were used to automatically detect and differentiate ruptured and unruptured intracranial aneurysms. Materials and methods 363 ruptured aneurysms and 535 unruptured aneurysms from Hospital 1 were included in the training set. 63 ruptured aneurysms and 190 unruptured aneurysms from Hospital 2 were used for independent external testing. Aneurysm detection, segmentation and morphological features extraction were automatically performed with a 3-dimensional convolutional neural network (CNN). Radiomic features were additionally computed via pyradiomics package. After dimensionality reduction, three classification models including support vector machines (SVM), random forests (RF), and multi-layer perceptron (MLP) were established and evaluated via area under the curve (AUC) of receiver operating characteristics. Delong tests were used for the comparison of different models. Results The 3-dimensional CNN automatically detected, segmented aneurysms and calculated 21 morphological features for each aneurysm. The pyradiomics provided 14 radiomics features. After dimensionality reduction, 13 features were found associated with aneurysm rupture. The AUCs of SVM, RF and MLP on the training dataset and external testing dataset were 0.86, 0.85, 0.90 and 0.85, 0.88, 0.86, respectively, for the discrimination of ruptured and unruptured intracranial aneurysms. Delong tests showed that there was no significant difference among the three models. Conclusions In this study, three classification models were established to distinguish ruptured and unruptured aneurysms accurately. The aneurysms segmentation and morphological measurements were performed automatically, which greatly improved the clinical efficiency. Clinical relevance statement Our fully automatic models could rapidly process the CTA data and evaluate the status of aneurysms in one minute. Graphical Abstract

Thin sections, AIM-SEM, MICP, and nitrogen adsorption were performed on laminated and layered shales to characterize their complex pore and fracture structure. Combining the MICP model with the FHH model, this work proposes a new fractal method for lacustrine shales with complex lamina structure. The fractal characteristics presented four zones, representing the heterogeneity of fractures, macropores, mesopores, and micropores. The pores and fractures of shale have strong heterogeneity. Laminated shale has strong heterogeneity in mesopores and moderate heterogeneity in micropores. Layered shale has strong heterogeneity in fractures and moderate heterogeneity in micropores. The lamina structure and content of organic and mineral composition has a great influence on heterogeneity. The mineral laminae in laminated shale change frequently; lamellation fractures are mainly developed, and the structures are similar. Layered shales develop fractures between layers and structural fractures; the structural differences are significant. Macropores are mostly interparticle pores between quarts with similar structures. The wider lamina thickness of layered shale provides sufficient crystallization space for minerals, so the mesopores of layered shale are more homogeneous. Micropores are less developed, mainly consisting of intraparticle pores between clay minerals, which are complex but similar in structure in the two types of shale. The heterogeneity of mesopores and micropores is not conducive to hydrocarbon migration. Fractures and macropores need to be connected with meso–micropores to form a transport system. So, mesopores and micropores play decisive roles in hydrocarbon migration. Based on the above understanding, this paper points out that hydrocarbon in laminated shale with more carbonate minerals and a high thermal evolution degree has better availability.

The composition of microbiota in the digestive tract gut is essential for insect physiology, homeostasis, and pathogen infection. Little is known about the interactions between microbiota load and oral infection with baculoviruses. CnmeGV is an obligative baculovirus to Cnaphalocrocis medinalis. We investigated the impact of CnmeGV infection on the structure of intestinal microbes of C. medinalis during the initial infection stage. The results revealed that the gut microbiota profiles were dynamically driven by pathogen infection of CnmeGV. The numbers of all the OTU counts were relatively higher at the early and later stages, while the microbial diversity significantly increased early but dropped sharply following the infection. The compositional abundance of domain bacteria Firmicutes developed substantially higher. The significantly enriched and depleted species can be divided into four groups at the species level. Fifteen of these species were ultimately predicted as the biomarkers of CnmeGV infection. CnmeGV infection induces significant enrichment of alterations in functional genes related to metabolism and the immune system, encompassing processes such as carbohydrate, amino acid, cofactor, and vitamin metabolism. Finally, the study may provide an in-depth analysis of the relationship between host microbiota, baculovirus infection, and pest control of C. medinalis.

Background As a member of the immunoglobulin superfamily, hemolins play a vital role in insect development and defense against pathogens. However, the innate immune response of hemolin to baculovirus infection varies among different insects. Methods and results In this study, the hemolin-like gene from a Crambidae insect, Cnaphalocrocis medinalis, CmHem was cloned, and its role in insect development and baculovirus infection was analyzed. A 1,528 bp contig as potential hemolin-like gene of C. medinalis was reassembled from the transcriptome. Further, the complete hemolin sequence of C. medinalis (CmHem) was cloned and sequenced. The cDNA of CmHem was 1,515 bp in length and encoded 408 amino acids. The deduced amino acid of CmHem has relatively low identities (41.9–62.3%) to various insect hemolins. However, it contains four Ig domains similarity to other insect hemolins. The expression level of CmHem was the highest in eggs, followed by pupae and adults, and maintained a low expression level at larval stage. The synthesized siRNAs were injected into mature larvae, and the CmHem transcription decreased by 51.7%. Moreover, the abdominal somites of larvae became straightened, could not pupate normally, and then died. Infection with a baculovirus, C. medinalis granulovirus (CnmeGV), the expression levels of CmHem in the midgut and fat body of C. medinalis significantly increased at 12 and 24 h, respectively, and then soon returned to normal levels. Conclusions Our results suggested that hemolin may be related to the metamorphosis of C. medinalis. Exposure to baculovirus induced the phased expression of hemolin gene in the midgut and fat body of C. medinalis, indicated that hemolin involved in the immune recognition of Crambidae insects to baculovirus.

Cell wall hydrolases are ubiquitous among spore-form bacteria and essential for mother cell lysis. In this study, a novel cell wall hydrolase gene cwlE involved in mother cell lysis was characterized from Bacillus thuringiensis subsp. israelensis (Bti) strain Bt-59. cwlE was specifically expressed in Bti and located in the large plasmid carrying the insecticidal genes. The encoded CwlE protein consists of a MurNAc-LAA domain and two highly conserved catalytic residues (E26 and E151). The recombinant CwlE-His protein was able to digest the cell wall of Bti, indicating that CwlE is an N-acetylmuramoyl-L-alanine amidase. Transcriptional analysis indicated that cwlE began to express at the early stage of stationary phase and was controlled by SigE. Single mutation of cwlE gene delayed Bti mother cell lysis, while double mutation of cwlE and sigK completely blocked Bti mother cell lysis. After exposure to UV light to deactivate the crystal proteins, the level of decrease of insecticidal activity against mosquito larvae of Bt-59 (ΔcwlE-sigK) was less than that observed for Bt-59. This study elucidates the mechanism of Bti mother cell lysis and provides an effective strategy for mosquito control using Bt products with increased persistence.

Hydrocarbon accumulation in coal measure strata is consist of several types which includes intra-source accumulation and adjusted accumulation, particularly in basins that had experienced multi-stage tectonic activities. The mechanism governing this accumulation is extremely complex. Using the Paleozoic petroleum system in the Huanghua Depression as an example, the mechanism of hydrocarbon accumulation in deep reservoirs can be revealed by means of core observation, geochemistry testing of coal measure source rock, thin section observation, fluid inclusions testing, and profile analysis of typical reservoirs, combined with the burial and thermal history of strata. Based on the regional tectonic, the mechanism of hydrocarbon accumulation in coal measures is defined and the accumulation model was established. The results show that the Paleozoic petroleum system in the Huanghua Depression has three different types of source-reservoir-cap assemblages: under-source, intra-source, and above-source assemblage. Regional tectonic evolution controlled the hydrocarbon generation process of source rocks, showing the hydrocarbon generation characteristics of “oil in the early stage and gas in the late stage.” The Middle Cretaceous is the first of two periods of hydrocarbon accumulation, during which stage occurred in low-maturity oil and a small amount of natural gas were mainly stored in intergranular pores and dissolution pores. The tectonic uplift in the Late Cretaceous caused the destruction of the ancient reservoir. The second accumulation stage occurred in the Middle Paleogene to the present. A large amount of natural gas and high maturity oil were mostly stored in dissolution pores and structural fractures. The hydrocarbon accumulation in Huanghua Depression was simultaneously regulated by reservoir reformation, tectonic activities, and source rock maturation. Based on the foregoing understanding, the hydrocarbon accumulation model of “oil and gas transfer station” in coal measures is put forward, that is, oil and gas are first accumulated in intra-source or near-source reservoirs, and are then adjusted from this “oil and gas transfer station” to other areas as a result of tectonic activity.

Symmetrical solid oxide fuel cells (S-SOFCs) are prepared via a facile one-step co-sintering method with highly reactive Sm0.2Ce0.8O1.9 (SDC) electrolyte and Sr2Fe1.5Mo0.5O6-δ (SFM) electrodes. The phase compositions and microstructures are studied by XRD, TEM, and FESEM techniques, and the electrolyte-supported single cells with gas-tight SDC electrolyte and porous SFM-SDC electrode are prepared after one-step co-sintering at 1100 °C or higher temperatures for 4 h. In particular, the AC impedance spectra reveal that the SDC electrolyte sintered at 1200 °C exhibits the highest oxide ionic conductivity of ~35 mS/cm at 700 °C, while the electrode polarization resistance achieves the lowest value of 0.32 Ω·cm2 at 700 °C in air for the sample co-sintered at 1100 °C. Accordingly, the output measurements are carried out on the single cells co-sintered at 1100 °C and 1200 °C. It is found that the single cell co-sintered at 1200 °C possesses the highest peak power density of 216 mW/cm2 at 700 °C, demonstrating the potential application of the one-step co-sintering method in low-cost manufacturing of S-SOFCs.

Impact ground pressure is one of the most common dynamic disasters induced by mining activities, and water content is an important factor affecting such dynamic disasters. In this paper, uniaxial compression test, cyclic loading and unloading test, and acoustic emission test were conducted on white sandstone using RMT-150B rock mechanics test system and DS5 acoustic emission test system. The influence law of water content was analyzed on the strength characteristics, energy change characteristics, and impact propensity of white sandstone. The results showed that (1) the internal structure of the sandstone gets softened with the increase of the water content. The cohesive effect within the rock also begins to weaken, which in turn reduces the stiffness of the material and enhances its plasticity. The ability of the rock to resist elastic deformation becomes weaker, resulting in lower compressive strength and elastic modulus when the rock is subjected to external forces, making it more prone to deform and fail. The decrease in compressive strength of the water-saturated rock is 33.3%, and the decrease in its elastic modulus is 28.1% compared to the dry rock. (2) As the water content increases, the cohesion of the rock decreases and the internal structure of the rock fails more easily, which ultimately makes the energy needed for rock destruction lower. As a result, the total energy, elastic energy, and dissipative energy of the rock are reduced. The accumulated AE energy also decreases with the increase of the water content, indicating that rocks with higher water content gather less elastic energy before damage and accumulate less energy when deformation damage occurs. (3) The impact energy index and elastic energy index are negatively correlated with the water content. The impact energy index is reduced by 28.6%, and the elastic energy index is reduced by 20.9% for the saturated rock compared to the dry rock. The elastic energy index and impact energy index both decrease with the increase of rock water content, indicating that the less elastic energy is stored before the destruction of the rock and no excess energy is transformed into energy in rock crushing when the rock breaks, and therefore, the impact propensity of the rock is smaller. The results of the study can provide a theoretical basis for underground construction as well as rock fracture destabilization.

Deep fluid activity is widespread in large oil-gas basins around the world. Deep fluids, as the links between internal and external factors of a basin, run in the way of organic-inorganic interactions through the oil-gas formation and aggregation. Herein, the identification characteristics of deep fluids in sedimentary basins as well as their influence on oil-gas reservoir formation and geothermal resource are summarized. The deep fluids of sedimentary basins are identified from three aspects, including mineral composition, fluid inclusions, and geochemical characteristics. The effects of deep fluid activities on oil-gas reservoir formation are manifested in two key aspects of matter and energy. As for the matter effects, deep fluids can improve the primary productivity of sedimentary basins and carry abundant inorganic hydrogen, which contributes to improving the hydrocarbon productivity through hydrogenation. As for the energy effects, the heat energy of deep fluids can promote the mature evolution from organic matter to oil and gas. During this process, the heating of deep fluids will cause the oil-generation window depth of the hydrocarbon source rocks to become thinner, and it will also generate very high pressure, which will promote the discharge of abundant hydrocarbons formed by the hydrocarbon source rocks. Furthermore, deep fluids can directly form volcanic rock oil-gas reservoirs. And another manifestation of deep fluid energy is geothermal. And the thermal energy of deep fluids can directly form hot dry rocks, which is the most important existing form of geothermal resources. The geological exploration of hot dry rocks should be supported by further geochemical and geophysical research.

BackgroundTraumatic brain injury (TBI) is the main cause of death and severe disability in young adults worldwide. Progressive hemorrhage (PH) worsens the disease and can cause a poor neurological prognosis. Radiomics analysis has been used for hematoma expansion of hypertensive intracerebral hemorrhage. This study attempts to develop an optimal radiomics model based on non-contrast CT to predict PH by machine learning (ML) methods and compare its prediction performance with clinical-radiological models.MethodsWe retrospectively analyzed 165 TBI patients, including 89 patients with PH and 76 patients without PH, whose data were randomized into a training set and a testing set at a ratio of 7:3. A total of 10 different machine learning methods were used to predict PH. Univariate and multivariable logistic regression analyses were implemented to screen clinical-radiological factors and to establish a clinical-radiological model. Then, a combined model combining clinical-radiological factors with the radiomics score was constructed. The area under the receiver operating characteristic curve (AUC), accuracy and F1 score, sensitivity, and specificity were used to evaluate the models.ResultsAmong the 10 various ML algorithms, the support vector machine (SVM) had the best prediction performance based on 12 radiomics features, including the AUC (training set: 0.918; testing set: 0.879) and accuracy (training set: 0.872; test set: 0.834). Among the clinical and radiological factors, the onset-to-baseline CT time, the scalp hematoma, and fibrinogen were associated with PH. The radiomics model's prediction performance was better than the clinical-radiological model, while the predictive nomogram combining the radiomics features with clinical-radiological characteristics performed best.ConclusionsThe radiomics model outperformed the traditional clinical-radiological model in predicting PH. The nomogram model of the combined radiomics features and clinical-radiological factors is a helpful tool for PH.

Soft broken surrounding rock exhibits obvious rheological properties and time-dependent weakening effects under the action of deep high-ground stress, leading to the increasingly prominent problem of sustained large deformation in deep roadways. In this study, with the II5 Rail Rise in Zhuxianzhuang Coal Mine as an example, the mechanism and control technology of time-dependent damage and instability in a deep soft-rock roadway were explored through a field observation and numerical simulation. The research results show that the range of the loose circle in the deep fractured surrounding rock can reach 3.0 m. The expansion of shallow and deep cracks causes the primary plastic deformation and secondary rheological deformation of the surrounding rock, with the rheological deformation rate increasing by 21.4% every 55 days on average, which ultimately induces the instability and failure of the surrounding rock. Based on the mechanism of roadway instability, a control technology of high-preload bolt + deep- and shallow-borehole crack filling was proposed. The technology reduces deformation and ensures the stability of the roadway surrounding rock by inhibiting the propagation of deep and shallow cracks and reinforcing the surrounding rock.

AbstractIn this study, the movement and failure law of working face overburden and the distribution characteristics of mining stress are analyzed using laboratory test and numerical calculation methods to address the problems of large deformation, failure instability, and difficult maintenance of the soft rock roof roadways of deep stope influenced by strong disturbance, the roof gas comprehensive treatment roadway of 17191 (1) working face of Pansan mine of China Huainan Mining Group was considered as the engineering background. The deformation and failure mechanisms of the surrounding rock in soft rock roof roadway are revealed, the surrounding rock control technology of presplitting and roof cutting pressure relief is proposed, and the key parameters of presplitting and roof cutting are systematically studied. According to the results, after mining, the overburden presents the distribution of “upper three zones,” in which the heights of the caving and fracture zones are 7 m and 38 m, respectively, the influence range of lateral mining abutment pressure is 80 m, and the influence height exceeds 42 m. The roadway is located in the same layer as the fracture zone and within the influence range of mining. Under the influence of overburden migration of the working face, the stress field around the roadway, and the mining stress field, the surrounding rock of the roof roadway is significantly damaged, and the floor heave is violent. Based on the stress distribution characteristics of the stope and the deformation mechanism of the roadway, the pressure relief control technology of surrounding rock presplitting roof cutting is proposed. The optimal values of key parameters are determined as the roof cutting height of 49.9 m, the roof cutting angle of 10°, and the blast hole spacing of 10 m. The results of this study have been successfully applied in 17191 (1) working face.

To study the evolution law of axial force and shear stress of a full-length anchorage bolt in a rectangular roadway during roadway driving and working face mining, based on the stress analysis of the bolt, considering the elastic parameters and geometric size of the bolt, the effect of a bearing plate on surrounding rock, roadway cross-section shape, roadway deformation degree, and roadway elastic parameters, elastic mechanics and mathematical analysis methods were used to establish the mechanical model describing the interaction between the bolt and surrounding rock, and the mechanical formulas for calculating the axial force and shear stress of the bolt were derived. Taking the mining roadway of 1,131(1) working face in the Zhujidong coal mine of the Huainan mining area as the engineering background, the axial force and shear stress of the bolt in the middle of the roof and side of the rectangular roadway with the advance of driving face and working face were analyzed. The mechanical model and theoretical analysis results are verified by installing force measuring bolts with the same mechanical properties as the field and observing the real axial force distribution of the bolts.

Intestinal bacterial flora plays an important role in the nutrition, physiology, and behavior of herbivorous insects. The composition of gut microbiota may also be affected by the food consumed. Cnaphalocrocis medinalis is an oligophagous pest, feeds on rice leaves almost exclusively and causes serious damage to rice in Asian countries. Using antibiotic treatment and metagenome sequencing, we investigated the influence of the food sources (rice and maize seedlings) on the structure and functions of intestinal bacteria of C. medinalis. Firstly, food utilization indices, relative growth rate (RGR), relative consumption rate (RCR), efficiency of conversion of ingested food (ECI), and efficiency of conversion of digested food (ECD), were all significantly adversely affected in the antibiotic treatment eliminating gut bacteria, showing that the microbiota loading in the gut were essential for the larva growth and development of C. medinalis. Further, metagenome sequencing revealed that different diets caused a variation in gut microbiota composition of C. medinalis, indicating that the gut microbiota were in part driven by the diet provided. However, the larvae of C. medinalis hosted a core microbial community in the gut, which was independent from the diets changing. The dominant bacteria in the two feeding groups were highly consistent in the gut of C. medinalis larvae, with the gut bacterial community dominated by Firmicutes at the phylum level, Enterococcus at the genus level, Enterococcus sp. FDAARGOS-375, E. casseliflavus, E. gallinarum, and E. sp. CR-Ec1 accounted for more than 96% of the gut microbiota. Functional prediction analysis demonstrated that gut bacteria encoded a series of metabolism-related enzymes involved in carbohydrate metabolism and amino acid synthesis. Carbohydrate metabolism was the most enriched function in both groups and was more abundant in rice feeding group than in maize feeding group. The core dominant Enterococcus species possessed complete pathways of 14 carbohydrates metabolism, 11 amino acids biosynthesis, and two vitamins synthesize, implied to contribute an essential role to the nutrition intake and development of C. medinalis. Finally, the study may provide an in-depth analysis of the symbiont-host co-adaptation and new insights into the management of C. medinalis.

The aim of this study was to explore the topological alterations of the brain functional network in type 2 diabetes mellitus (T2DM) patients with and without mild cognitive impairment (MCI) using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory approaches. In total, 27 T2DM patients with MCI, 27 T2DM patients without MCI, and 27 healthy controls (HCs) underwent rs-fMRI scanning. The whole-brain functional network was constructed by thresholding the Pearson’s correlation matrices of 90 brain regions. The topological organization of the constructed networks was analyzed by using graph theory approaches. The global and nodal properties of the participants in the three groups were compared by using one-way ANOVA as well as post hoc Tukey’s t-tests. The relationships between the altered topological properties and clinical features or scores of neuropsychological tests were analyzed in T2DM patients with MCI. At the global level, the global and local efficiency of the patients in the T2DM with MCI group were significantly higher than that of participants in the HCs group, and the length of the characteristic path was significantly lower than that of the participants in the HCs group (p < 0.05). No significant difference was found among the other groups. At the nodal level, when compared with T2DM patients without MCI, T2DM patients with MCI showed significantly increased nodal centrality in four brain regions, which were mainly located in the orbitofrontal lobe and anterior cingulate gyrus (ACG) (p < 0.05). No significant difference was found between the T2DM patients without MCI and HCs. Moreover, nodal degree related coefficient (r = −0381, p = 0.050) and nodal efficiency (r = −0.405, P = 0.036) of the ACG showed a significant closed correlation with the scores of the digit span backward test in the T2DM patients with MCI. Our results suggested that the increased nodal properties in brain regions of the orbitofrontal lobe and ACG were biomarkers of cognitive impairment in T2DM patients and could be used for its early diagnosis. The global topological alterations may be related to the combination of MCI and T2DM, rather than any of them.

PurposeTo investigate whether the combination of radiomics derived from brain high-resolution T1-weighted imaging and automatic machine learning could diagnose subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) accurately.MethodsA total of 116 right-handed participants involving 40 SIVCIND patients and 76 gender-, age-, and educational experience-matched normal controls (NM) were recruited. A total of 7,106 quantitative features from the bilateral thalamus, hippocampus, globus pallidus, amygdala, nucleus accumbens, putamen, caudate nucleus, and 148 areas of the cerebral cortex were automatically calculated from each subject. Six methods including least absolute shrinkage and selection operator (LASSO) were utilized to lessen the redundancy of features. Three supervised machine learning approaches of logistic regression (LR), random forest (RF), and support vector machine (SVM) employing 5-fold cross-validation were used to train and establish diagnosis models, and 10 times 10-fold cross-validation was used to evaluate the generalization performance of each model. Correlation analysis was performed between the optimal features and the neuropsychological scores of the SIVCIND patients.ResultsThirteen features from the right amygdala, right hippocampus, left caudate nucleus, left putamen, left thalamus, and bilateral nucleus accumbens were included in the optimal subset. Among all the three models, the RF produced the highest diagnostic performance with an area under the receiver operator characteristic curve (AUC) of 0.990 and an accuracy of 0.948. According to the correlation analysis, the radiomics features of the right amygdala, left caudate nucleus, left putamen, and left thalamus were found to be significantly correlated with the neuropsychological scores of the SIVCIND patients.ConclusionsThe combination of radiomics derived from brain high-resolution T1-weighted imaging and machine learning could diagnose SIVCIND accurately and automatically. The optimal radiomics features are mostly located in the right amygdala, left caudate nucleus, left putamen, and left thalamus, which might be new biomarkers of SIVCIND.

The aim of our study was to explore the dynamic functional alterations in the brain in patients with subjective cognitive decline (SCD) and their relationship to apolipoprotein E (APOE) €4 alleles. In total, 95 SCD patients and 49 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Then, the mean time series of 90 cortical or subcortical regions were extracted based on anatomical automatic labeling (AAL) atlas from the preprocessed rs-fMRI data. The static functional connectome (SFC) and dynamic functional connectome (DFC) were constructed and compared using graph theory methods and leading eigenvector dynamics analysis (LEiDA), respectively. The SCD group displayed a shorter lifetime (p = 0.003, false discovery rate corrected) and lower probability (p = 0.009, false discovery rate corrected) than the HC group in a characteristic dynamic functional network mainly involving the bilateral insular and temporal neocortex. No significant differences in the SFC were detected between the two groups. Moreover, the lower probability in the SCD group was found to be negatively correlated with the number of APOE ε4 alleles (r = −0.225, p = 0.041) in a partial correlation analysis with years of education as a covariate. Our results suggest that the DFC may be a more sensitive parameter than the SFC and can be used as a potential biomarker for the early detection of SCD.

Aiming at the problem of the deformation of the roadway floor plate during the laneway during the retention period, the mechanical model of the roadway floor is established, and the deformation characteristics of the roadway floor and the change law of the bottom drum are studied and analyzed through theoretical calculation and calculus simulation, revealing the instability mechanism of the surrounding rock of the roadway under the stress disturbance environment, and when not affected by the adoption, the roadway forms a certain stress concentration area within the effective range of support. During mining, under the comprehensive action of the original peripheral stress field and the mining stress field, the cliffhanger is unstable under the comprehensive action of the original peripheral stress field and the mining stress field, and the extrusion and stretching effect of the unflapped part of the rock layer above the goaf section of the coal seam is set up along the air, resulting in violent deformation such as the bottom drum, and the rotational sinking of this part of the unflinted rock layer further aggravates the transfer of the overburden load to the surrounding rock of the lane, so that the surrounding rock along the empty lane is subjected to a large additional stress, and the mining stress field plays a leading role, and the mining stress “far field” is the compound stress field, of which the tensile stress is the leading destructive factor. The deformation of the surrounding rock is mainly based on the bottom, and the horizontal stress on the bottom plate along the empty lane is mainly generated by the horizontal strain that occurs after the lower rock layer of the filling body and the coal gang is subjected to the supporting pressure transmitted by the top plate. With the mining of the working surface, the roof of the goaf area is broken and collapsed to form the characteristics of “vertical three belts,” which is affected by the “large support” of the coal body of the working surface and the “small support” of the surrounding rock along the empty roadway, and the pressure relief of the cut roof can make the roof plate along the empty lane change from the “long arm beam” structure when the roof is not cut into the “short arm beam” structure, blocking the lateral stress of the goaf area to the roof plate of the alley and significantly reducing the degree of stress superposition of the roof plate of the alley. The technical means of blasting cutting roof active pressure relief and protective lane are used to block the transmission of lateral support pressure, the roof slate layer is precracked in advance, the sinking of the rock layer is accelerated, the disturbance time is reduced, the vertical stress of the rock layer and the rock layer above it along the empty roadway is reduced, the vertical stress concentration of the roadway is reduced, the stress concentration coefficient is reduced, the degree of damage of the surrounding rock after the top is weakened, the damage range is reduced, and the technical problem of large deformation prevention and control along the bottom drum of the empty alley can be solved. Constructing the mechanical structure model of the top plate of the cut top pressure relief and the uncut top pressure relief along the empty lane, the stress change characteristics of the active protective rock surrounding rock along the hollow top of the cut top pressure relief were calculated, and after the technical scheme of the blasting cut top active pressure relief and protection lane was adopted, the deformation along the empty roadway was significantly weakened, the stability of the surrounding rock of the roadway after the blasting of the cut roof was significantly improved, the maintenance state along the section of the empty roadway was good, and the cross-sectional convergence rate was reduced by 37.3% compared with the original section. Cutting the roof active pressure relief and protective lane can effectively improve the stability of the surrounding rock.

The nondestructive testing technique used to evaluate the quality of bolt support by detecting the axial force is suitable for the bolt with a short construction time. For the bolt in the support state for a long time period, it may lead to the detection of small axial force only and ignore the fact that the bolt has entered the necking fracture stage, and thus fail to detect safety hazards in time. Three sets of parallel tests were conducted to solve the misjudgment of detection results due to the reduction of axial force when the bolt was in the necking fracture stage. Bolt deformation characteristics and stress wave propagation characteristics in bolts under axial tensile stress were studied by using the bolt tensile and stress wave detection test system which was modified and built independently. The results showed that (1) The diameter of the necking position decreases continuously during the tensioning process of the bolt and the rate of decrease increases abruptly during the necking fracture stage. (2) Due to the bolt stretching, the stress wave propagates in the bolt with different degrees of reflection and transmission, resulting in the attenuation of the stress wave energy; the energy attenuation ratio of the stress wave signal in the necking fracture stage reaches 35%, and the energy attenuation ratio increases exponentially as the necking continues to occur. (3) The frequency distribution of the stress wave signal during the bolt stretching process is from scattered to concentrated, the dominant frequency is gradually prominent and changes from low frequency to high frequency, the high-frequency signal is more sensitive to the cracks and necking of the bolt, and the dominant frequency is between 9500 and 10,000 Hz. (4) The average error of the stress wave method is 1.945% and the maximum and minimum values are 4.12% and 0.51%, respectively. The method is promising and provides a reference for the study of nondestructive testing of bolt stress waves in field support.

To determine the occurrence mechanism and mobility of shale oil in the Shahejie Formation in the Jiyang Depression, organic geochemistry analysis, thin-section petrological observation, low-temperature nitrogen adsorption, high-pressure mercury intrusion porosimetry, field emission scanning electron microscopy experiments were conducted on shale samples to reveal its storage mechanism, including pore size, ratio of adsorbed oil to free oil, mobility and its influencing factors, and mode of storage. Residual shale oil is mainly present in pores less than 100 nm in diameter under the atmospheric temperature and pressure. The lower limit of pore size for free oil is 5 nm, and the lower limit of pore size for movable oil occurrence is about 30 nm. The light components, low TOC and high porosity are the main factors contributing to the high proportion of movable oil. Each type of pore can contain residual shale oil, but not all pores have shale oil. Pore connectivity and surface wettability are the determinants of shale oil enrichment degree and enrichment state. Key words: shale oil, absorbed oil, free oil, occurrence mechanism, Paleogene Shahejie Formation, Jiyang Depression, Bohai Bay Basin

In order to solve the problems of the uneven deformation of Gangue Filled Wall and the difficulty of large-scale promotion of roadway side support, and to achieve the purposes of direct disposal of coal mine waste, reducing costs, and protecting the environment, the failure mechanics model of the bagged gangue was established, and the mechanical action relationship between longitudinal external load and transverse external load of gangue woven bag was deduced. Through the uniaxial compression test of large-scale flexible backfill (coal gangue of different particle sizes), it was obtained that when the strain is 0.2, the bearing capacity of particles with particle sizes between 0 and 10 mm is greater than 5 MPa, and when the strain is 1.27, the bearing capacity of particles with particle thicknesses between 10 and 20 mm is greater than 0 mpa, which meets the requirements of resistance value and resistance growth rate of gob side entry. In the “load deflection” test of backfill (gangue) samples, it was found that the maximum failure load of wet shotcrete is greater than that of dry shotcrete, and the wet shotcrete can withstand greater deformation under the same load conditions. Through the analysis of the experimental results of “flexural strength thickness” and “maximum failure load thickness”, it was finally determined that the thickness of the spray layer with good flexibility and sufficient support force is controlled at about 80 mm.

Rock burst occurs frequently as coal mining depth goes deeper, which seriously impacts the safety production of underground coal mines. Coal seam water injection is a technique commonly used to prevent and control such accidents. Moisture content is a critical factor tightly related to rock burst; however, an in-depth insight is required to discover their relationship. In this study, the influence of moisture content on the mechanical properties of coal and rock burst tendency is explored via multiple measurement techniques: uniaxial compression test, cyclic loading/unloading test, and acoustic emission (AE) test. These tests were performed on coal samples using the MTS-816 rock mechanics servo testing machine and AE system. The testing results showed that with the increase in moisture content, the peak strength and elastic modulus of each coal sample are reduced while the peak strain increases. The duration of the elastic deformation phase in the complete stress-strain curves of coal samples is shortened. As the moisture content increases, the area of hysteretic loop and elastic energy index WET of each coal sample are reduced, and the impact energy index KE is negatively correlated with the moisture content, whereas dynamic failure time is positively correlated with the moisture content, but this variation trend is gradually mitigated with the continuous increase of moisture content. The failure of the coal sample is accompanied by the sharp increase in the AE ring-down count, whose peak value lags behind the peak stress, and the ring-down count is still generated after the coal sample reached the peak stress. With the increase in moisture content, the failure mode of the coal sample is gradually inclined to tensile failure. The above test results manifested that the strength of the coal sample is weakened to some extent after holding moisture, the accumulative elastic energy is reduced in case of coal failure, and thus, coal and rock burst tendency can be alleviated. The study results can provide a theoretical reference for studying the fracture instability of moisture-bearing coal and prevention of coal and rock burst by the water injection technique.

To explore the microstructure evolution of oolitic hematite during microwave fluidization roasting, COMSOL multiphysics and scanning electron microscopy (SEM)–energy-dispersive spectrometry (EDS) were used to simulate and explore the microstructure evolution. The simulation results indicated that with the extension of microwave heating time and the increase of microwave power, the surface temperature in the particle model progressively increased, and the heating rate of hematite was the fastest, followed by quartz and apatite; simultaneously, the temperature stress and difference between the three mineral interfaces in the model were increased. The SEM–EDS results illustrated that there were microcracks at the interface between iron minerals and gangue minerals, such as quartz and apatite, and the microcracks were more obvious at the interface between iron minerals and quartz minerals. With the extension of microwave treatment time, the microcracks were gradually extended and expanded inward along the outer edge of oolitic and gradually formed in the core of the oolitic structure. Appropriately increasing the roasting temperature, prolonging the roasting time, and increasing the CO concentration made the particle surface more loose and rough, and produced more cracks and pores, while the ore surface presented a honeycomb morphology.

Background: Accurate diagnosis and timely treatment for posterior reversible encephalopathy syndrome (PRES) with atypical regions are very important in clinical practice. However, until now, little has been known about the clinical and MRI manifestations of this disease. Therefore, the aim of this study is to investigate the clinical and MRI features of PRES to promote clinical management and deepen our understanding of this disease.Materials and Methods: Data from six PRES patients with atypical regions were collected from our hospital. Data from another 550 cases were obtained by searching the PubMed, EMBASE and Web of Science databases with the keywords “posterior reversible encephalopathy syndrome” “PRES” “reversible posterior leukoencephalopathy” “RPLS” “hypertensive encephalopathy” “hyperperfusion encephalopathy” or “reversible posterior cerebral edema encephalopathy.” The clinical and MRI features of these 556 cases were analyzed together.Results: A total of 305 patients were female, and 248 were male, with a median age of 34 years. The information on sex and age of three patients was not available. The most common symptom was headache (282/556, 50.7%), followed by altered mental status (243/556, 43.7%), seizures (233/556, 41.9%), visual disturbances (194/556, 34.9%), nausea/vomiting (130/556, 23.4%), and focal neurological deficits (101/556, 18.2%). Hypertension (425/556, 76.4%), renal diseases (152/556, 27.3%), immunosuppressant drugs (79/556, 14.2%), and chemotherapy/chemoradiotherapy (59/556, 10.6%) were the major predisposing factors. The atypical regions of the lesions were the cerebellum (331/556, 59.5%), basal ganglia (135/556, 24.3%), periventricular/deep white matter (125/556, 22.5%), pons (124/556, 22.3%), brainstem (115/556, 20.7%), thalamus (114/556, 20.5%), midbrain (48/556, 8.6%), spinal cord (33/556, 5.9%), and medulla (29/556, 5.2%). Additionally, the following typical regions were observed: occipital (278/556, 50.0%), parietal (234/556, 42.1%), frontal (150/556, 27.0%), and temporal (124/556, 22.3%) lobes. The major treatments were antihypertensives (358/515, 69.5%), antiepileptics/sedation (126/515, 24.5%), discontinuation/switching agents (67/515, 13.0%), and steroids (54/515, 10.5%). The median time of the clinical state improved and abnormal neuroimaging resolved is 2–3 weeks after appropriate treatment.Conclusion: The common symptoms of PRES with atypical regions include headaches, altered mental status, seizures, visual disturbances, nausea or vomiting, and focal neurological deficits. The frequent predisposing factors include hypertension, renal diseases, immunosuppressant drugs and chemotherapy/chemoradiotherapy. MRI features are mainly characterized by vasogenic edema in central zones always accompanied by typical regions. Most cases can be reversed in 2–3 weeks when promptly recognized and properly treated.

The moisture content is a critical factor tightly related to rock deformation and its failure process since it leads to a significant change in the physicomechanical properties of rock during the underground engineering construction. As a result, engineering construction accidents take place frequently. To figure out the influence of the moisture content on the physicomechanical properties of water-bearing rock and then effectively avoid engineering accidents, multiple tests including the uniaxial compression test, Brazilian splitting test, and the acoustic emission (AE) test were carried out in this study. The experimental results showed that the water absorption rate of the sandstone gradually stabilizes after 5 h, and its uniaxial compressive strength, tensile strength, and elastic modulus all decline with the increase of the moisture content. Compared to the dry state of the sample, the reduction amplitudes of the elastic modulus, compressive strength, and tensile strength of water-saturated rock samples can reach up to 27.3%, 35.2%, and 38.1%, respectively. It indicates that the tensile strength is more sensitive to the softening effect of the moisture. Through the AE test, it can be found that the internal state of water-saturated rock samples is greatly changed; the compressive strength of rock samples drops, so the rock can be damaged after absorbing less energy. Thus, moisture shows a certain softening effect on rock. The research results are expected to provide a basis for underground engineering construction and rock fracture and failure.

The alteration of the functional topological organization in subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND) patients has been illuminated by previous neuroimaging studies. However, in regard to the changes in the structural connectivity of brain networks, little has been reported. In this study, a total of 27 subjects, consisting of 13 SIVCIND patients, and 14 normal controls, were recruited. Each of the structural connectivity networks was constructed by diffusion tensor tractography. Subsequently, graph theory, and network-based statistics (NBS) were employed to analyze the whole-brain mean factional anisotropy matrix. After removing the factor of age, gender, and duration of formal education, the clustering coefficients (Cp) and global efficiency (Eglob) were significantly decreased and the mean path length (Lp) was significantly increased in SIVCIND patients compared with normal controls. Using the combination of four network topological parameters as the classification feature, a classification accuracy of 78% was obtained by leave-one-out cross-validation for all subjects with a sensitivity of 69% and a specificity of 86%. Moreover, we also found decreased structural connections in the SIVCIND patients, which mainly concerned fronto-occipital, fronto-subcortical, and tempo-occipital connections (NBS corrected, p < 0.01). Additionally, significantly altered nodal centralities were found in several brain regions of the SIVCIND patients, mainly located in the prefrontal, subcortical, and temporal cortices. These results suggest that cognitive impairment in SIVCIND patients is associated with disrupted topological organization and provide structural evidence for developing reliable biomarkers related to cognitive decline in SIVCIND.

Purpose: To investigate whether a combination of radiomics and automatic machine learning applied to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of primary breast cancer can non-invasively predict axillary sentinel lymph node (SLN) metastasis.Methods: 62 patients who received a DCE-MRI breast scan were enrolled. Tumor resection and sentinel lymph node (SLN) biopsy were performed within 1 week after the DCE-MRI examination. According to the time signal intensity curve, the volumes of interest (VOIs) were delineated on the whole tumor in the images with the strongest enhanced phase. Datasets were randomly divided into two sets including a training set (~80%) and a validation set (~20%). A total of 1,409 quantitative imaging features were extracted from each VOI. The select K best and least absolute shrinkage and selection operator (Lasso) were used to obtain the optimal features. Three classification models based on the logistic regression (LR), XGboost, and support vector machine (SVM) classifiers were constructed. Receiver Operating Curve (ROC) analysis was used to analyze the prediction performance of the models. Both feature selection and models construction were firstly performed in the training set, then were further tested in the validation set by the same thresholds.Results: There is no significant difference between all clinical and pathological variables in breast cancer patients with and without SLN metastasis (P > 0.05), except histological grade (P = 0.03). Six features were obtained as optimal features for models construction. In the validation set, with respect to the accuracy and MSE, the SVM demonstrated the highest performance, with an accuracy, AUC, sensitivity (for positive SLN), specificity (for positive SLN) and Mean Squared Error (MSE) of 0.85, 0.83, 0.71, 1, 0.26, respectively.Conclusions: We demonstrated the feasibility of combining artificial intelligence and radiomics from DCE-MRI of primary tumors to predict axillary SLN metastasis in breast cancer. This non-invasive approach could be very promising in application.

Purpose: Depression is common in Parkinson's disease (PD) and is correlated with the severity of motor deficits and quality of life. The present study aimed to investigate alterations in the structural brain network related to depression in Parkinson's disease (d-PD) and their correlations with structural impairments of white matter (WM).Materials and Methods: Data were acquired from the Parkinson Progression Markers Initiative (PPMI) database. A total of 84 de novo and drug-naïve PD patients were screened and classified into two groups according to the 15-item Geriatric Depression Scale (GDS-15): d-PD (n = 28) and nondepression in PD (nd-PD, n = 56). Additionally, 37 healthy controls (HC) were screened. All subjects underwent DTI and 3D-T1WI on a 3.0 T MR scanner. Individual structural brain networks were constructed and analyses were performed using graph theory and network-based statistics (NBS) at both global and local levels. Differences in global topological properties were explored among the three groups. The association models between node and edge changes and the GDS-15 were constructed to detect regions that were specifically correlated with d-PD. Tract-based spatial statistics (TBSS) was used to detect structural impairments of WM between the d-PD and nd-PD groups. The correlations between altered global topological properties and structural impairments were analyzed in the d-PD group.Results: The global efficiency and characteristic path length of the structural brain network were impaired in the d-PD group compared with those in the nd-PD and HC groups. Thirteen nodes and 1 subnetwork with 10 nodes and 12 edges specifically correlated with d-PD were detected. The left hippocampus, left parahippocampal, left lingual, left middle occipital, left inferior occipital, left fusiform, left middle temporal, and left inferior temporal regions were all involved in the results of node and edge analysis. No WM microstructural impairments were identified in the d-PD group.Conclusion: Our study suggests that the integration of the structural brain network is impaired with disrupted connectivity of limbic system and visual system in the de novo and drug-naïve d-PD patients.The topological properties assessing integration of the structural brain network can serve as a potential objective neuroimaging marker for early diagnosis of d-PD.

Cognitive impairment caused by subcortical ischemic vascular disease (SIVD) has been elucidated by many neuroimaging studies. However, little is known regarding the changes in brain functional connectivity networks in relation to the severity of cognitive impairment in SIVD. In the present study, 20 subcortical ischemic vascular cognitive impairment no dementia patients (SIVCIND) and 20 dementia patients (SIVaD) were enrolled; additionally, 19 normal controls were recruited. Each participant underwent a resting-state functional MRI scan. Whole-brain functional networks were analyzed with graph theory and network-based statistics (NBS) to study the functional organization of networks and find alterations in functional connectivity among brain regions. After adjustments for age, gender, and duration of formal education, there were significant group differences for two network functional organization indices, global efficiency and local efficiency, which decreased (NC > SIVCIND > SIVaD) as cognitive impairment worsened. Between-group differences in functional connectivity (NBS corrected, p

Cnaphalocrocis medinalis is a major pest of rice in South and South-East Asia. Insecticides are the major means farmers use for management. A naturally occurring baculovirus, C. medinalis granulovirus (CnmeGV), has been isolated from the larvae and this has the potential for use as microbial agent. Here, we described the complete genome sequence of CnmeGV and compared it to other baculovirus genomes. The genome of CnmeGV is 112,060 base pairs in length, has a G+C content of 35.2%. It contains 133 putative open reading frames (ORFs) of at least 150 nucleotides. A hundred and one (101) of these ORFs are homologous to other baculovirus genes including 37 baculovirus core genes. Thirty-two (32) ORFs are unique to CnmeGV with no homologues detected in the GeneBank and 53 tandem repeats (TRs) with sequence length from 25 to 551 nt intersperse throughout the genome of CnmeGV. Six (6) homologous regions (hrs) were identified interspersed throughout the genome. Hr2 contains 11 imperfect palindromes and a high content of AT sequence (about 73%). The unique ORF28 contains a coiled-coil region and a zinc finger-like domain of 4-50 residues specialized by two C2C2 zinc finger motifs that putatively bound two atoms of zinc. ORF21 encoding a chit-1 protein suggesting a horizontal gene transfer from alphabaculovirus. The putative protein presents two carbohydrate-binding module family 14 (CBM_14) domains rather than other homologues detected from betabaculovirus that only contains one chit-binding region. Gene synteny maps showed the colinearity of sequenced betabaculovirus. Phylogenetic analysis indicated that CnmeGV grouped in the betabaculovirus, with a close relation to AdorGV. The cladogram obtained in this work grouped the 17 complete GV genomes in one monophyletic clade. CnmeGV represents a new crambidae host-isolated virus species from the genus Betabaculovirus and is most closely relative of AdorGV. The analyses and information derived from this study will provide a better understanding of the pathological symptoms caused by this virus and its potential use as a microbial pesticide.

Purpose: To detect the functional deficit of the visual cortex in anisometropic amblyopia children using functional magnetic resonance imaging (fMRI) technique, and investigate the relationship between visual acuity and visual cortex function.Methods: Blood oxygenation level-dependent fMRI (BOLD-fMRI) was performed in ten monocular anisometropic amblyopia children and ten normal controls. fMRI images were acquired in two runs with visual stimulation delivered separately through the sound and amblyopic eyes. Measurements were performed in cortical activation of striate and extrastriate areas at the occipital lobe. The relationship between cortex function and visual acuity was analyzed by Pearson partial analysis.Results: The activation areas of both the striate and extrastriate cortices in the amblyopic eyes were significantly lower than that of the sound fellow eyes. No relationship was found between the striate and extrastriate cortex activation. No relationship was found between the visual cortical activation of striate, extrastriate areas and visual acuity of anisometropic amblyopes.Conclusions: BOLD-fMRI revealed the independent striate and extrastriate cortical deficits in anisometropic amblyopes. In addition, the visual acuity lesion and the striate and extrastriate cortical deficits were not parallel, and results of fMRI examination have much potential value in the evaluation of amblyopia.

BACKGROUND AND PURPOSE: The present study was designed to detect the abnormalities of the cerebral grey-matter density in subcortical ischemic vascular dementia patients by FSL-VBM method to promote the early diagnosis of it.METHODS: Nine subcortical ischemic vascular dementia patients and nine age-matched normal controls underwent MRI brain structure scanning that was performed on a SIEMENS AVANTO 1.5 Tesla scanner and standard T1-weighted high-resolution anatomic scans of MPRAGE sequence were obtained. The 3-demensional MPRAGE images were processed with FSL-VBM package and the cerebral gray matter density was compared between the subcortical ischemic vascular dementia patients and normal controls.RESULTS: Compared with the normal control group, the cerebral gray matter density of subcortical ischemic vascular dementia patients was found significantly decreasing, including brain regions of thalamus, parietal lobe, frontal lobe and temporal lobe (PCONCLUSIONS: The cerebral gray matter density alterations have closed correlation with cognitive dysfunction in subcortical ischemic vascular dementia patient and can be detected by MRI. MRI has some potential value in the diagnosis of them.

Accumulating evidence has indicated that amputation induces functional reorganization in the sensory and motor cortices. However, the extent of structural changes after lower limb amputation in patients without phantom pain remains uncertain. We studied 17 adult patients with right lower limb amputation and 18 healthy control subjects using T1-weighted magnetic resonance imaging and diffusion tensor imaging. Cortical thickness and fractional anisotropy (FA) of white matter (WM) were investigated. In amputees, a thinning trend was seen in the left premotor cortex (PMC). Smaller clusters were also noted in the visual-to-motor regions. In addition, the amputees also exhibited a decreased FA in the right superior corona radiata and WM regions underlying the right temporal lobe and left PMC. Fiber tractography from these WM regions showed microstructural changes in the commissural fibers connecting the bilateral premotor cortices, compatible with the hypothesis that amputation can lead to a change in interhemispheric interactions. Finally, the lower limb amputees also displayed significant FA reduction in the right inferior frontooccipital fasciculus, which is negatively correlated with the time since amputation. In conclusion, our findings indicate that the amputation of lower limb could induce changes in the cortical representation of the missing limb and the underlying WM connections.

The stress-dependent permeability of coal during coalbed methane production has been extensively studied both experimentally and theoretically. However, how permeability changes as a function of stress variation is somewhat unclear to date, and currently used analytical models fail to accurately predict permeability evolution with gas depletion. Considering that the role played by changes in in situ stress in permeability evolution is critical, a comprehensive theoretical study was first conducted, through which it was found that coal permeability is determined by mean effective stress. Moreover, the influence of matrix shrinkage on cleat deformation and then coal permeability was overestimated by currently used models, leading to inaccuracy of the predicted permeability. By taking both mean effective stress and the influence of matrix shrinkage on cleat deformation into account, a new permeability model was developed under the uniaxial strain condition in order to precisely estimate permeability evolution during gas depletion. An in-depth investigation and comparison among four commonly-used permeability models, the Palmer and Mansoori (P&M) model, Improved P&M model, Shi and Durucan (S&D) model, and Cui and Bustin (C&B) model, was then conducted. It was experimentally verified that a good match can be achieved between the lab data and the results predicted by the proposed model. Permeability variation of coalbed reservoirs associated with gas depletion is a consequence of two opposing effects: mechanical compaction and matrix shrinkage. In comparison, it was found that the coefficients of these two effects incorporated in those four models have a significant impact on permeability variation; and the accuracy of the values of initial cleat porosity and cleat compressibility, the bridges connecting permeability, and those two effects in analytical models, is extremely critical to permeability estimations. This study can shed light on improving the accuracy of analytical coal permeability models and the prediction of gas production.

Binswanger's disease (BD) is a common cause of vascular dementia in elderly patients; however, few studies have investigated the medial temporal lobe (MTL) atrophy in BD, and the differences in the atrophic patterns between BD and Alzheimer's disease (AD) remain largely unknown. Such knowledge is essential for understanding the pathologic basis of dementia. In this study, we collected structural magnetic resonance imaging (MRI) data from 16 normal controls, 14 patients with AD and 14 patients with BD. The volumes of the hippocampus and amygdala, and morphologic parameters (volume, surface area, cortical thickness and mean curvature) of the entorhinal cortex (ERC) and perirhinal cortex (PRC) were calculated using an automated approach. Volume reduction of the hippocampus, amygdala and ERC, and disturbance of the PRC curvature was found in both AD and BD patients compared with the controls (p

BACKGROUND: Accurate detection and determination of axillary lymph node metastasis are crucial for the clinical management of patients with breast cancer. Noninvasive imaging methods including ultrasound (US), computed tomography (CT), or conventional magnetic resonance imaging (MRI) are not yet accurate enough. The purpose of this study was to investigate the value of in vivo T2* in differentiating metastatic from benign axillary lymph nodes in patients with breast cancer. METHODOLOGY/PRINCIPAL FINDINGS: In this institutional review board approved study, 35 women with breast cancer underwent multi-echo T2* weighted imaging (T2*WI) of the axillary area on a 3.0 T clinical magnetic resonance (MR) imaging system. T2* values of pathologically proven benign and metastatic axillary lymph nodes were calculated and compared. Receiver operating characteristics (ROC) analysis was conducted to evaluate the diagnostic ability. The areas under the ROC curve (AUCs) and the confidence intervals (CIs) were assessed. In total, 56 metastatic and 65 benign axillary lymph nodes were identified in this study. For metastatic lymph nodes, the average T2* value (55.96±11.87 ms) was significantly longer than that of the benign lymph nodes (26.00±5.51 ms, P

OBJECTIVES: To investigate the amplitude of low-frequency fluctuations (ALFF) alteration of whole brain in patients with subcortical ischemic vascular dementia (SIVD). MATERIALS AND METHODS: Thirty patients with SIVD and 35 control subjects were included in this study. All of them underwent structural MRI and rs-fMRI scan. The structural data were processed using the voxel-based morphometry 8 toolbox (VBM8). The rs-fMRI data were processed using Statistical Parametric Mapping (SPM8) and Data Processing Assistant for Resting-State fMRI (DPARSF) software. Within-group analysis was performed with a one-sample Student's t-test to identify brain regions with ALFF value larger than the mean. Intergroup analysis was performed with a two-sample Student's t-test to identify ALFF differences of whole brain between SIVD and control subjects. Partial correlations between ALFF values and Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) scores were analyzed in the SIVD group across the parameters of age, gender, years of education, and GM volume. RESULTS: Within-group analysis showed that the bilateral anterior cingulate cortex (ACC), posterior cingulate cortex, medial prefrontal cortex (MPFC), inferior parietal lobe (IPL), occipital lobe, and adjacent precuneus had significantly higher standardized ALFF values than the global mean ALFF value in both groups. Compared to the controls, patients with SIVD presented lower ALFF values in the bilateral precuneus and higher ALFF values in the bilateral ACC, left insula and hippocampus. Including GM volume as an extra covariate, the ALFF inter-group difference exhibited highly similar spatial patterns to those without GM volume correcting. Close negative correlations were found between the ALFF values of left insula and the MoCA and MMSE scores of SIVD patients. CONCLUSION: SIVD is associated with a unique spontaneous aberrant activity of rs-fMRI signals, and measurement of ALFF in the precuneus, ACC, insula, and hippocampus may aid in the detection of SIVD.

BACKGROUND: Susceptibility-weighted imaging (SWI) has been proven to be superior to T2*-weighted imaging and also other existing magnetic resonance imaging (MRI) techniques for the detection of iron content and hemorrhage in the brain. The purpose of this study was to compare SWI with T1WI, T2WI and T2*WI in detecting splenic siderotic lesions. METHODOLOGY/PRINCIPAL FINDINGS: Twenty-two patients with splenic siderotic nodule were imaged with non-contrast MRI T1WI, T2WI, T2*WI and SWI at 3.0 Tesla. Imaging data were independently analyzed by two experienced radiologists. The number of splenic siderotic nodules was counted, and the size (largest diameter) was measured. The conspicuity was calculated as the nodule to background parenchyma intensity ratio. We found that SWI detected a larger average number of splenic siderotic nodules than T1WI, T2WI, or T2*WI (all P