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Abstract This study aims to explore the inhibitory effects of combined metformin and simvastatin therapy on the malignant progression of glioma. The research specifically examines how the maturation of SREBP2 as a transcription factor affects the expression of GLUT1 and GLUT6 in glioma cells. Additionally, it investigates the impact of this combination therapy on the biological functions and energy metabolism of glioma cells. To assess the functions of GLUT1/6, sh-GLUT1/6 plasmids were employed. The study determined the half-maximal inhibitory concentrations (IC50) of metformin and simvastatin using the CCK-8 assay. Subsequently, the effects of these drugs on glioma metabolism, proliferation, and apoptosis were explored in vitro and in vivo, using drug concentrations significantly lower than their respective IC50 values. The impact of drug treatment on GLUT1/6 and SREBP2 expression levels was also evaluated. The study elucidated the significant impact of GLUT1/6 on glioma cell functions, resulting in decreased glucose uptake. Moreover, it unveiled the regulatory role of SREBP2 in GLUT1 and GLUT6 transcription, alongside revealing differential expression of SREBP2 precursor and mature forms within gliomas. Following combined drug therapy, GLUT1/6 expression decreased, while the precursor form of SREBP2 increased, and mature SREBP2 reduced. This dual-drug treatment effectively modulated glioma cell energy metabolism. Subsequent in vivo experiments affirmed the augmented anti-tumor efficacy of combined drug therapy. Specifically, the synergistic action of metformin and simvastatin reshaped glioma metabolism, curbed malignant proliferation, promoted apoptosis, and demonstrated superior anti-tumor effects both in vitro and in vivo compared to individual administration of metformin or simvastatin. Importantly, the combination therapy achieved these effects at lower doses, rendering it a safer treatment option.

Abstract Purpose Currently, deep learning methods for the classification of benign and malignant lung nodules encounter challenges encompassing intricate and unstable algorithmic models, limited data adaptability, and an abundance of model parameters.To tackle these concerns, this investigation introduces a novel approach: the 3D Global Coordinated Attention Wide Inverted ResNet Network (GC-WIR). This network aims to achieve precise classification of benign and malignant pulmonary nodules, leveraging its merits of heightened efficiency, parsimonious parameterization, and robust stability. Methods Within this framework, a 3D Global Coordinate Attention Mechanism (3D GCA) is designed to compute the features of the input images by converting 3D channel information and multi-dimensional positional cues. By encompassing both global channel details and spatial positional cues, this approach maintains a judicious balance between flexibility and computational efficiency. Furthermore, the GC-WIR architecture incorporates a 3D Wide Inverted Residual Network (3D WIRN), which augments feature computation by expanding input channels. This augmentation mitigates information loss during feature extraction, expedites model convergence, and concurrently enhances performance. The utilization of the inverted residual structure imbues the model with heightened stability. Results Empirical validation of the GC-WIR method is performed on the LUNA 16 dataset, yielding predictions that surpass those generated by previous models. This novel approach achieves an impressive accuracy rate of 94.32%, coupled with a specificity of 93.69%. Notably, the model’s parameter count remains modest at 5.76M, affording optimal classification accuracy. Conclusion Furthermore, experimental results unequivocally demonstrate that, even under stringent computational constraints, GC-WIR outperforms alternative deep learning methodologies, establishing a new benchmark in performance.

Abstract Glioblastoma (GBM) presents significant challenges due to its invasive nature and genetic heterogeneity. In this study, we investigated the impact of Small VCP/P97-Interacting Protein (SVIP) on GBM progression. Our results revealed elevated expression of Insulin-like Growth Factor Binding Protein 2 (IGFBP-2) and STIP1 homology and U-box containing protein 1 (STUB1), coupled with reduced SVIP levels in GBM samples. Notably, high IGFBP-2 expression correlated with poor prognosis. Mechanistically, SVIP competitively inhibited STUB1, selectively binding to VCP/p97, thereby reducing PTEN degradation. This SVIP-mediated regulation exerted influence on the PTEN/PI3K/AKT/mTOR pathway, leading to the suppression of GBM progression. Co-localization experiments demonstrated that SVIP hindered PTEN ubiquitination and degradation by outcompeting STUB1 for VCP/p97 binding. Moreover, SVIP overexpression resulted in reduced activation of AKT/mTOR signaling and facilitated autophagy. In vivo experiments using a GBM xenograft model substantiated the tumor-suppressive effects of SVIP, evident by suppressed tumor growth, decreased IGFBP-2 expression, and improved survival rates. Collectively, our findings underscore the functional significance of SVIP in GBM progression. By inhibiting STUB1 and stabilizing PTEN, SVIP modulates the expression of IGFBP-2 and attenuates the activation of the PI3K/AKT/mTOR pathway, thereby emerging as a promising therapeutic target for GBM treatment.

Abstract Glioma is the most common malignant tumor of the central nervous system, with EZH2 playing a crucial regulatory role. This study further explores the abnormal expression of EZH2 and its mechanisms in regulating glioma progression. Additionally, it was found that IHMT-337 can potentially be a therapeutic agent for glioma. The prognosis, expression, and localization of EZH2 were determined using bioinformatics, IHC staining, Western blot (WB) analysis, and immunofluorescence (IF) localization. The effects of EZH2 on cell function were assessed using CCK-8 assays, Transwell assays, and wound healing assays. Public databases and RT-qPCR were utilized to identify downstream targets. The mechanisms regulating these downstream targets were elucidated using MS-PCR and WB analysis. The efficacy of IHMT-337 was demonstrated through IC50 measurements, WB analysis, and RT-qPCR. The effects of IHMT-337 on glioma cells in vitro were evaluated using Transwell assays, EdU incorporation assays, and flow cytometry. The potential of IHMT-337 as a treatment for glioma was assessed using a blood–brain barrier (BBB) model and an orthotopic glioma model. Our research confirms significantly elevated EZH2 expression in gliomas, correlating with patient prognosis. EZH2 facilitates glioma proliferation, migration, and invasion alongside promoting SLC12A5 DNA methylation. By regulating SLC12A5 expression, EZH2 activates the WNK1-OSR1-NKCC1 pathway, enhancing its interaction with ERM to promote glioma migration. IHMT-337 targets EZH2 in vitro to inhibit WNK1 activation, thereby suppressing glioma cell migration. Additionally, it inhibits cell proliferation and arrests the cell cycle. IHMT-337 has the potential to cross the BBB and has successfully inhibited glioma progression in vivo. This study expands our understanding of the EZH2-SLC12A5 axis in gliomas, laying a new foundation for the clinical translation of IHMT-337 and offering new insights for precision glioma therapy.

The study of agricultural non-point source pollution (ANNSP) patterns and driving mechanisms is crucial for regional ecological management. This paper evaluates the sources of ANNSP in the Huang-Huai-Hai Plain for the years 2000, 2010, and 2020 using the source list method. Additionally, nitrogen source data for the InVEST model were supplemented and adjusted, and the nitrogen output load and proportions derived in farmland from both methods were compared. The temporal and spatial distribution of nitrogen emission intensity was analyzed based on InVEST model outputs. Key source areas were identified through hotspot analysis, and spatial driving factors were examined using geodetector. Key findings reveal: 1) While the source list method estimated a higher nitrogen output load, both methods concurred on the proportion of agricultural nitrogen. The main sources of nitrogen input were overuse of fertilizer and livestock breeding. 2) Over this period, nitrogen emission intensity declined, exhibiting a distinct spatial pattern of “northwest low, southeast high.” 3) The extent of critical source areas underwent a dynamic shift, initially contracting before expanding. 4) Rainfall emerged as the primary driver of spatial variability in agricultural TN emission intensity. These insights offer critical reference points for achieving efficient ANNSP management in the Huang-Huai-Hai Plain.

Circadian dysfunction is prevalent in neurodevelopmental disorders, particularly in autism spectrum disorder (ASD). A plethora of empirical studies demonstrate a strong correlation between ASD and circadian disruption, suggesting that modulation of circadian rhythms and the clocks could yield satisfactory advancements. Research indicates that circadian dysfunction associated with abnormal neurodevelopmental phenotypes in ASD individuals, potentially contribute to synapse plasticity disruption. Therefore, targeting circadian rhythms may emerge as a key therapeutic approach. In this study, we did a brief review of the mammalian circadian clock, and the correlation between the circadian mechanism and the pathology of ASD at multiple levels. In addition, we highlight that circadian is the target or modulator to participate in the therapeutic approaches in the management of ASD, such as phototherapy, melatonin, modulating circadian components, natural compounds, and chronotherapies. A deep understanding of the circadian clock’s regulatory role in the neurodevelopmental phenotypes in ASD may inspire novel strategies for improving ASD treatment.

In this article, a time-varying coefficient modified nonlinear Schrödinger equation (tvcmNLSE) with non-zero boundary conditions (NZBCs) at infinity, phase term of which contains time-varying coefficients, is proposed to describe the nonlinear propagation behavior of optical pulses in non-uniform optical fibre. Meanwhile, the Riemann–Hilbert method (RHM) for the tvcmNLSE with NZBCs is presented for the first time. Specifically, a special transformation is constructed to convert the tvcmNLSE with NZBCs into the case with constant NZBCs, and the associated asymptotic spectral problem (ASP) is obtained. By introducing a suitable two-piece Riemann surface to map the original spectral parameter into a single-valued one, and analyzing the ASP, we construct the corresponding Jost solutions and spectral matrix, and sequentially analyze their analytical, symmetric, and asymptotic properties. Then, a generalized Riemann–Hilbert problem (RHP) is established that relates to the converted tvcmNLSE with constant NZBCs. Using the reconstruction formula, we further derive N-soliton solution with NZBCs in the absence of reflection potential, and analyze the dynamic characteristics of single and double solitons. Most notably, by modulating discrete spectral points (DSPs) and time-varying coefficients, we discover some previously unreported new waveforms, such as parabolic and periodic solitons with NZBCs. These waveforms have important implications in both theory and practice. In addition, the influences of different time-varying coefficients, NZBCs, and DSPs on soliton solutions are also discussed and analyzed. This study shows that the selection of time-varying coefficients, distribution of DSPs, and constraints from NZBCs all have significant impacts on the properties of soliton solutions.

Abstract Background To evaluate the efficacy of modified uterine stent in the treatment of mild-to-moderate intrauterine adhesions and explore the relative indicators affecting prognosis prediction. Methods A total of 115 patients with mild-to-moderate intrauterine adhesions received a modified uterine stent placement after hysteroscopy adhesiolysis. The second-look hysteroscopy operated after 3 months surgery, and the third-look hysteroscopy operated after 6 months surgery if necessary. The stent was removed when the cavity shape was repaired, then the reproductive outcomes were followed up one year. Results Menstrual blood volume, endometrial thickness and volume had increased significantly after 3 months surgery. The rates of cavity repaired were 86.96% (100/115) after 3 months surgery and 100% (115/115) after 6 months surgery cumulatively. Endometrial thickness after 3-months surgery was positively associated with uterine cavity shape repaired (P

Abstract Background The aim of this study was to develop a nomogram by combining chest computed tomography (CT) images and clinicopathological predictors to assess the survival outcomes of patients with primary pulmonary lymphoepithelial carcinoma (PLEC). Methods 113 patients with stage I–IV primary PLEC who underwent treatment were retrospectively reviewed. The Cox regression analysis was performed to determine the independent prognostic factors associated with patient’s disease-free survival (DFS) and cancer-specific survival (CSS). Based on results from multivariate Cox regression analysis, the nomograms were constructed with pre-treatment CT features and clinicopathological information, which were then assessed with respect to calibration, discrimination and clinical usefulness. Results Multivariate Cox regression analysis revealed the independent prognostic factors for DFS were surgery resection and hilar and/or mediastinal lymphadenopathy, and that for CSS were age, smoking status, surgery resection, tumor site in lobe and necrosis. The concordance index (C‑index) of nomogram for DFS and CSS were 0.777 (95% CI: 0.703–0.851) and 0.904 (95% CI: 0.847–0.961), respectively. The results of the time‑dependent C‑index were internally validated using a bootstrap resampling method for DFS and CSS also showed that the nomograms had a better discriminative ability. Conclusions We developed nomograms based on clinicopathological and CT factors showing a good performance in predicting individual DFS and CSS probability among primary PLEC patients. This prognostic tool may be valuable for clinicians to more accurately drive treatment decisions and individualized survival assessment.

ABSTRACTConvex and concave hulls originating from computational geometry are widely applied in practice. For instance, to determine the boundaries of a geographical area within a group of cities, convex hulls can represent the approximate boundaries of the areas. Concave hulls can accurately describe the shape of the area. The traditional methods for solving two-dimensional convex hull problems include the Jarvis March algorithm and the Graham scanning algorithm. The K-nearest neighbours and alpha-shape methods are designed for solving the concave hull problem. Other than traditional algorithms, we consider using deep neural networks to handle the convex and concave hull problems. General neural networks cannot deal with the problem whose output is a variable-length sequence. Our study provides a machine-learning approach for solving the convex hull and concave hull problems. We combine the Pointer network (Ptr-Net) with the Transformer model and propose the DeepHullNet. The trained DeepHullNet can provide a feasible solution in the majority of cases. The experimental results show that DeepHullNet outperforms the original Ptr-Net regarding accuracy. Compared with traditional methods, DeepHullNet can generate a good solution quickly, and the running time is shortened by nearly 100 times based on GPU.

Abstract Background Calcifying pseudoneoplasm of the neuraxis (CAPNON) is indeed a rare central nervous system lesion that can occur in central nervous system (CNS). Due to its infrequency and limited literature reports, it is challenging to diagnose and manage CAPNON. Case presentation In this intriguing study, we embarked on a quest to uncover the story of a 16-year-old girl who experienced bothersome headaches. Through advanced imaging techniques like computed tomography (CT) and magnetic resonance imaging (MRI), we glimpsed a delicate calcified growth within the lateral ventricles’ posterior horn. Motivated by our unwavering commitment to solving mysteries, we embarked on a surgical journey that not only freed the young patient from her ailment but also shed light on the true nature of her puzzling adversary—a remarkable CAPNON. Conclusions For patients with CAPNON who have multiple or non-respectable lesions, the primary goal is to alleviate symptoms. After alleviating the symptoms with partial resection, close monitoring of any residual lesions is essential. If there is no evidence for disease progression, a strategy of continued close observation is appropriate.

By studying the development law of urbanization, the problems of disorderly expansion and resource wastage in urban built-up areas can be effectively avoided, which is crucial for the long-term sustainable development of cities. This study proposes a high-precision urban built-up-area extraction method for county-level cities for small and medium-sized towns in county-level regions. Our process is based on the Defense Meteorological Satellite/Operational Linescan System (DMSP/OLS) and the NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS), which develops long-term series of coordinated night-time light (NTL) datasets. We then combined this with the Normalized Vegetation Index (NDVI) to calculate the Vegetation-Adjusted NTL Urban Index (VANUI). We combine land use data and a support vector machine (SVM) for semi-supervised classification learning to propose a high-precision urban built-up-area extraction method for county-level cities. We achieved the following results: (1) we fit binary polynomials to the DMSP/OLS and VIIRS NTL datasets based on the correspondence of the mean values to construct a consistent time series of NTL data. (2) Our method effectively improves the accuracy of urban built-up-area extraction, especially for county-level cities, with an overall accuracy of 91.84% and a Kappa coefficient of 0.83. (3) Our method can perform a long-time series of urban built-up-area extraction, and, by studying the spatial and temporal changes in urban built-up areas, it can provide valuable information for sustainable urban development and urban planning.

In order to explore the suitable temperature and time for waterless live transportation of Litopenaeus vannamei, this paper investigated the low dormancy temperature and determined the survival rate at different time periods of simulated transportation under 4 and 10 ℃. The muscle quality and physiological stress indexes were analyzed in four states: Control group, dormant group, transport group and recovered for 30 min group. The results indicated that the dormancy temperature of Litopenaeus vannamei was (10.0±0.2) ℃. The survival rates of two temperature groups were both 100% within 12 h of simulated transportation and lower than 30% after 36 h. The effects of different transport temperatures on muscle quality indexes were not significant (P>0.05). Except for the cooking loss rate, the effects of transport stress on moisture, crude protein and crude fat content at the same temperature were not significant (P>0.05). Compared with the control, the contents of muscle glycogen, succinate dehydrogenase (SDH), lactate dehydrogenase (LDH) and malondialdehyde (MDA) were significantly (P

Background: To explore the risk factors for early pregnancy loss and to study the relationship between early pregnancy loss and intrauterine adhesion (IUA) confirmed by hysteroscopy. Methods: A retrospective study was conducted on 226 early pregnancy loss and 51 early pregnancy patients who received medical management combined with hysteroscopy at a regional institution from March 2020 to February 2021. The uterine cavity’s shape was evaluated by hysteroscopy 6 hours after treatment with medicine. Risk factors included maternal age, gestational weeks, gravidity, parity, number of prior early pregnancy losses, number of prior induced abortions, mean sac diameter (MSD) and IUA. Results: Our results showed that the prevalence of IUA increased significantly in early pregnancy loss cases (31.42%) compared with early pregnancy cases (9.8%) (p < 0.01). Multivariate logistic regression analysis showed that maternal age (odds ratio (OR): 1.195, 95% confidence interval (95% CI): 1.077–1.326), gestational weeks (OR: 2.919, 95% CI: 2.028–4.201) and IUA (OR: 8.631, 95% CI: 2.455–30.336) were positively associated with early pregnancy loss, while MSD (OR: 0.943, 95% CI: 0.899–0.990) and parity (OR: 0.194, 95% CI: 0.088–0.428) were inversely associated with early pregnancy loss. Conclusions: Maternal age, gestational weeks and, IUA were the risk factors for early pregnancy loss. Special attention is to be given to cases of combined IUA when managing early pregnancy loss.

Human health is facing a host of new threats linked to unbalanced diets, including high-sugar diet (HSD), which contributes to the development of both metabolic and behavioral disorders. Studies have shown that diet-induced metabolic dysfunctions can be transmitted to multiple generations of offspring and exert long-lasting health burden. Meanwhile, whether and how diet-induced behavioral abnormalities can be transmitted to the offspring remains largely unclear. Here, we showed that ancestral HSD exposure suppressed sweet sensitivity and feeding behavior in the offspring in Drosophila. These behavioral deficits were transmitted through the maternal germline and companied by the enhancement of H3K27me3 modifications. PCL-PRC2 complex, a major driver of H3K27 trimethylation, was upregulated by ancestral HSD exposure, and disrupting its activity eliminated the transgenerational inheritance of sweet sensitivity and feeding behavior deficits. Elevated H3K27me3 inhibited the expression of a transcriptional factor Cad and suppressed sweet sensitivity of the sweet-sensing gustatory neurons, reshaping the sweet perception and feeding behavior of the offspring. Taken together, we uncovered a novel molecular mechanism underlying behavioral abnormalities spanning multiple generations of offspring upon ancestral HSD exposure, which would contribute to the further understanding of long-term health risk of unbalanced diet.

Abstract Background Gastric cancer (GC) is the third-leading cause of cancer-associated mortalities globally. The deregulation of circular RNAs (circRNAs) and microRNAs (miRNAs or miRs) is widely implicated in the pathogenesis and progression of different cancer types. Methods The expression profiling of circRNAs in GC is required to identify crucial circRNAs as biomarkers or therapeutic targets. In the present study, a published circRNA microarray dataset was used to identify differentially expressed circRNAs between GC tissues and normal gastric mucosa tissues. Reverse transcription-quantitative PCR was performed to validate the expression of circ_0001789. Fisher’s exact test, receiver operating characteristic curve and Kaplan-Meier plots were employed to analyze the clinical significance of circ_0001789. The miRNA targets of circ_0001789 were predicted using an online database, and their functional interaction was further confirmed by RNA pull-down, RNA immunoprecipitation and dual luciferase reporter assays. Transwell assays were conducted to investigate the biological functions of circ_0001789, miR-140-3p and p21 activated kinase 2 (PAK2) in the migration and invasion of GC cells. A xenograft mouse model was established to validate the role of circ_0001789 in the tumorigenesis of GC cells. Results circ_0001789 was identified as a highly expressed circRNA in GC tissues versus normal gastric mucosa tissues. Silencing circ_0001789 attenuated the malignancy of GC cells, and exosomal circ_0001789 was sufficient to regulate the malignant phenotype of GC cells. miR-140-3p was further identified as a downstream target of circ_0001789, which showed a negative correlation with circ_0001789 expression in GC tissues. Overexpression of miR-140-3p suppressed cell migration, invasion and epithelial-mesenchymal transition in GC cells. PAK2 was identified as the target of miR-140-3 to mediate the malignant phenotype of GC cells. Conclusion The present data suggested that the upregulation of circ_0001789 was associated with the progression of GC and with poor prognosis in patients with GC, and that miR-140-3p/PAK2 served as the downstream axis to mediate the oncogenic effect of circ_0001789.

Clubroot disease, caused by Plasmodiophora brassicae, poses a significant global threat to cruciferous crops. The epidemic area of clubroot disease is expanding rapidly. In response to this pressing issue, there is a compelling need for the development of clubroot disease-resistant radish cultivars. China boasts an extensive array of radish varieties and germplasm resources. However, a comprehensive assessment of their resistance to clubroot has not yet been carried out, thereby impeding the effective utilization of germplasm and clubroot-resistant breeding. Therefore, it is urgent to systematically evaluate the clubroot resistance of the radish germplasm and identify resistant resources. In this study, clubroot resistance evaluations were conducted on 268 excellent radish varieties derived from 30 provinces in China, as well as seven accessions from Russia, North Korea, France, South Korea, and Germany. The resistance evaluation revealed a diverse range of resistance indices, with a mean disease index (DI) ranging from 0.6 to 58.5, showing significant disparities in clubroot resistance among these radish resources. A total of six accessions were characterized as highly resistant to clubroot, and a further 50 accessions were characterized as resistant. The disease-resistant radishes showed diversity in horticultural traits. Provinces in South China contributed significantly more resistance germplasm than those of North China. These materials are of great value for both genetic investigation and the crop breeding of clubroot resistance. Furthermore, we employed a previously established clubroot-resistance-linked SSR marker to analyze the clubroot-resistant resources. The accessions exhibited dissimilar genetic profiles from known clubroot-resistant germplasm, suggesting their potential status as novel sources of clubroot resistance. Conclusively, these newly identified accessions enriched the genetic diversity within the clubroot-resistant gene pool and may contribute to the future cloning of previously undiscovered clubroot-resistant genes.

To address the problem that traditional spectral clustering algorithms cannot obtain the complete structural information of networks, this paper proposes a spectral clustering community detection algorithm, PMIK-SC, based on the point-wise mutual information (PMI) graph kernel. The kernel is constructed according to the point-wise mutual information between nodes, which is then used as a proximity matrix to reconstruct the network and obtain the symmetric normalized Laplacian matrix. Finally, the network is partitioned by the eigendecomposition and eigenvector clustering of the Laplacian matrix. In addition, to determine the number of clusters during spectral clustering, this paper proposes a fast algorithm, BI-CNE, for estimating the number of communities. For a specific network, the algorithm first reconstructs the original network and then runs Monte Carlo sampling to estimate the number of communities by Bayesian inference. Experimental results show that the detection speed and accuracy of the algorithm are superior to other existing algorithms for estimating the number of communities. On this basis, the spectral clustering community detection algorithm PMIK-SC also has high accuracy and stability compared with other community detection algorithms and spectral clustering algorithms.

In order to solve the problem that the organic working medium of a power generation system is easy to thermal decomposition at medium and high temperature, the waste heat was recovered with the supercritical and transcritical CO2 used in combination on the principle of "appropriate temperature and cascade utilization", and a poly-generation system based on LNG cold energy utilization was established. Herein, the system was simulated by Aspen HYSYS in terms of the process flow and evaluated from the prospective of thermal performance and exergoeconomy. Besides, the effect of main parameters on system performance was analyzed, and on this basis, the multi-objective optimization of system performance was carried out using Matlab. The results show that the reduction of split ratio in supercritical CO2 recompression Brayton cycle and compression ratio in refrigeration cycle can not only improve the system efficiency, but also reduce the average unit cost. In addition, the power generation efficiency, exergy efficiency and average unit cost of the optimized poly-generation system are 55.83%, 52.23% and 16.57 $/GJ, respectively, and the power generation efficiency has been enhanced by 14.05% in comparison to the system integrated with the single supercritical CO2 recompression Brayton cycle. Generally, the research results could provide an application idea for the utilization of LNG cold energy and the recovery of waste heat.

PURPOSEThis study aimed to compare the radiation dose received by the operator among different patients’ positions via transradial access (TRA) or transfemoral access (TFA) during transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC).METHODSA total of 120 patients with HCC undergoing TACE for the first time between January and November 2019 were randomized into 4 groups with 30 patients in each group. In group A, patients were placed in the foot-first position with the left upper arm abducted, and TACE was performed via the left radial artery. In group B, patients were placed in the conventional headfirst position with the left hand placed at the left groin, and TACE was performed via the left radial artery. In group C, patients were placed in the conventional head-first position, and TACE was performed via the right radial artery. In group D, patients were placed in the conventional head-first position, and TACE was performed via the right femoral artery. Before each procedure, thermoluminescent dosimeters were taped at 7 different body parts of the operator and the radiation dose was measured and collected after the procedure. The normalized radiation dose was also calculated. Procedural parameters included radiation dose, fluoroscopy time (FT), dose–area product (DAP), and air kerma (AK) were recorded. Patients’ demographics, tumor baseline characteristics, radiation dose, and procedural parameters were compared between groups.RESULTSNo significant differences were found in patients’ demographics, tumor baseline characteristics, as well as in total FT, DAP, and AK. However, significant differences were found in the total radiation dose received by the operator and the doses on the pelvic cavity and the right wrist (P < .05). In group C, the radiation doses received on the pelvic cavity, the right wrist, and the total radiation doses were relatively higher. Significant differences were also found in the normalized radiation doses received by the operator on the thyroid, chest, left wrist, right wrist, and pelvic cavity, and the total normalized doses (all P < .05). Similarly, the radiation doses received by the operator at the aforementioned parts in group C were higher, while those in group A were lower.CONCLUSIONNo statistically significant differences were observed in the FT, DAP, and AK in TACE via TRA when patients were placed in different positions. However, TACE via the left TRA, with patients in the feet-first position, reduced the radiation dose received by the operator, thereby reducing the radiation risk.

China's shale gas production in 2020 exceeds 200 × 108 m³, which creates a miracle in the history of natural gas development in China. The Sichuan Basin has already been and will be the main battlefield of shale gas exploration and development in China. In order to further promote the large-scale efficient development of shale gas in China, under the new situation of global COVID-19 spread and domestic “carbon peak and carbon neutrality” goal, this paper analyzes the progress and challenges of shale gas exploration and development in the Sichuan Basin from four aspects, including resource exploration, gas reservoir engineering, drilling and production engineering and industry regulation, and puts forward countermeasures and suggestions for achieving large-scale efficient development of shale gas. The following research results are obtained: First, the large-scale efficient development of shale gas in the Sichuan Basin has to take the sustainable and stable production of middle–shallow shale gas and the large-scale productivity construction of deep shale gas as the base. Second, compared with the shale gas exploration and development in the North America, the Sichuan Basin has its own characteristics in terms of geographical setting, geological condition, drilling and production technology and industry regulation, which makes it difficult to copy the development pattern of large scale, high density and continuous well deployment from the North America, so it is necessary to adopt the strategy of “high production with few wells”. On the one hand, continue to apply the geology and engineering integration technology to carry out “integrated research, integrated design, integrated implementation and integrated iteration” in the whole life cycle of shale gas well; and on the other hand, carry out problem-oriented continuous researches from the aspects of geological evaluation, development policy, engineering technology and industry regulation, so as to improve geological evaluation theory and technology, innovate gas reservoir engineering theory and method, research and develop engineering technology for cost reduction and efficiency improvement, improve shale gas industry regulation, and form a new pattern of collaborative promotion of technical and non-technical elements. In conclusion, the research results provide important reference and guidance for the large-scale efficient development of shale gas in the Sichuan Basin and even the whole country.

Abstract Background Immunotherapies targeting ligand-receptor interactions (LRIs) are advancing rapidly in the treatment of colorectal cancer (CRC), and LRIs also affect many aspects of CRC development. However, the pattern of LRIs in CRC and their effect on tumor microenvironment and clinical value are still unclear. Methods We delineated the pattern of LRIs in 55,539 single-cell RNA sequencing (scRNA-seq) samples from 29 patients with CRC and three bulk RNA-seq datasets containing data from 1411 CRC patients. Then the influence of tumor microenvironment, immunotherapy and prognosis of CRC patients were comprehensively investigated. Results We calculated the strength of 1893 ligand-receptor pairs between 25 cell types to reconstruct the spatial structure of CRC. We identified tumor subtypes based on LRIs, revealed the relationship between the subtypes and immunotherapy efficacy and explored the ligand-receptor pairs and specific targets affecting the abundance of tumor-infiltrating lymphocytes. Finally, a prognostic model based on ligand-receptor pairs was constructed and validated. Conclusion Overall, through the comprehensive and in-depth investigation of the existing ligand-receptor pairs, this study provides new ideas for CRC subtype classification, a new risk screening tool for CRC patients, and potential ligand-receptor pair targets and pathways for CRC therapy.

Abstract Background The imaging features of focal liver lesions (FLLs) are diverse and complex. Diagnosing FLLs with imaging alone remains challenging. We developed and validated an interpretable deep learning model for the classification of seven categories of FLLs on multisequence MRI and compared the differential diagnosis between the proposed model and radiologists. Methods In all, 557 lesions examined by multisequence MRI were utilised in this retrospective study and divided into training–validation (n = 444) and test (n = 113) datasets. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the performance of the model. The accuracy and confusion matrix of the model and individual radiologists were compared. Saliency maps were generated to highlight the activation region based on the model perspective. Results The AUC of the two- and seven-way classifications of the model were 0.969 (95% CI 0.944–0.994) and from 0.919 (95% CI 0.857–0.980) to 0.999 (95% CI 0.996–1.000), respectively. The model accuracy (79.6%) of the seven-way classification was higher than that of the radiology residents (66.4%, p = 0.035) and general radiologists (73.5%, p = 0.346) but lower than that of the academic radiologists (85.4%, p = 0.291). Confusion matrices showed the sources of diagnostic errors for the model and individual radiologists for each disease. Saliency maps detected the activation regions associated with each predicted class. Conclusion This interpretable deep learning model showed high diagnostic performance in the differentiation of FLLs on multisequence MRI. The analysis principle contributing to the predictions can be explained via saliency maps.

Abstract Objective Neuroinflammation plays a critical role in central nervous system diseases. Exosomal miRNAs released from various cells are implicated in cell-to-cell communication. Prior studies have placed substantial emphasis on the role of cytokines in mast cell-microglia interactions during neuroinflammation. However, it has never been clearly determined whether exosomal miRNAs participate in the interaction between mast cells and microglia and thus mediate neuroinflammation. Methods The characteristics of exosomes isolated from cell culture supernatants were confirmed by transmission electron microscopy (TEM), nanoparticle-tracking analysis (NTA) and Western blot. The transfer of PKH67-labelled exosomes and Cy3-labelled miR-409-3p was observed by fluorescence microscopy. Migration and activation of murine BV-2 microglial cells were evaluated through Transwell assays and immunofluorescence staining for Iba1 and CD68. CD86, IL-1β, IL-6 and TNF-α were assessed via qRT-PCR and ELISA. MiR-409-3p was detected by qRT-PCR. Nr4a2 and NF-κB levels were measured by western blot. Regulatory effects were identified by luciferase reporter assays. Results Lipopolysaccharide (LPS)-stimulated murine P815 mast cells secreted exosomes that were efficiently taken up by murine BV-2 cells, which promoted murine BV-2 cell migration and activation. LPS-P815 exosomes increased the CD86, IL-1β, IL-6 and TNF-α levels in murine BV-2 microglia. Furthermore, activated mast cells delivered exosomal miR-409-3p to murine BV-2 microglia. Upregulated miR-409-3p promoted murine BV-2 microglial migration, activation and neuroinflammation by targeting Nr4a2 to activate the NF-κB pathway. Conclusion Exosomal miR-409-3p secreted from activated mast cells promotes microglial migration, activation and neuroinflammation by targeting Nr4a2 to activate the NF-κB pathway, which provides evidence that not only cytokines but also exosomal miRNAs participate in neuroinflammation. In the future, targeting exosomal miRNAs may provide new insights into neuroinflammation.

Interventional therapy is one of the most effective methods for diagnosing and treating vascular-related diseases at present. It relies on achieving precise and safe navigation of intravascular tools within a patient’s vasculature. Vascular Interventional Surgical Robots (VISR) can reduce surgeons’ exposure to operational hazards including radiation. However, the absence of apt position control and force feedback remains a challenge. This study presents an isomorphic master–slave VISR for precise navigation of endovascular tools viz. catheters and guidewires. The master console aids operators in issuing manipulation commands and logs feedback from the force, rotation, and translation data. The slave manipulator uses the commands received from the master platform for actual tool navigation. However, precise master–slave position control and force feedback are precursors for optimal patient outcomes. This study utilized a fuzzy-PID controller for precise tool navigation and a neural network model for resistance force modulation with 50 mN precision. Furthermore, we evaluated the performance of using the learning-based models within our VISR and compared it with the performances from conventional methods. Results show that the models enhanced the proposed robotic system with better navigation precision, faster response speed, and improved force measurement capabilities.

Cardiovascular diseases (CVDs) are the leading cause of deaths in the world. The intricacies of the cellular composition and tissue microenvironment in heart and vasculature complicate the dissection of molecular mechanisms of CVDs. Over the past decade, the rapid development of single-cell omics technologies generated vast quantities of information at various biological levels, which have shed light on the cellular and molecular dynamics in cardiovascular development, homeostasis and diseases. Here, we summarize the latest single-cell omics techniques, and show how they have facilitated our understanding of cardiovascular biology. We also briefly discuss the clinical value and future outlook of single-cell applications in the field.

Abstract Background This study aimed to confirm that blocking RasGRP4 can effectively slow down the growth of DLBCL both in vitro and in vivo and ascertain the role of RasGRP4 in the prognosis of DLBCL clinically. Methods RasGRP4 expression levels were examined in benign tissues and lymphomas. In order to verify somatic mutation in RasGRP4 gene, cDNA sequencing was performed in DLBCL patients. RasGRP4-dependent cell proliferation, mitochondrial membrane potential, oxidative stress levels and signaling pathway changes were measured by knockdown of RasGRP4. Tumor growth was monitored in xenografted lymphoma model. Clinical data were collected to confirm the role of RasGRP4 in DLBCL. Results RasGRP4 expression was significantly elevated in DLBCL while no somatic mutations were detected of this gene in DLBCL patients. Decreased RasGRP4 significantly inhibited cell proliferation by simultaneously reducing mitosis and promoting apoptosis and increased the oxidative stress levels. Mechanistically, reduced expression of RasGRP4 decreased ERK while increased JNK expression in SUDHL-4 cells. Knockdown of RasGRP4 also significantly inhibited tumor formation in vivo. Furthermore, RasGRP4 expression levels were significantly higher in patients with larger DLBCL lesions (P = 0.0004), high-risk international prognostic index score groups (P = 0.0042), and its expression was positively correlated with maximum standardized uptake value in DLBCL (P = 0.0004). Conclusions These findings indicate the oncogenic role of RasGRP4 in DLBCL, suggesting it as a prognostic biomarker and potential therapeutic target in DLBCL.

The controllable preparation of silver nanowires (AgNWs) with a high aspect ratio is key for enabling their applications on a large scale. Herein, the aspect ratio regulation of AgNWs mediated by halogen ion composition in ethylene glycol system was systematically investigated and the size evolution mechanism is elaborately understood. The co-addition of Br− and Cl− results in AgNWs with the highest aspect ratio of 1031. The surface physicochemical analysis of AgNWs and the density functional theory calculations indicate that the co-addition of Br− and Cl− contributes to the much-enhanced preferential growth of the Ag(111) crystal plane. At the same time, when Cl− and Br− coexist in the solution, the growth of the Ag(100) crystal plane on the AgNWs was restrained compared with that in the single Cl− system. Resultantly, the enhanced growth of Ag(111) and the inhibited growth of Ag(100) contribute to the formation of AgNWs with a higher aspect ratio in the Cl–Br mixed solution. The results can provide new insights for understanding the morphology and size evolution during the AgNWs preparation in ethylene glycol system.

Community structure is a network characteristic where nodes can be naturally divided into densely connected groups. Community structures are ubiquitous in social, biological, and technological networks. Revealing community structure in the network helps in the understanding of the topological associations and interactions of elements in the network, as well as helping to mine their potential information. However, this has been proven to be a difficult challenge. On the one hand, this is because there is no unified definition of the quality of a community; on the other hand, due to the complexity of the network, it is impossible to traverse all the possibilities of community partitions to find the best one. Aiming at performing high-accuracy community detection, an information-theoretic approach AMI-NRL was proposed. The approach first constructs a community evolution process based on the representation of the target network, then finds the most stable community structure during the evolution using an average-mutual-information-based criterion. The experiments show that the approach can effectively detect community structures on real-world datasets and synthetic datasets.

Neuroinflammation contributes to or even causes central nervous system (CNS) diseases, and its regulation is thus crucial for brain disorders. Mast cells (MCs) and microglia, two resident immune cells in the brain, together with astrocytes, play critical roles in the progression of neuroinflammation-related diseases. MCs have been demonstrated as one of the fastest responders, and they release prestored and newly synthesized mediators including histamine, β-tryptase, and heparin. However, temporal changes in MC activation in this inflammation process remain unclear. This study demonstrated that MC activation began at 2 h and peaked at 4 h after lipopolysaccharide (LPS) administration. The number of activated MCs remained elevated until 24 h after LPS administration. In addition, the levels of histamine and β-tryptase in the hippocampus markedly and rapidly increased within 6 h and remained higher than the baseline level within 24 h after LPS challenge. Furthermore, mast cell-deficient KitW-sh/W-sh mice were used to investigate the effects of MCs on microglial and astrocytic activation and blood-brain barrier (BBB) permeability at 4 h after LPS stimulation. Notably, LPS-induced proinflammatory cytokine secretion, microglial activation, and BBB damage were inhibited in KitW-sh/W-sh mice. However, no detectable astrocytic changes were found in WT and KitW-sh/W-sh mice at 4 h after LPS stimulation. Our findings indicate that MC activation precedes CNS inflammation and suggest that MCs are among the earliest participants in the neuroinflammation-initiating events.

The cooperative control in complex multitasks using unmanned aerial vehicle and unmanned ground vehicle (UAV/UGV) is an important and challenging issue in the multirobot cooperative field. The main goal of the task studied in this paper is to minimize the time and energy consumed by the system to complete the assigned tasks. In this paper, a complex multitask problem using the hybrid UAV/UGV system is studied, which is divided into three stages, namely, the stage of finding the optimal locations of the relay stations for the UGV; the stage of solving the path planning problem for the UGV; and the stage of the task assignment for multi-UAVs. Furthermore, an improved integrated method is proposed to deal with the cooperative control problems in these three stages. Firstly, an adaptive clustering method is proposed to determine the locations of the UGV relay stations, and then an improved cuckoo search algorithm is used to find the shortest path for the UGV. Finally, a grouping method is presented to solve the multitask allocation problem of UAVs, based on an improved dynamic programming algorithm. In addition, some simulations are carried out and the results show that the proposed method has better performance when it comes to the time and energy consumption and can effectively guide the hybrid UAV/UGV system to carry out the complex multitasks.

Complex networks usually consist of dense-connected cliques, which are defined as communities. A community structure is a reflection of the local characteristics existing in the network topology, this makes community detection become an important research field to reveal the internal structural characteristics of networks. In this article, an information-based community detection approach MINC-NRL is proposed, which can be applied to both overlapping and non-overlapping community detection. MINC-NRL introduces network representation learning (NRL) to represent the target network as vectors, then generates a community evolution process based on these vectors to reduce the search space, and finally, finds the best community partition in this process using mutual information between network and communities (MINC). Experiments on real-world and synthetic data sets verifies the effectiveness of the approach in community detection, both on non-overlapping and overlapping tasks.

Objective MicroRNA-590-5p (miR-590-5p) has been reported to stimulate osteoblast differentiation; however, its effect in diabetic osteoporosis remains unknown. This study investigated the effect of miR-590-5p on high glucose (HG)-suppressed osteoblast differentiation. Methods The effect of HG on MC3T3-E1 cell survival was assessed using the MTT assay. The expression levels and activities of osteoblastic proteins were evaluated by quantitative reverse transcription polymerase chain reaction (qRT-PCR), alkaline phosphatase (ALP) assay, and immunoblotting assay. Tumor growth factor-β (TGF-β) signaling in MC3T3-E1 cells was assessed using luciferase assay, qRT-PCR, and immunoblotting. Mineralized nodule formation in MC3T3-E1 cells was examined by using the mineralization assay. Results When MC3T3-E1 cells were exposed to HG conditions, there was significant downregulation of miR-590-5p and osteoblastic proteins (e.g., collagen I, Runx2, and ALP); in contrast, Smad7 was upregulated. Furthermore, miR-590-5p targeted Smad7 and inhibited its expression. Additionally, overexpression of miR-590-5p significantly promoted osteoblast growth and differentiation by upregulating TGF-β signaling in HG-treated MC3T3-E1 cells. Conclusions Collectively, the results showed that miR-590-5p was involved in osteogenesis; moreover, miR-590-5p may represent a potential target for the treatment of diabetic osteoporosis.

Objective. To compare the effects of training of jaw and finger movements with and without visual feedback on precision and accuracy. Method. Twenty healthy participants (10 men and 10 women; mean age 24.6±0.8 years) performed two tasks: a jaw open-close movement and a finger lifting task with and without visual feedback before and after 3-day training. Individually determined target positions for the jaw corresponded to 50% of the maximal jaw opening position, and a fixed target position of 20 mm was set for the finger. Movements were repeated 10 times each. The variability in the amplitude of the movements was expressed as percentage in relation to the target position (Daccu—accuracy) and as coefficient of variation (CVprec—precision). Result. Daccu and CVprec were significantly influenced by visual feedback (P=0.001 and P

Self-driving cars are a hot research topic in science and technology, which has a great influence on social and economic development. Deep learning is one of the current key areas in the field of artificial intelligence research. It has been widely applied in image processing, natural language understanding, and so on. In recent years, more and more deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. This paper presents a review of recent research on theories and applications of deep learning for self-driving cars. This survey provides a detailed explanation of the developments of self-driving cars and summarizes the applications of deep learning methods in the field of self-driving cars. Then the main problems in self-driving cars and their solutions based on deep learning methods are analyzed, such as obstacle detection, scene recognition, lane detection, navigation and path planning. In addition, the details of some representative approaches for self-driving cars using deep learning methods are summarized. Finally, the future challenges in the applications of deep learning for self-driving cars are given out.

This study explored potential biomarkers associated with Lauren classification of gastric cancer. We screened microarray datasets on gastric cancer with information of Lauren classification in gene expression omnibus (GEO) database, and compared differentially expressing genes between intestinal-type or diffuse-type gastric cancer. Four sets of microarray data (GSE2669, GSE2680, GDS3438, and GDS4007) were enrolled into analysis. By differential gene analysis, UBE2C, CDH1, CENPF, ERO1L, SCD, SOX9, CKS1B, SPP1, MMP11, and ANLN were identified as the top genes related to intestinal-type gastric cancer, and MGP, FXYD1, FAT4, SIPA1L2, MUC5AC, MMP15, RAB23, FBLN1, ANXA10, and ADH1B were genes related to diffuse-type gastric cancer. We comprehensively validated the biological functions of the intestinal-type gastric cancer related gene UBE2C and evaluated its clinical significance on 1,868 cases of gastric cancer tissues from multiple medical centers of Shanghai, China. The gain of copy number on 20q was found in 4 out of 5 intestinal-type cancer cell lines, and no similar copy number variation (CNV) was found in any diffuse-type cancer cell line. Interfering UBE2C expression inhibited cell proliferation, migration and invasion in vitro, and tumorigenesis in vivo. Knockdown of UBE2C resulted in G2/M blockage in intestinal-type gastric cancer cells. Overexpression of UBE2C activated ERK signal pathway and promoted cancer cell proliferation. U0126, an inhibitor of ERK signaling pathway reversed the oncogenic phenotypes caused by UBE2C. Moreover, overexpression of UBE2C was identified in human intestinal-type gastric cancer. Overexpression of UBE2C protein predicted poor clinical outcome. Taken together, we characterized a group of Lauren classification-associated biomarkers, and clarified biological functions of UBE2C, an intestinal-type gastric cancer associated gene. Overexpression of UBE2C resulted in chromosomal instability that disturbed cell cycle and led to poor prognosis of intestinal-type gastric cancer.

Recent research has revealed that uncontrolled chronic neuroinflammation is closely associated with diverse neurodegenerative diseases, by impairing blood-brain barrier (BBB) function and astrocytic reaction. Endoplasmic reticulum (ER) stress is conventionally linked to the loss of neuronal structure and function and should be widely attenuated. This notion has been questioned by recent experimental studies, which have shown that non-harmful levels of ER stress had numerous beneficial roles against neurodegeneration, including neuroprotection and inhibition of cytokine production. Here, we investigated the mild ER stress-based regulation of LPS-induced inflammatory responses in astrocytes. Primary astrocytes were exposed to tunicamycin (TM), a compound that activates ER stress, with or without the ER-stress inhibitor sodium 4-phenylbutyrate (4-PBA) before LPS treatment. Astrocytic activation, proinflammatory factor production, and the extent of ER stress were assessed. In addition, the effect of mild ER stress on astrocytes and BBB function was determined in vivo. Male Sprague-Dawley rats received intracerebroventricular injections of TM with or without intraperitoneal 4-PBA before LPS administration. The levels of astrocytic activation and BBB permeability were measured after treatment. Our results showed that lower doses of TM resulted in a mild ER-stress response without inducing cytotoxicity and tissue toxicity. Non-toxic ER-stress preconditioning ameliorated LPS-induced overactivation and inflammatory responses in astrocytes. Moreover, pre-exposure to non-lethal doses of TM improved LPS-induced BBB impairment and cognitive ability dysfunction in rats. However, 4-PBA, reversed the protective effect of TM preconditioning in vitro and in vivo. We conclude that mild ER stress (“preconditioning”) can alleviate LPS-induced astrocytic activation and BBB disruption. Our findings provide a better understanding for the regulatory role of ER stress in neuroinflammation and indicate that mild ER stress might have therapeutic value for the treatment of neurodegenerative diseases.

EPS concrete was produced by mixing the expanded polystyrene spheres (EPS) and polymer emulsion and thickener to the matrix concrete, and this concrete had good vibration energy absorption characteristics. Based on the experimental data obtained on EPS volume ratio of 0%, 20%, 30%, and 40% by replacing matrix or coarse aggregate, the two design styles had nearly the same compressive strength. By applying frequency of 5 Hz, 50000 or 100000 times, 40 KN, 50 KN, and 60 KN cyclic loading, it is shown that the higher the inclusion size was, the lower the compressive strength of the EPS concrete would be; the larger the applying dynamic cyclic load was, the more obvious the compressive strength changing would be. Meanwhile, the strength of EPS concrete had no evident change after durability test. The results of this research had practical significance on using EPS concrete in some long-term cyclic dynamic load engineering.

There is much discussion in the cancer drug development community about how to incorporate molecular tools into early-stage clinical trials to assess target modulation, measure anti-tumor activity, and enrich the clinical trial population for patients who are more likely to benefit. Small, molecularly focused clinical studies offer the promise of the early definition of optimal biologic dose and patient population.Based on preclinical evidence that phosphatase and tensin homolog deleted on Chromosome 10 (PTEN) loss sensitizes tumors to the inhibition of mammalian target of rapamycin (mTOR), we conducted a proof-of-concept Phase I neoadjuvant trial of rapamycin in patients with recurrent glioblastoma, whose tumors lacked expression of the tumor suppressor PTEN. We aimed to assess the safety profile of daily rapamycin in patients with glioma, define the dose of rapamycin required for mTOR inhibition in tumor tissue, and evaluate the antiproliferative activity of rapamycin in PTEN-deficient glioblastoma. Although intratumoral rapamycin concentrations that were sufficient to inhibit mTOR in vitro were achieved in all patients, the magnitude of mTOR inhibition in tumor cells (measured by reduced ribosomal S6 protein phosphorylation) varied substantially. Tumor cell proliferation (measured by Ki-67 staining) was dramatically reduced in seven of 14 patients after 1 wk of rapamycin treatment and was associated with the magnitude of mTOR inhibition (p = 0.0047, Fisher exact test) but not the intratumoral rapamycin concentration. Tumor cells harvested from the Ki-67 nonresponders retained sensitivity to rapamycin ex vivo, indicating that clinical resistance to biochemical mTOR inhibition was not cell-intrinsic. Rapamycin treatment led to Akt activation in seven patients, presumably due to loss of negative feedback, and this activation was associated with shorter time-to-progression during post-surgical maintenance rapamycin therapy (p < 0.05, Logrank test).Rapamycin has anticancer activity in PTEN-deficient glioblastoma and warrants further clinical study alone or in combination with PI3K pathway inhibitors. The short-term treatment endpoints used in this neoadjuvant trial design identified the importance of monitoring target inhibition and negative feedback to guide future clinical development.http://www.ClinicalTrials.gov (#NCT00047073).