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Abstract Background Ovarian cancer (OC) typically develops an immunosuppressive microenvironment by funtional changes of host immune cells. Dysregulated m6A level is associated with cancer progression via the intrinsic oncogenic pathways. However, the role of m6A in regulating host immune cell function during anti-tumor immunity needs comprehensive analysis. This study aimed to investigate the role of METTL3, a catalytic subunit of the methyltransferase complex, in regulating host immune cell response against OC. Methods In this study, myeloid-specific Mettl3 gene knockout (Mettl3-cKO) mice were bred using the Cre-LoxP system. Intraperitoneally injection of ID8 cells was used as a syngeneic OC model. Furthermore, the compositions of immune cell populations were analyzed by flow cytometry and single-cell sequencing. Moreover, chemokines and cytokines secretion were assessed using ELISA. Lastly, the role of METTL3 in regulating IL-1β secretion and inflammasome activation in bone marrow-derived macrophages cocultured with ID8 cells was specified by ELISA and immunoblotting. Results It was revealed that OC cell growth was enhanced in Mettl3-cKO mice. Furthermore, a shift of decreased M1 to increased M2 macrophage polarization was observed during OC progression. Moreover, Mettl3 depletion in myeloid lineage cells increased secretion of CCL2 and CXCL2 in peritoneal lavage fluild. Interestingly, Mettl3 deficiency enhanced IL-1β secretion induced by viable ID8 cells independent of inflammasome activation and cell death. Therefore, OC cells in tumor-bearing mice trigger a slight inflammatory response with a low-to-moderate secretion of pro-inflammatory cytokines and chemokines. Conclusion This study provides new insights into METTL3-mediated m6A methylation, which regulates host immune response against OC.

As a unique geological hazard in a high-geo-stress environment, rockburst happens with strong suddenness, randomness, and destructiveness, but the mechanism of its occurrence in a deep-buried tunnel in a high-geo-stress environment needs further study. Based on the analyses of the stress field of the rockburst section of Ping’an Tunnel, which is over-long and deep-buried, the occurrence mechanism of rockburst is figured out. Furtherly, the intensity and location of rockburst are predicted by using the rockburst criterion. Results show that there exists large compressive stress at the side wall of the tunnel, which is the main cause of rockburst. Under a high-geo-stress condition, due to the existence of unfavorable factors like structural planes, high intensity rockburst is likely to happen in the middle of the tunnel face after the sudden release of original rock stress. Arranging stress-releasing holes in the rockburst section can effectively reduce the possibility of rockburst by releasing the original rock stress in advance. The research results can deepen the understanding of the mechanism of rockburst in a high-geo-stress environment and provide scientific basis for the prevention and control of rockburst in similar engineering projects.

To study the potential disasters caused by tunnels crossing water-abundant fault areas, this study takes the Jinyunshan Tunnel as an example, and studies the groundwater flow law between different rock layers, the interaction between surrounding rock hydrostatic pressure and soil pressure, and the mechanical features and safety of the lining during construction by combining field tests and finite element simulation analysis. The results show that the displacement change rate of the tunnel vault reaches 2.8 mm/d, and the maximum earth pressure and hydrostatic pressure are 2.3 MPa and 1.15 MPa, respectively, both at the bottom of the tunnel in section II. When the tunnel enters the fault fracture zone from the V surrounding rock, the bending moment of the lining increases by 222.78% at the left haunch and 60.87% at the bottom of the right wall. The axial force of the right spandrel increases by 2579.2%, and the left spandrel increases by 221.18%. The safety factor of the two sections is greater than 2.4, indicating that the overall structure is in a safe state, but the safety factor of the second right shoulder is 2.54, which is close to the safety threshold of 2.4. The research results provide a basis for the safety design and construction safety of tunnels through water-rich sections in similar fault fracture zones, and provide a reference for reducing groundwater loss and protecting ecological vegetation.

Constructing a tunnel with a large longitudinal slope and a small-radius sharp curve is challenging. During the construction process, it necessitates a series of intricate operations, including adjusting the horizontal and vertical posture of the shield machine, controlling the tunnelling thrust, and consistently ensuring the appropriate over-excavation amount inside and outside of the turn. Improper operations can easily induce undue stress on the segments. This study establishes a finite element numerical model of lining segments subjected to jacking force under various construction conditions. The concrete damage plasticity (CDP) constitutive model was used to characterize the mechanical behavior of concrete under load. The mechanical characteristics and damage behavior of segments under construction conditions, such as significant thrust escape, vertical attitude adjustment of the shield machine, excavation in soft and hard interbedded strata, line turning, sudden failure of the propulsion system, and eccentricity of brace boots, were analyzed. The results revealed that, when advancing according to the maximum thrust design value (50 MPa), cracks in the tensile plastic damage zone near the brace boot plate and the edges of the segment can develop. This can lead to localized corner failure of the concrete at the lining’s edge. Therefore, it is recommended that the jack’s thrust value should not surpass 30 MPa. Maintaining the usual uneven jack thrust state of shield tunnelling along the design axis is unlikely to result in segment concrete cracking. Damage to the segment caused by the eccentricity of the brace boot plate is the most severe; hence, avoiding the eccentricity of the brace boot plate during construction is crucial. The findings of this research can guide the control of jack thrust during shield tunnelling construction and offer insights into the design of segment parameters.

This research paper systematically investigates the combined influence of fly ash, cementitious capillary crystalline waterproofing (CCCW) materials, and polypropylene fibers on the mechanical properties and impermeability of concrete through comprehensive orthogonal tests. Microscopic morphological changes in the concrete induced by different composite materials are examined via scanning electron microscopy (SEM) and X-ray diffraction (XRD) testing. The objective is to facilitate a beneficial synergetic interaction among these materials to develop highly permeable, crack-resistant concrete. Key findings of this study are: (1) The study unveils the impact of the concentration of three additive materials on the concrete’s compressive strength, tensile strength, and penetration height, thereby outlining their significant influence on the mechanical properties and impermeability of the concrete; (2) An integrated scoring method determined the optimal composite dosage of three materials: 15% fly ash, 2% CCCW, and polypropylene fibers at 1.5 kg/m3. This combination increased the concrete’s compressive strength by 12.5%, tensile strength by 48.4%, and decreased the average permeability height by 63.6%; (3) The collective introduction of these three materials notably augments the hydration reaction of the cement, resulting in denser concrete microstructure, enhanced bonding between fibers and matrix, and improved concrete strength and durability.

IntroductionPanum’s limiting case is one of the typical configurations of monocular occlusion region. The matching rule of Panum’s limiting case is the key to understanding how monocular occlusion region produces stereopsis. There are currently two main views on the matching rule of Panum’s limiting case, namely double fusion and uniqueness constraint. This paper further discusses its matching mechanism on the basis of previous studies.MethodsIn this study, fold line Panum’s stimuli were used to study the matching rule of Panum’s limiting case. In Experiment 1, fixation position was adopted to present the stimulus in a short time to explore the matching rules in Panum’s limiting case. In Experiment 2, the effect of fixation position on Panum’s limiting case matching results was further investigated.ResultsThe results of Experiment 1 show that when stimuli are presented in a short period of time, the reported result that a single feature in one eye may be matched alternately with two features in the other eye. This matching rule is called “fast alternative matching” in this article. The results of Experiment 2 results show that the position of the fixation could affect the matching result of participants.ConclusionIn conclusion, the matching rule of Panum’s limiting case is fast alternative matching, and the matching result is related to the attention state of the participant. These results not only provide a new perspective for matching rules in Panum’s limiting case, but also show that depth perception results in stereopsis can be influenced by top-down cognitive processing. This study provides a theoretical basis for studying the formation of stereopsis in the monocular region to a certain extent. In summary, the matching rule of Panum’s limiting case is fast alternative matching. In previous studies, the perceived result of double fusion may be caused by fast alternative matching. Also, the matching results are related to the participant’s state of attention, which suggests that the depth perception results of stereopsis are influenced by top-down cognitive processing.

Growing evidences indicate that age plays an important role in the development of mental disorders, but few studies focus on the neuro mechanisms of generalized anxiety disorder (GAD) in different age groups. Therefore, this study attempts to reveal the neurodynamics of Young_GAD (patients with GAD under the age of 50) and Old_GAD (patients with GAD over 50 years old) through statistical analysis of multidimensional electroencephalogram (EEG) features and machine learning models. In this study, 10-min resting-state EEG data were collected from 45 Old_GAD and 33 Young_GAD. And multidimensional EEG features were extracted, including absolute power (AP), fuzzy entropy (FE), and phase-lag-index (PLI), on which comparison and analyses were performed later. The results showed that Old_GAD exhibited higher power spectral density (PSD) value and FE value in beta rhythm compared to theta, alpha1, and alpha2 rhythms, and functional connectivity (FC) also demonstrated significant reorganization of brain function in beta rhythm. In addition, the accuracy of machine learning classification between Old_GAD and Young_GAD was 99.67%, further proving the feasibility of classifying GAD patients by age. The above findings provide an objective basis in the field of EEG for the age-specific diagnosis and treatment of GAD.

Abstract Objectives In this study, we aimed to investigate the spontaneous neural activity in the conventional frequency band (0.01−0.08 Hz) and two sub-frequency bands (slow-4: 0.027–0.073 Hz, and slow-5: 0.01–0.027 Hz) in tension-type headache (TTH) patients with regional homogeneity (ReHo) analyses. Methods Thirty-eight TTH patients and thirty-eight healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (RS-fMRI) scanning to investigate abnormal spontaneous neural activity using ReHo analysis in conventional frequency band (0.01−0.08 Hz) and two sub-frequency bands (slow-4: 0.027–0.073 Hz and slow-5: 0.01–0.027 Hz). Results In comparison with the HC group, patients with TTH exhibited ReHo increases in the right medial superior frontal gyrus in the conventional frequency band (0.01−0.08 Hz). The between group differences in the slow-5 band (0.01–0.027 Hz) highly resembled the differences in the conventional frequency band (0.01−0.08 Hz); even the voxels with increased ReHo were spatially more extensive, including the right medial superior frontal gyrus and the middle frontal gyrus. In contrast, no region showed significant between-group differences in the slow-4 band (0.027–0.073 Hz). The correlation analyses showed no correlation between the ReHo values in TTH patients and VAS scores, course of disease and number of seizures per month in conventional band (0.01−0.08 Hz), slow-4 band (0.027–0.073 Hz), as well as in slow-5 band (0.01–0.027 Hz). Conclusions The results showed that the superior frontal gyrus and middle frontal gyrus were involved in the integration and processing of pain signals. In addition, the abnormal spontaneous neural activity in TTH patients was frequency-specific. Namely, slow-5 band (0.01–0.027 Hz) might contain additional useful information in comparison to slow-4 band (0.027−0.073 Hz). This preliminary exploration might provide an objective imaging basis for the understanding of the pathophysiological mechanism of TTH.

BackgroundMyotonic dystrophy type 1 (DM1) is the most common and dominant inherited neuromuscular dystrophy disease in adults, involving multiple organs, including the brain. Although structural measurements showed that DM1 is predominantly associated with white-matter damage, they failed to reveal the dysfunction of the white-matter. Recent studies have demonstrated that the functional activity of white-matter is of great significance and has given us insights into revealing the mechanisms of brain disorders.Materials and methodsUsing resting-state fMRI data, we adopted a clustering analysis to identify the white-matter functional networks and calculated functional connectivity between these networks in 16 DM1 patients and 18 healthy controls (HCs). A two-sample t-test was conducted between the two groups. Partial correlation analyzes were performed between the altered white-matter FC and clinical MMSE or HAMD scores.ResultsWe identified 13 white-matter functional networks by clustering analysis. These white-matter functional networks can be divided into a three-layer network (superficial, middle, and deep) according to their spatial distribution. Compared to HCs, DM1 patients showed increased FC within intra-layer white-matter and inter-layer white-matter networks. For intra-layer networks, the increased FC was mainly located in the inferior longitudinal fasciculus, prefrontal cortex, and corpus callosum networks. For inter-layer networks, the increased FC of DM1 patients is mainly located in the superior corona radiata and deep networks.ConclusionResults demonstrated the abnormalities of white-matter functional connectivity in DM1 located in both intra-layer and inter-layer white-matter networks and suggested that the pathophysiology mechanism of DM1 may be related to the white-matter functional dysconnectivity. Furthermore, it may facilitate the treatment development of DM1.

Social function impairment is the core deficit of autism spectrum disorder (ASD). Although many studies have investigated ASD through a variety of neuroimaging tools, its brain mechanism of social function remains unclear due to its complex and heterogeneous symptoms. The present study aimed to use resting-state functional magnetic imaging data to explore effective connectivity between the right temporoparietal junction (RTPJ), one of the key brain regions associated with social impairment of individuals with ASD, and the whole brain to further deepen our understanding of the neuropathological mechanism of ASD. This study involved 1,454 participants from 23 sites from the Autism Brain Imaging Data Exchange (ABIDE) public dataset, which included 618 individuals with ASD and 836 with typical development (TD). First, a voxel-wise Granger causality analysis (GCA) was conducted with the RTPJ selected as the region of interest (ROI) to investigate the differences in effective connectivity between the ASD and TD groups in every site. Next, to obtain further accurate and representative results, an image-based meta-analysis was implemented to further analyze the GCA results of each site. Our results demonstrated abnormal causal connectivity between the RTPJ and the widely distributed brain regions and that the connectivity has been associated with social impairment in individuals with ASD. The current study could help to further elucidate the pathological mechanisms of ASD and provides a new perspective for future research.

As a new type of pre-reinforcement material for tunnel faces, glass fiber-reinforced polymer (GFRP) bolts can effectively and safely improve the stability of tunnel faces in soft surrounding rocks and speed up excavation. Therefore, in this paper, systematic research is carried out on the bond strength of GFRP bolts in tunnel faces and their relative pre-reinforcement parameters. Firstly, the effects of rebar diameter, anchorage length, and mortar strength on the bonding properties of GFRP bars were studied by indoor pull-out tests. The bond strength–slip curves under different working conditions were obtained, and the curves showed that the ultimate bond strength between GFRP bars and mortar was negatively correlated with the diameter of GFRP bars but positively correlated with the strength of the mortar. In addition, the increase in anchorage length led to a reduction in bonding strength. Secondly, inverse analysis was used to analyse the mechanical parameters of the bond performance of the anchor bars by the finite difference software FLAC3D, and the results indicated that 1/5 of the compressive strength of the GFRP bar grouting body can be taken as the ultimate bond strength to calculate the cohesive strength of the grout. Additionally, the formula of GFRP bar grouting body stiffness was revised. Finally, based on the results of laboratory tests and the inverse analysis, the numerical simulation analysis results showed that the optimal reinforcement configuration for a shallow buried tunnel face surrounded by weak rock is to use GFRP bars with a length of 17 m arranged in the center circle of the tunnel face with a reasonable reinforcement density of 1.0 bolt/m2. The calculation formula of the stiffness and cohesion strength of the GFRP bar grouting body and the reinforcement scheme proposed in this paper can provide a reference for the construction of shallowly buried rock tunnels in soft surrounding rock.

Depression has become one of the most common mental illnesses, causing serious physical and mental harm. However, there remain unclear and uniform physiological indicators to support the diagnosis of clinical depression. This study aimed to use machine learning techniques to investigate the abnormal multidimensional EEG features in patients with depression. Resting-state EEG signals were recorded from 41 patients with depression and 34 healthy controls. Multiple dimensional characteristics were extracted, including power spectral density (PSD), fuzzy entropy (FE), and phase lag index (PLI). These three different dimensional characteristics with statistical differences between two groups were ranked by three machine learning algorithms. Then, the ranked characteristics were placed into the classifiers according to the importance of features to obtain the optimal feature subset with the highest classification accuracy. The results showed that the optimal feature subset contained 86 features with the highest classification accuracy of 98.54% ± 0.21%. According to the statistics of the optimal feature subset, PLI had the largest number of features among the three categories, and the number of beta features was bigger than other rhythms. Moreover, compared to the healthy controls, the PLI values in the depression group increased in theta and beta rhythms, but decreased in alpha1 and alpha2 rhythms. The PSD of theta and beta rhythms were significantly greater in depression group than that in healthy controls, and the FE of beta rhythm showed the same trend. These findings indicate that the distribution of abnormal multidimensional features is potentially useful for the diagnosis of depression and understanding of neural mechanisms.

BackgroundTransient ischemic attack (TIA) is known as “small stroke.” However, the diagnosis of TIA is currently difficult due to the transient symptoms. Therefore, objective and reliable biomarkers are urgently needed in clinical practice.ObjectiveThe purpose of this study was to investigate whether dynamic alterations in resting-state local metrics could differentiate patients with TIA from healthy controls (HCs) using the support-vector machine (SVM) classification method.MethodsBy analyzing resting-state functional MRI (rs-fMRI) data from 48 patients with and 41 demographically matched HCs, we compared the group differences in three dynamic local metrics: dynamic amplitude of low-frequency fluctuation (d-ALFF), dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), and dynamic regional homogeneity (d-ReHo). Furthermore, we selected the observed alterations in three dynamic local metrics as classification features to distinguish patients with TIA from HCs through SVM classifier.ResultsWe found that TIA was associated with disruptions in dynamic local intrinsic brain activities. Compared with HCs, the patients with TIA exhibited increased d-fALFF, d-fALFF, and d-ReHo in vermis, right calcarine, right middle temporal gyrus, opercular part of right inferior frontal gyrus, left calcarine, left occipital, and left temporal and cerebellum. These alternations in the dynamic local metrics exhibited an accuracy of 80.90%, sensitivity of 77.08%, specificity of 85.37%, precision of 86.05%, and area under curve of 0.8501 for distinguishing the patients from HCs.ConclusionOur findings may provide important evidence for understanding the neuropathology underlying TIA and strong support for the hypothesis that these local metrics have potential value in clinical diagnosis.

Objective. This study is aimed at exploring alteration in motor-related effective connectivity in individuals with transient ischemic attack (TIA). Methods. A total of 48 individuals with TIA and 41 age-matched and sex-matched healthy controls (HCs) were recruited for this study. The participants were scanned using MRI, and their clinical characteristics were collected. To investigate motor-related effective connectivity differences between individuals with TIA and HCs, the bilateral primary motor cortex (M1) was used as the regions of interest (ROIs) to perform a whole-brain Granger causality analysis (GCA). Furthermore, partial correlation was used to evaluate the relationship between GCA values and the clinical characteristics of individuals with TIA. Results. Compared with HCs, individuals with TIA demonstrated alterations in the effective connectivity between M1 and widely distributed brain regions involved in motor, visual, auditory, and sensory integration. In addition, GCA values were significantly correlated with high- and low-density lipoprotein cholesterols in individuals with TIA. Conclusion. This study provides important evidence for the alteration of motor-related effective connectivity in TIA, which reflects the abnormal information flow between different brain regions. This could help further elucidate the pathological mechanisms of motor impairment in individuals with TIA and provide a new perspective for future early diagnosis and intervention for TIA.

In this study, the relationship between four expansion indices and the expansion potential of gypsum rock was studied; on this basis, a criterion for judging expansion potential is established for gypsum rock. The results show that the free expansion rate is unsuitable for grading gypsum rocks’ expansion potential. Setting the gypsum rock in the Wuzhishan tunnel as the research subject, the ultimate expansion rate is 24.28% on the 7th day and 34.08% on the 30th day; the ultimate expansion rate on the 7th day of the indoor rock sample can be estimated by the fitting formula on the 30th day, the ultimate expansion force is 304.51 kPa, and the BET-specific surface area is 6.31 m2/g. The ultimate expansion ratio and BET-specific surface area have an excellent linear relationship with the ultimate expansion force. Setting the ultimate expansion force, ultimate expansion ratio and BET-specific surface area as the standard, the criterion for judging the expansion potential of gypsum rock is determined, which is more convenient and accurate than existing standards. The standard in this paper can predict the potential disasters that may occur in underground engineering.

Purpose. Several functional magnetic resonance imaging (fMRI) studies have investigated the resting-state functional connectivity (rs-FC) changes in the primary motor cortex (M1) in patients with acute basal ganglia ischemic stroke (BGIS). However, the frequency-specific FC changes of M1 in acute BGIS patients are still unclear. Our study was aimed at exploring the altered FC of M1 in three frequency bands and the potential features as biomarkers for the identification by using a support vector machine (SVM). Methods. We included 28 acute BGIS patients and 42 healthy controls (HCs). Seed-based FC of two regions of interest (ROI, bilateral M1s) were calculated in conventional, slow-5, and slow-4 frequency bands. The abnormal voxel-wise FC values were defined as the features for SVM in different frequency bands. Results. In the ipsilesional M1, the acute BGIS patients exhibited decreased FC with the right lingual gyrus in the conventional and slow-4 frequency band. Besides, the acute BGIS patients showed increased FC with the right medial superior frontal gyrus (SFGmed) in the conventional and slow-5 frequency band and decreased FC with the left lingual gyrus in the slow-5 frequency band. In the contralesional M1, the BGIS patients showed lower FC with the right SFGmed in the conventional frequency band. The higher FC values with the right lingual gyrus and left SFGmed were detected in the slow-4 frequency band. In the slow-5 frequency band, the BGIS patients showed decreased FC with the left calcarine sulcus. SVM results showed that the combined features (slow-4+slow-5) had the highest accuracy in classification prediction of acute BGIS patients, with an area under curve (AUC) of 0.86. Conclusion. Acute BGIS patients had frequency-specific alterations in FC; SVM is a promising method for exploring these frequency-dependent FC alterations. The abnormal brain regions might be potential targets for future researchers in the rehabilitation and treatment of stroke patients.

Driving fatigue is the main cause of traffic accidents, which seriously affects people’s life and property safety. Many researchers have applied electroencephalogram (EEG) signals for driving fatigue detection to reduce negative effects. The main challenges are the practicality and accuracy of the EEG-based driving fatigue detection method when it is applied on the real road. In our previous study, we attempted to improve the practicality of fatigue detection based on the proposed non-hair-bearing (NHB) montage with fewer EEG channels, but the recognition accuracy was only 76.47% with the random forest (RF) model. In order to improve the accuracy with NHB montage, this study proposed an improved transformer architecture for one-dimensional feature vector classification based on introducing the Gated Linear Unit (GLU) in the Attention sub-block and Feed-Forward Networks (FFN) sub-block of a transformer, called GLU-Oneformer. Moreover, we constructed an NHB-EEG-based feature set, including the same EEG features (power ratio, approximate entropy, and mutual information (MI)) in our previous study, and the lateralization features of the power ratio and approximate entropy based on the strategy of brain lateralization. The results indicated that our GLU-Oneformer method significantly improved the recognition performance and achieved an accuracy of 86.97%. Our framework demonstrated that the combination of the NHB montage and the proposed GLU-Oneformer model could well support driving fatigue detection.

Mental fatigue is a widely studied topic on account of its serious negative effects. But how the neural mechanism of task switching before and after mental fatigue remains a question. To this end, this study aims to use brain functional network features to explore the answer to this question. Specifically, task-state EEG signals were recorded from 20 participants. The tasks include a 400-s 2-back-task (2-BT), followed by a 6480-s of mental arithmetic task (MAT), and then a 400-s 2-BT. Network features and functional connections were extracted and analyzed based on the selected task switching states, referred to from Pre_2-BT to Pre_MAT before mental fatigue and from Post_MAT to Post_2-BT after mental fatigue. The results showed that mental fatigue has been successfully induced by long-term MAT based on the significant changes in network characteristics and the high classification accuracy of 98% obtained with Support Vector Machines (SVM) between Pre_2-BT and Post_2-BT. when the task switched from Pre_2-BT to Pre_MAT, delta and beta rhythms exhibited significant changes among all network features and the selected functional connections showed an enhanced trend. As for the task switched from Post_MAT to Post_2-BT, the network features and selected functional connectivity of beta rhythm were opposite to the trend of task switching before mental fatigue. Our findings provide new insights to understand the neural mechanism of the brain in the process of task switching and indicate that the network features and functional connections of beta rhythm can be used as neural markers for task switching before and after mental fatigue.

Steel fibers are widely used because they can effectively improve the tensile, compressive and flexural properties of concrete structures. The selection of steel fiber dosage and aspect ratio at high temperature has an important impact on the flexural toughness of concrete components post-fire. In this paper, discussions are made on the simulated fire test in compliance with the ISO 834 standard to study the steel fiber-reinforced concrete (SFRC) components post-fire. The research reveals the influence of two commonly used steel fiber aspect ratios (50, 70) and steel fiber dosages (30 kg/m3, 40 kg/m3, 45 kg/m3) on the changes of the internal temperature field, the initial crack flexural strength and the flexural toughness of the SFRC components under a single-side fire. Moreover, combined with the four-point flexural test of the SFRC components post fire, the research also describes the damage of high temperatures to the flexural toughness of SFRC components, and suggests a calculation formula for SFRC thermal conductivity by way of the numerical inversion method. The results of this study have verified that the incorporation of steel fiber into concrete helps to reduce its internal thermal stress difference and improve the crack resistance and fire resistance of the concrete. Moreover, under high temperature conditions, the concrete component added with the steel fiber in an aspect ratio of 70 and a dosage of 45 kg/m3 increased their initial crack flexural strength by 56.8%, higher than that of plain concrete components, and the loss of equivalent flexural strength and flexural toughness of SFRC post fire was only 45.2% and 13.6%, respectively. The proposed calculation formula of thermal conductivity can provide a reference for a numerical simulation study of the temperature field of SFRC components in a high temperature environment.

Cemented coal waste backfill material (CCWBM) is developed for backfilling the goaf in coal mines. As fresh CCWBM slurry is generally transported into underground openings through a pipeline, the fluidity of fresh slurry becomes one of the most important properties. Adding superplasticizer is considered to improve the flow performance of the slurry without alerting the mechanical performance of filling body. The dosage of superplasticizer (SP) is related to filling cost, thus response surface methodology (RSM) is adopted to study the influence of material composition on SP when target slump is 250 mm. The effects of fly ash content, fine gangue ratio, and mass concentration on SP are analyzed using the software of Design-Expert and central composite design (CCD), and models are established for SP. Results show that the SP model coincides greatly with the test results and can be applied to analyze and predict SP in CCWBM. Mass concentration, fly ash content, and fine gangue ratio influence SP from high to low. The interaction of fine gangue ratio and mass concentration between SP is the most significant. The fact that the improved aggregate space model can be applied to analyze the fluidity of CCWBM is proved too. The research results provide guidance for the design and preparation of CCWBM with favourable performance and low cost in practical production.

Glutathione peroxidases (GPX) catalyze the reduction of H2O2 or organic hydroperoxides to water or corresponding alcohols using reduced glutathione, which plays an essential role in ROS (reactive oxygen species) homeostasis and stress signaling. Thellungiella salsuginea (Eutrema salsugineum), a relative of Arabidopsis thaliana, displays an extremely high level of tolerance to salt, drought, cold and oxidative stresses. The enzymatic antioxidant systems may contribute to the stress tolerance of T. salsuginea. In the present study, we aimed at understanding the roles of the antioxidant enzymes in T. salsuginea by focusing on the GPX family. We identified the eight GPX genes in T. salsuginea, and the structure of the N-terminal domains indicated their putative chloroplastic, mitochondrial and cytoplasmic location. The exon-intron organization of these genes exhibited a conserved pattern among plant GPX genes. Multiple environmental stresses and hormone response related cis-acting elements were predicted in the promoters of TsGPX genes. The gene and protein expression profiles of TsGPXs in response to high level of salinity and osmotic stresses, in leaves and roots of T. salsuginea were investigated using real-time RT-PCR and western blotting analysis. Our result showed that different members of the GPX gene family were coordinately regulated under specific environmental stress conditions, and supported the important roles of TsGPXs in salt and drought stress response in T. salsuginea.

Ammopiptanthus mongolicus (Maxim. Ex Kom.) Cheng f., a relic tree of the Tertiary period, plays a critical role in maintaining desert ecosystems in the Mid-Asia region. Genome-scale gene expression profiling studies will provide deep insight into the molecular mechanism underlying the drought tolerance of A. mongolicus. In the present study, we investigated the transcriptional changes induced by drought treatment in A. mongolicus leaves by establishing a comprehensive transcriptome database and then performing a Digital Gene Expression (DGE) analysis using Solexa sequencing technology. A comprehensive transcriptome database was obtained by assembling the Illumina unigenes with expressed sequence tags (EST) available publicly, and other high throughput sequencing data. To analyze the dynamic and complicated gene regulation network during PEG6000-induced drought treatment in leaves of A. mongolicus, a time-course gene expression analysis was performed using tag-based DGE technology, which identified 437, 1,247 and 802 differentially expressed transcripts in 1, 24 and 72 h drought stress libraries, respectively. GO and KEGG analyses revealed hormone signal transduction and phenylpropanoid biosynthesis were enriched during drought treatment. A batch of drought-regulated transcription factor transcripts were identified, including the subsets of HD-ZIP, bZIP, WRKY, AP2/ERF and bHLH family members, which may play roles in drought response in A. mongolicus. The sequence collection assembled in the present study represents one of the most comprehensive transcriptome databases for A. mongolicus currently. The differentially expressed transcripts identified in our study provide a good start for identifying the key genes in stress response and performing functional analysis to reveal their roles in stress adaptation in planta.

Bivalirudin as an anticoagulant reduces bleeding after percutaneous coronary intervention (PCI), while its impact in elderly Chinese patients treated with PCI needs more evidence. This study aimed to compare the clinical outcomes between bivalirudin and heparin in elderly Chinese patients treated with PCI. This cohort study retrieved data of 1,286 elderly patients treated with PCI who used bivalirudin (bivalirudin group, N = 493) or heparin (heparin group, N = 793) as anticoagulants. Net adverse clinical events (NACEs) (primary endpoint), major adverse cardiac and cerebral events (MACCEs), bleeding, and major bleeding within 30 days after PCI treatment were recorded for analysis. Our study illustrated that NACEs (12.4% vs. 17.4%, P = 0.015), bleeding (6.7% vs. 12.1%, P = 0.002), and major bleeding (2.2% vs. 6.6%, P < 0.001) were fewer in bivalirudin group compared to heparin group. No difference was found in MACCEs (7.5% vs. 9.6%, P = 0.200), and incidences of all-cause mortality (P = 0.257), cardiac mortality (P = 0.504), recurrent myocardial infarction (P = 0.423), ischemia-driven revascularization (P = 0.509), and stroke (P = 0.467), between bivalirudin group and heparin group. According to univariate logistic regression analyses, bivalirudin (vs. heparin) correlated with fewer NACEs (P = 0.016), bleeding (P = 0.002), and major bleeding (P = 0.001) in elderly patients treated with PCI, but not MACCEs (P = 0.202). After adjustment, bivalirudin (vs. heparin) was an independent factor for fewer NACEs [odds ratio (OR): 0.619, P = 0.009], bleeding (OR: 0.499, P = 0.003), and major bleeding (OR: 0.342, P = 0.003) in these patients. In summary, bivalirudin achieves fewer NACEs, bleeding, and major bleeding, but not MACCEs, versus heparin in elderly patients treated with PCI, which is verified in the multivariate model. [ABSTRACT FROM AUTHOR]

Abstract Objective To develop and validate a multiphase CT-based radiomics model for preoperative risk stratification of patients with localized clear cell renal cell carcinoma (ccRCC). Methods A total of 425 patients with localized ccRCC were enrolled and divided into training, validation, and external testing cohorts. Radiomics features were extracted from three-phase CT images (unenhanced, arterial, and venous), and radiomics signatures were constructed by the least absolute shrinkage and selection operator (LASSO) regression algorithm. The radiomics score (Rad-score) for each patient was calculated. The radiomics model was established and visualized as a nomogram by incorporating significant clinical factors and Rad-score. The predictive performance of the radiomics model was evaluated by the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA). Results The AUC of the triphasic radiomics signature reached 0.862 (95% CI: 0.809–0.914), 0.853 (95% CI: 0.785–0.921), and 0.837 (95% CI: 0.714–0.959) in three cohorts, respectively, which were higher than arterial, venous, and unenhanced radiomics signatures. Multivariate logistic regression analysis showed that Rad-score (OR: 4.066, 95% CI: 3.495–8.790) and renal vein invasion (OR: 12.914, 95% CI: 1.118–149.112) were independent predictors and used to develop the radiomics model. The radiomics model showed good calibration and discrimination and yielded an AUC of 0.872 (95% CI: 0.821–0.923), 0.865 (95% CI: 0.800–0.930), and 0.848 (95% CI: 0.728–0.967) in three cohorts, respectively. DCA showed the clinical usefulness of the radiomics model in predicting the Leibovich risk groups. Conclusions The radiomics model can be used as a non-invasive and useful tool to predict the Leibovich risk groups for localized ccRCC patients. Critical relevance statement The triphasic CT-based radiomics model achieved favorable performance in preoperatively predicting the Leibovich risk groups in patients with localized ccRCC. Therefore, it can be used as a non-invasive and effective tool for preoperative risk stratification of patients with localized ccRCC. Key points • The triphasic CT-based radiomics signature achieves better performance than the single-phase radiomics signature. • Radiomics holds prospects in preoperatively predicting the Leibovich risk groups for ccRCC. • This study provides a non-invasive method to stratify patients with localized ccRCC. Graphical Abstract

Objective: This study aimed to develop a nomogram combining CT-based handcrafted radiomics and deep learning (DL) features to preoperatively predict muscle invasion in bladder cancer (BCa) with multi-center validation. Methods: In this retrospective study, 323 patients underwent radical cystectomy with pathologically confirmed BCa were enrolled and randomly divided into the training cohort (n = 226) and internal validation cohort (n = 97). And fifty-two patients from another independent medical center were enrolled as an independent external validation cohort. Handcrafted radiomics and DL features were constructed from preoperative nephrographic phase CT images. Least absolute shrinkage and selection operator (LASSO) regression was used to identify the most discriminative features in train cohort. Multivariate logistic regression was used to develop the predictive model and a deep learning radiomics nomogram (DLRN) was constructed. The predictive performance of models was evaluated by area under the curves (AUC) in the three cohorts. The calibration and clinical usefulness of DLRN were estimated by calibration curve and decision curve analysis. Results: The nomogram that incorporated radiomics signature and DL signature demonstrated satisfactory predictive performance for differentiating non-muscle invasive bladder cancer (NMIBC) from muscle invasive bladder cancer (MIBC), with an AUC of 0.884 (95 % CI: 0.813–0.953) in internal validation cohort and 0.862 (95 % CI: 0.756–0.968) in external validation cohort, respectively. Decision curve analysis confirmed the clinical usefulness of the nomogram. Conclusions: A CT-based deep learning radiomics nomogram exhibited a promising performance for preoperative prediction of muscle invasion in bladder cancer, and may be helpful in the clinical decision-making process.