Publications by authors named "Lei Xing"

633 Publications

The Expression and Effect of ABCE1 in Gastric Adenocarcinoma.

Appl Biochem Biotechnol 2022 Jun 23. Epub 2022 Jun 23.

The First Department of Surgery, Chengde Third Hospital, Chengde, China.

ATP-binding cassette E1 (ABCE1) is mainly related to the regulation of viral infection, cell multiplication, and anti-apoptosis. Previous reports confirmed the central role in the regulation of ABCE1 in liver and breast cancer; however, its potential role in gastric adenocarcinoma remains unclear. In our study, siRNA and plasmid were transfected to construct gastric cancer cell lines with low and overexpression of ABCE1, and Western blot, RT-qPCR, and immunohistochemical staining were used to detect ABCE1 expression levels in gastric cancer tissues and cell lines. The effects of ABCE1 on cell growth, metastasis, invasion, cell cycle, and drug resistance were investigated using CCK-8 test, wound healing assay, and clone formation experiment. Functional experiments indicated that si-ABCE1 decreased the proliferation, metastasis, and invasion of gastric adenocarcinoma. Meanwhile, si-ABCE1 has significantly promoted EMT process and enhanced the sensitivity of paclitaxel and cisplatin. In vivo experiments also confirmed that si-ABCE1 group had significantly smaller tumors, and immunohistochemical staining results showed the tumor growth in si-ABCE1 group was reduced obviously. In summary, we found ABCE1 is considered as a crucial role in the evolution of gastric adenocarcinoma and could be a viable therapeutic target for the disease.
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http://dx.doi.org/10.1007/s12010-022-03986-6DOI Listing
June 2022

A geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction.

Comput Biol Med 2022 Jun 6:105710. Epub 2022 Jun 6.

Stanford University, Stanford, CA, 94305, USA. Electronic address:

Deep learning affords enormous opportunities to augment the armamentarium of biomedical imaging. However, the pure data-driven nature of deep learning models may limit the model generalizability and application scope. Here we establish a geometry-informed deep learning framework for ultra-sparse 3D tomographic image reconstruction. We introduce a novel mechanism for integrating geometric priors of the imaging system. We demonstrate that the seamless inclusion of known priors is essential to enhance the performance of 3D volumetric computed tomography imaging with ultra-sparse sampling. The study opens new avenues for data-driven biomedical imaging and promises to provide substantially improved imaging tools for various clinical imaging and image-guided interventions.
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http://dx.doi.org/10.1016/j.compbiomed.2022.105710DOI Listing
June 2022

Scheimpflug Camera-Based Technique for Multi-Point Displacement Monitoring of Bridges.

Sensors (Basel) 2022 May 27;22(11). Epub 2022 May 27.

School of Geosciences and Info-Physics, Central South University, Changsha 410083, China.

Owing to the limited field of view (FOV) and depth of field (DOF) of a conventional camera, it is quite difficult to employ a single conventional camera to simultaneously measure high-precision displacements at many points on a bridge of dozens or hundreds of meters. Researchers have attempted to obtain a large FOV and wide DOF by a multi-camera system; however, with the growth of the camera number, the cost, complexity and instability of multi-camera systems will increase exponentially. This study proposes a multi-point displacement measurement method for bridges based on a low-cost Scheimpflug camera. The Scheimpflug camera, which meets the Scheimpflug condition, can enlarge the depth of field of the camera without reducing the lens aperture and magnification; thus, when the measurement points are aligned in the depth direction, all points can be clearly observed in a single field of view with a high-power zoom lens. To reduce the impact of camera motions, a motion compensation method applied to the Scheimpflug camera is proposed according to the characteristic that the image plane is not perpendicular to the lens axis in the Scheimpflug camera. Several tests were conducted for performance verification under diverse settings. The results showed that the motion errors in and directions were reduced by at least 62% and 92%, respectively, using the proposed method, and the measurements of the camera were highly consistent with LiDAR-based measurements.
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http://dx.doi.org/10.3390/s22114093DOI Listing
May 2022

NeRP: Implicit Neural Representation Learning With Prior Embedding for Sparsely Sampled Image Reconstruction.

IEEE Trans Neural Netw Learn Syst 2022 Jun 3;PP. Epub 2022 Jun 3.

Image reconstruction is an inverse problem that solves for a computational image based on sampled sensor measurement. Sparsely sampled image reconstruction poses additional challenges due to limited measurements. In this work, we propose a methodology of implicit Neural Representation learning with Prior embedding (NeRP) to reconstruct a computational image from sparsely sampled measurements. The method differs fundamentally from previous deep learning-based image reconstruction approaches in that NeRP exploits the internal information in an image prior and the physics of the sparsely sampled measurements to produce a representation of the unknown subject. No large-scale data is required to train the NeRP except for a prior image and sparsely sampled measurements. In addition, we demonstrate that NeRP is a general methodology that generalizes to different imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). We also show that NeRP can robustly capture the subtle yet significant image changes required for assessing tumor progression.
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http://dx.doi.org/10.1109/TNNLS.2022.3177134DOI Listing
June 2022

Treatment planning system commissioning of the first clinical biology-guided radiotherapy machine.

J Appl Clin Med Phys 2022 May 29:e13638. Epub 2022 May 29.

Department of Radiation Oncology, Stanford University, Stanford, California, USA.

Purpose: The RefleXion X1 is a novel radiotherapy machine designed for image-guided radiotherapy (IGRT) and biology-guided radiotherapy (BgRT). Its treatment planning system (TPS) generates IMRT and SBRT plans for a 6MV-FFF beam delivered axially via 50 firing positions with the couch advancing every 2.1 mm. The purpose of this work is to report the TPS commissioning results for the first clinical installation of RefleXion™ X1.

Methods: CT images of multiple phantoms were imported into the RefleXion TPS to evaluate the accuracy of data transfer, anatomical modeling, plan evaluation, and dose calculation. Comparisons were made between the X1, Eclipse™, and MIM™. Dosimetric parameters for open static fields were evaluated in water and heterogeneous slab phantoms. Representative clinical IMRT and SBRT cases were planned and verified with ion chamber, film, and ArcCHECK measurements. The agreement between TPS and measurements for various clinical plans was evaluated using Gamma analysis with a criterion of 3%/2 mm for ArcCHECK and film. End-to-end (E2E) testing was performed using anthropomorphic head and lung phantoms.

Results: The average difference between the TPS-reported and known HU values was -1.4 ± 6.0 HU. For static fields, the agreements between the TPS-calculated and measured PDD , crossline profiles, and inline profiles (FWHM) were within 1.5%, 1.3%, and 0.5 mm, respectively. Measured output factors agreed with the TPS within 1.3%. Measured and calculated dose for static fields in heterogeneous phantoms agreed within 2.5%. The ArcCHECK mean absolute Gamma passing rate was 96.4% ± 3.4% for TG 119 and TG 244 plans and 97.8% ± 3.6% for the 21 clinical plans. E2E film analysis showed 0.8 mm total targeting error for isocentric and 1.1 mm for off-axis treatments.

Conclusions: The TPS commissioning results of the RefleXion X1 TPS were within the tolerances specified by AAPM TG 53, MPPG 5.a, TG 119, and TG 148. A subset of the commissioning tests has been identified as baseline data for an ongoing QA program.
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http://dx.doi.org/10.1002/acm2.13638DOI Listing
May 2022

Long noncoding RNA GK-IT1 promotes esophageal squamous cell carcinoma by regulating MAPK1 phosphorylation.

Cancer Med 2022 May 24. Epub 2022 May 24.

Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Background: Long noncoding RNAs (lncRNAs) are implicated in the oncogenesis and metastasis of multiple human cancers. Nonetheless, the precise molecular mechanisms underlying the oncogenic role of lncRNA in esophageal squamous cell carcinoma (ESCC) remains to be clarified.

Methods: The expression of GK intronic transcript 1 (GK-IT1) was analyzed using ESCC RNA-seq data from The Cancer Genome Atlas database. Quantitative real-time PCR was used to measure the expression of GK-IT1 in ESCC clinical samples and cells. The correlation between GK-IT1 expression and clinicopathological variables was examined using chi-squared tests. Kaplan-Meier survival and Cox regression analyses were employed to generate the survival curve and assess the prognostic value of GK-IT1. Functional experiments were utilized to explore the role of GK-IT1 in promoting cell migration, invasion, proliferation, and suppressing apoptosis and autophagy in ESCC. To understand the mechanism, an RNA pulldown assay, RNA immunoprecipitation, agarose gel electrophoresis, immunofluorescence, and co-immunoprecipitation assays were used.

Results: In this study we identified an unreported lncRNA, termed GK-IT1 that was aberrantly overexpressed in ESCC tissues and cells. GK-IT1 was closely associated with advanced clinical stage, and it was an independent prognostic indicator of ESCC. Functional assays verified that GK-IT1 significantly promoted ESCC proliferation, invasion, and migration, and suppressed ESCC apoptosis and autophagy. Furthermore, tumorigenesis experiments in nude mice indicated that GK-IT1 promoted ESCC tumor growth and metastasis. Mechanistically, GK-IT1 competitively bound to mitogen-activated protein kinase 1 (MAPK1) to prevent the interaction between dual specificity phosphatase 6 (DUSP6) and MAPK1, thereby controlling the phosphorylation of MAPK1 and promoting ESCC progression.

Conclusion: Our study revealed that GK-IT1 competed with DUSP6 to attenuate the interaction between DUSP6 and MAPK1, leading to activation of the ERK/MAPK pathway, thereby promoting progression of ESCC. Our research indicated that GK-IT1 served as a novel potential target for the diagnosis and treatment of ESCC.
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http://dx.doi.org/10.1002/cam4.4795DOI Listing
May 2022

Effect of the Acidity Coefficient on the Properties of Molten Modified Blast Furnace Slag and Those of the Produced Slag Fibers.

Materials (Basel) 2022 Apr 25;15(9). Epub 2022 Apr 25.

School of Metallurgy and Energy, North China University of Science and Technology, Tangshan 063009, China.

The online preparation of fibers using molten modified blast furnace slag can not only achieve the high-value-added utilization of the slag but can also make use of the sensible heat of the slag. In this paper, blast furnace slag was modified using iron tailings, and was then used to prepare slag fiber online; the effects of the acidity coefficient on the properties of the molten modified blast furnace slag and modified blast furnace slag fiber were investigated. With an increase in the acidity coefficient from 1.2 to 1.6, the temperature range of the slag melt, with viscosity in the 1-3 Pa·s range, increased from 101.2 °C to 119.9 °C. The melting temperature increased from 1326.2 °C to 1388.7 °C, and the suitable fiber-forming temperature range increased from 70.7 °C to 82.9 °C. With the increasing acidity coefficient, the crystallization temperature of the molten modified slag decreased markedly. When the acidity coefficient was greater than 1.4, the slag system was still in a disordered glassy phase at 1100 °C. The hardening speed gradually reduced with the increasing acidity coefficient when the modified slag was cooled at the critical cooling rate, resulting in a gradual increase in fiber formability. The fibers prepared from the modified slag at different acidity coefficients had smooth surfaces, and were arranged in a crossed manner at the macroscopic level. Their color was white, and small quantities of slag balls were doped inside the fibers. With an increase in the acidity coefficient from 1.2 to 1.6, the average fiber diameter increased from 4.2 μm to 8.2 μm, and their slag ball content increased from 0.73% to 4.49%. Overall, the acidity coefficient of modified blast furnace slag should be less than 1.5 in actual production.
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http://dx.doi.org/10.3390/ma15093113DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9103622PMC
April 2022

IMRT and SBRT Treatment Planning Study for the First Clinical Biology-Guided Radiotherapy System.

Technol Cancer Res Treat 2022 Jan-Dec;21:15330338221100231

Department of Radiation Oncology, 6429Stanford University, Stanford, CA, USA.

The first clinical biology-guided radiation therapy (BgRT) system-RefleXion X1-was installed and commissioned for clinical use at our institution. This study aimed at evaluating the treatment plan quality and delivery efficiency for IMRT/SBRT cases without PET guidance. A total of 42 patient plans across 6 cancer sites (conventionally fractionated lung, head, and neck, anus, prostate, brain, and lung SBRT) planned with the Eclipse treatment planning system (TPS) and treated with either a TrueBeam or Trilogy were selected for this retrospective study. For each Eclipse VMAT plan, 2 corresponding plans were generated on the X1 TPS with 10 mm jaws (X1-10mm) and 20 mm jaws (X1-20mm) using our institutional planning constraints. All clinically relevant metrics in this study, including PTV D95%, PTV D2%, Conformity Index (CI), R50, organs-at-risk (OAR) constraints, and beam-on time were analyzed and compared between 126 VMAT and RefleXion plans using paired -tests. All but 3 planning metrics were either equivalent or superior for the X1-10mm plans as compared to the Eclipse VMAT plans across all planning sites investigated. The Eclipse VMAT and X1-10mm plans generally achieved superior plan quality and sharper dose fall-off superior/inferior to targets as compared to the X1-20mm plans, however, the X1-20mm plans were still considered acceptable for treatment. On average, the required beam-on time increased by a factor of 1.6 across all sites for X1-10mm compared to X1-20mm plans. Clinically acceptable IMRT/SBRT treatment plans were generated with the X1 TPS for both the 10 mm and 20 mm jaw settings.
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http://dx.doi.org/10.1177/15330338221100231DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9118457PMC
May 2022

Nano-Graphene Layer from Facile, Scalable and Eco-Friendly Liquid Phase Exfoliation Strategy as Effective Barrier Layer for High-Performance and Durable Direct Liquid Alcohol Fuel Cells.

Molecules 2022 May 9;27(9). Epub 2022 May 9.

Institute for Energy Research, Jiangsu University, Zhenjiang 212013, China.

Graphene, in spite of exceptional physio-chemical properties, still faces great limitations in its use and industrial scale-up as highly selective membranes (enhanced ratio of proton conductivity to fuel cross-over) in liquid alcohol fuel cells (LAFCs), due to complexity and high cost of prevailing production methods. To resolve these issues, a facile, low-cost and eco-friendly approach of liquid phase exfoliation (bath sonication) of graphite to obtain graphene and spray depositing the prepared graphene flakes, above anode catalyst layer (near the membrane in the membrane electrode assembly (MEA)) as barrier layer at different weight percentages relative to the base membrane Nafion 115 was utilized in this work. The 5 wt.% nano-graphene layer raises 1 M methanol/oxygen fuel cell power density by 38% to 91 mW·cm, compared to standard membrane electrode assembly (MEA) performance of 63 mW·cm, owing to less methanol crossover with mild decrease in proton conductivity, showing negligible voltage decays over 20 h of operation at 50 mA·cm. Overall, this work opens three prominent favorable prospects: exploring the usage of nano-materials prepared by liquid phase exfoliation approach, their effective usage in ion-transport membrane region of MEA and enhancing fuel cell power performance.
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http://dx.doi.org/10.3390/molecules27093044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100842PMC
May 2022

High-performance cavity-enhanced quantum memory with warm atomic cell.

Nat Commun 2022 May 2;13(1):2368. Epub 2022 May 2.

State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Opto-Electronics, Shanxi University, Taiyuan, 030006, P. R. China.

High-performance quantum memory for quantized states of light is a prerequisite building block of quantum information technology. Despite great progresses of optical quantum memories based on interactions of light and atoms, physical features of these memories still cannot satisfy requirements for applications in practical quantum information systems, since all of them suffer from trade-off between memory efficiency and excess noise. Here, we report a high-performance cavity-enhanced electromagnetically-induced-transparency memory with warm atomic cell in which a scheme of optimizing the spatial and temporal modes based on the time-reversal approach is applied. The memory efficiency up to 67 ± 1% is directly measured and a noise level close to quantum noise limit is simultaneously reached. It has been experimentally demonstrated that the average fidelities for a set of input coherent states with different phases and amplitudes within a Gaussian distribution have exceeded the classical benchmark fidelities. Thus the realized quantum memory platform has been capable of preserving quantized optical states, and is ready to be applied in quantum information systems, such as distributed quantum logic gates and quantum-enhanced atomic magnetometry.
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http://dx.doi.org/10.1038/s41467-022-30077-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061733PMC
May 2022

Beam commissioning of the first clinical biology-guided radiotherapy system.

J Appl Clin Med Phys 2022 Jun 28;23(6):e13607. Epub 2022 Apr 28.

Department of Radiation Oncology, Stanford University, Stanford, California, USA.

This study reports the beam commissioning results for the first clinical RefleXion Linac.

Methods: The X1 produces a 6 MV photon beam and the maximum clinical field size is 40 × 2 cm at source-to-axis distance of 85 cm. Treatment fields are collimated by a binary multileaf collimator (MLC) system with 64 leaves with width of 0.625 cm and y-jaw pairs to provide either a 1 or 2 cm opening. The mechanical alignment of the radiation source, the y-jaw, and MLC were checked with film and ion chambers. The beam parameters were characterized using a diode detector in a compact water tank. In-air lateral profiles and in-water percentage depth dose (PDD) were measured for beam modeling of the treatment planning system (TPS). The lateral profiles, PDDs, and output factors were acquired for field sizes from 1.25 × 1 to 40 × 2 cm field to verify the beam modeling. The rotational output variation and synchronicity were tested to check the gantry angle, couch motion, and gantry rotation.

Results: The source misalignments were 0.049 mm in y-direction, 0.66% out-of-focus in x-direction. The divergence of the beam axis was 0.36 mm with a y-jaw twist of 0.03°. Clinical off-axis treatment fields shared a common center in y-direction were within 0.03 mm. The MLC misalignment and twist were 0.57 mm and 0.15°. For all measured fields ranging from the size from 1.25 × 1 to 40 × 2 cm , the mean difference between measured and TPS modeled PDD at 10 cm depth was -0.3%. The mean transverse profile difference in the field core was -0.3% ± 1.1%. The full-width half maximum (FWHM) modeling was within 0.5 mm. The measured output factors agreed with TPS within 0.8%.

Conclusions: This study summarizes our specific experience commissioning the first novel RefleXion linac, which may assist future users of this technology when implementing it into their own clinics.
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http://dx.doi.org/10.1002/acm2.13607DOI Listing
June 2022

Influence of Association Network Properties and Ecological Assembly of the Foliar Fugal Community on Crop Quality.

Front Microbiol 2022 5;13:783923. Epub 2022 Apr 5.

College of Agronomy, Hunan Agricultural University, Changsha, China.

Revealing community assembly and their impacts on ecosystem service is a core issue in microbial ecology. However, what ecological factors play dominant roles in phyllosphere fungal community assembly and how they link to crop quality are largely unknown. Here, we applied internal transcriptional spacer high-throughput sequencing to investigate foliar fungal community assembly across three cultivars of a Solanaceae crop (tobacco) and two planting regions with different climatic conditions. Network analyses were used to reveal the pattern in foliar fungal co-occurrence, and phylogenetic null model analysis was used to elucidate the ecological assembly of foliar fungal communities. We found that the sensory quality of crop leaves and the composition of foliar fungal community varied significantly across planting regions and cultivars. In Guangcun (GC), a region with relatively high humidity and low precipitation, there was a higher diversity and more unique fungal species than the region of Wuzhishan (WZS). Further, we found that the association network of foliar fungal communities in GC was more complex than that in WZS, and the network properties were closely related to the sensory quality of crop. Finally, the results of the phylogenetic analyses show that the stochastic processes played important roles in the foliar fungal community assembly, and their relative importance was significantly correlated with the sensory quality of crop leaves, which implies that ecological assembly processes could affect crop quality. Taken together, our results highlight that climatic conditions, and plant cultivars play key roles in the assembly of foliar fungal communities and crop quality, which enhances our understanding of the connections between the phyllosphere microbiome and ecosystem services, especially in agricultural production.
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http://dx.doi.org/10.3389/fmicb.2022.783923DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9037085PMC
April 2022

Implicit neural representation for radiation therapy dose distribution.

Phys Med Biol 2022 06 13;67(12). Epub 2022 Jun 13.

Department of Electrical Engineering, Stanford University, Stanford, CA 94305, United States of America.

. Dose distribution data plays a pivotal role in radiotherapy treatment planning. The data is typically represented using voxel grids, and its size ranges from 10to 10. A concise representation of the treatment plan is of great value in facilitating treatment planning and downstream applications. This work aims to develop an implicit neural representation of 3D dose distribution data.. Instead of storing the dose values at each voxel, in the proposed approach, the weights of a multilayer perceptron (MLP) are employed to characterize the dosimetric data for plan representation and subsequent applications. We train a coordinate-based MLP with sinusoidal activations to map the voxel spatial coordinates to the corresponding dose values. We identify the best architecture for a given parameter budget and use that to train a model for each patient. The trained MLP is evaluated at each voxel location to reconstruct the dose distribution. We perform extensive experiments on dose distributions of prostate, spine, and head and neck tumor cases to evaluate the quality of the proposed representation. We also study the change in representation quality by varying model size and activation function.. Using coordinate-based MLPs with sinusoidal activations, we can learn implicit representations that achieve a mean-squared error of 10and peak signal-to-noise ratio greater than 50 dB at a target bitrate of ∼1 across all the datasets, with a compression ratio of ∼32. Our results also show that model sizes with a bitrate of 1-2 achieve optimal accuracy. For smaller bitrates, performance starts to drop significantly.. The proposed model provides a low-dimensional, implicit, and continuous representation of 3D dose data. In summary, given a dose distribution, we systematically show how to find a compact model to fit the data accurately. This study lays the groundwork for future applications of neural representations of dose data in radiation oncology.
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http://dx.doi.org/10.1088/1361-6560/ac6b10DOI Listing
June 2022

Predicting peritoneal recurrence and disease-free survival from CT images in gastric cancer with multitask deep learning: a retrospective study.

Lancet Digit Health 2022 05;4(5):e340-e350

Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA. Electronic address:

Background: Peritoneal recurrence is the predominant pattern of relapse after curative-intent surgery for gastric cancer and portends a dismal prognosis. Accurate individualised prediction of peritoneal recurrence is crucial to identify patients who might benefit from intensive treatment. We aimed to develop predictive models for peritoneal recurrence and prognosis in gastric cancer.

Methods: In this retrospective multi-institution study of 2320 patients, we developed a multitask deep learning model for the simultaneous prediction of peritoneal recurrence and disease-free survival using preoperative CT images. Patients in the training cohort (n=510) and the internal validation cohort (n=767) were recruited from Southern Medical University, Guangzhou, China. Patients in the external validation cohort (n=1043) were recruited from Sun Yat-sen University Cancer Center, Guangzhou, China. We evaluated the prognostic accuracy of the model as well as its association with chemotherapy response. Furthermore, we assessed whether the model could improve the ability of clinicians to predict peritoneal recurrence.

Findings: The deep learning model had a consistently high accuracy in predicting peritoneal recurrence in the training cohort (area under the receiver operating characteristic curve [AUC] 0·857; 95% CI 0·826-0·889), internal validation cohort (0·856; 0·829-0·882), and external validation cohort (0·843; 0·819-0·866). When informed by the artificial intelligence (AI) model, the sensitivity and inter-rater agreement of oncologists for predicting peritoneal recurrence was improved. The model was able to predict disease-free survival in the training cohort (C-index 0·654; 95% CI 0·616-0·691), internal validation cohort (0·668; 0·643-0·693), and external validation cohort (0·610; 0·583-0·636). In multivariable analysis, the model predicted peritoneal recurrence and disease-free survival independently of clinicopathological variables (p<0·0001 for all). For patients with a predicted high risk of peritoneal recurrence and low survival, adjuvant chemotherapy was associated with improved disease-free survival in both stage II disease (hazard ratio [HR] 0·543 [95% CI 0·362-0·815]; p=0·003) and stage III disease (0·531 [0·432-0·652]; p<0·0001). By contrast, chemotherapy had no impact on disease-free survival for patients with a predicted low risk of peritoneal recurrence and high survival. For the remaining patients, the benefit of chemotherapy depended on stage: only those with stage III disease derived benefit from chemotherapy (HR 0·637 [95% CI 0·484-0·838]; p=0·001).

Interpretation: The deep learning model could allow accurate prediction of peritoneal recurrence and survival in patients with gastric cancer. Prospective studies are required to test the clinical utility of this model in guiding personalised treatment in combination with clinicopathological criteria.

Funding: None.
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http://dx.doi.org/10.1016/S2589-7500(22)00040-1DOI Listing
May 2022

Hypoxia-induced circWSB1 promotes breast cancer progression through destabilizing p53 by interacting with USP10.

Mol Cancer 2022 03 29;21(1):88. Epub 2022 Mar 29.

Department of Cell Biology and Genetics, Chongqing Medical University, #1 Yixueyuan Road, Chongqing, 400016, China.

Background: Hypoxia has long been considered as a hallmark of solid tumors and is closely associated with tumor progression. Circular RNAs (circRNAs) have been identified as a critical modulator in various cancers. However, the connections between hypoxia and circRNAs are largely unknown.

Methods: Here, we investigated the expression profile of circRNAs in breast cancer (BC) MCF-7 cells under hypoxia and normoxia using microarray. We identified a novel hypoxia-responsive circRNA named circWSB1, whose expression pattern, potential diagnostic value and prognostic significance were assessed by qRT-PCR and in situ hybridization. Loss- and gain-of-function investigations in vivo and in vitro were performed to determine the biological functions of circWSB1. Mechanistically, chromatin immunoprecipitation and dual luciferase reporter assays were carried out to analyze the biogenesis of circWSB1. Furthermore, biotin-labeled RNA pull-down, mass spectrometry, RNA immunoprecipitation, fluorescent in situ hybridization, RNA electrophoretic mobility shift, deletion-mapping, co-immunoprecipitation assays and rescue experiments were applied to investigate the interaction between circWSB1 and Ubiquitin-specific peptidase 10 (USP10) as well as the relationship between USP10 and p53.

Results: We found that the expression of circWSB1 was significantly upregulated in BC tissues and correlated with poor clinical outcomes, which might serve as an independent prognostic factor for BC patients. Ectopic expression of circWSB1 promoted the proliferation of BC cell in vitro and in vivo. Mechanistically, circWSB1 was transcriptionally upregulated by HIF1α in response to hypoxia and could competitively bind to deubiquitinase USP10 to prevent the access of p53 to USP10 in BC cells, leading to degradation of p53 and tumor progression of BC.

Conclusions: Taken together, our findings disclose a novel mechanism that hypoxia-inducible circWSB1 could interact with USP10 to attenuate USP10 mediated p53 stabilization and promote the progression of BC, providing an alternative prognostic biomarker and therapeutic target for BC.
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http://dx.doi.org/10.1186/s12943-022-01567-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961958PMC
March 2022

Construction of Confined Bifunctional 2D Material for Efficient Sulfur Resource Recovery and Hg Adsorption in Desulfurization.

Environ Sci Technol 2022 04 24;56(7):4531-4541. Epub 2022 Feb 24.

MOE Key Laboratory of Resources and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing, 102206, P. R. China.

Substantial energy penalty of valuable sulfate recovery restricts the efficiency of wet desulfurization and increases the risk of Hg reemission. Although the enhanced sulfite oxidation rate with cobalt-based materials can increase the energy efficiency, inactivation and poisoning of catalyst due to the competition of reactant must be addressed. Here we obtained a superwetting two-dimensional cobalt-nitrogen-doped carbon (2D Co-N-C) nanosheet featuring confined catalysis/adsorption sites for the energy-efficient sulfite oxidation and Hg adsorption. The designed structure exhibits enhanced surface polarity, availability and short reactant diffusion path, thus enabling the significant catalytic TOF value of 0.085 s and simultaneous mercury removal ability of 143.26 mg·g. The catalyst nanosheets present regenerating stabilities to improve cost-efficiency. By deployment of the Co-N-C catalysts, a marked reduction of heat penalty up to 69% can be achieved, which makes this catalytic pathway for sulfur resource recovery economically feasible in real industry scenario.
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http://dx.doi.org/10.1021/acs.est.2c00377DOI Listing
April 2022

Mechanoporation enables rapid and efficient radiolabeling of stem cells for PET imaging.

Sci Rep 2022 02 22;12(1):2955. Epub 2022 Feb 22.

Division of Medical Physics, Department of Radiation Oncology, School of Medicine, Stanford University, Stanford, CA, 94305, USA.

Regenerative medicine uses the patient own stem cells to regenerate damaged tissues. Molecular imaging techniques are commonly used to image the transplanted cells, either right after surgery or at a later time. However, few techniques are fast or straightforward enough to label cells intraoperatively. Adipose tissue-derived stem cells (ADSCs) were harvested from knee joints of minipigs. The cells were labeled with PET contrast agent by flowing mechanoporation using a microfluidic device. While flowing through a series of microchannels, cells are compressed repeatedly by micro-ridges, which open transient pores in their membranes and induce convective transport, intended to facilitate the transport of Ga-labeled and lipid-coated mesoporous nanoparticles (MSNs) into the cells. This process enables cells to be labeled in a matter of seconds. Cells labeled with this approach were then implanted into cartilage defects, and the implant was imaged using positron emission tomography (PET) post-surgery. The microfluidic device can efficiently label millions of cells with Ga-labeled MSNs in as little as 15 min. The method achieved labeling efficiency greater than 5 Bq/cell on average, comparable to 30 min-long passive co-incubation with Ga-MSNs, but with improved biocompatibility due to the reduced exposure to ionizing radiation. Labeling time could also be accelerated by increasing throughput through more parallel channels. Finally, as a proof of concept, ADSCs were labeled with Ga-MSNs and quantitatively assessed using clinical PET/MR in a mock transplant operation in pig knee joints. MSN-assisted mechanoporation is a rapid, effective and straightforward approach to label cells with Ga. Given its high efficiency, this labeling method can be used to track small cells populations without significant effects on viability. The system is applicable to a variety of cell tracking studies for cancer therapy, regenerative therapy, and immunotherapy.
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http://dx.doi.org/10.1038/s41598-022-06938-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863797PMC
February 2022

Meta-optimization for fully automated radiation therapy treatment planning.

Phys Med Biol 2022 03 3;67(5). Epub 2022 Mar 3.

Department of Radiation Oncology, Stanford University, Stanford, United States of America.

. Radiation therapy treatment planning is a time-consuming process involving iterative adjustments of hyperparameters. To automate the treatment planning process, we propose a meta-optimization framework, called MetaPlanner (MP).. Our MP algorithm automates planning by performing meta-optimization of treatment planning hyperparameters. The algorithm uses a derivative-free method (i.e. parallel Nelder-Mead simplex search) to search for weight configurations that minimize a meta-scoring function. Meta-scoring is performed by constructing a tier list of the relevant considerations (e.g. dose homogeneity, conformity, spillage, and OAR sparing) to mimic the clinical decision-making process. Additionally, we have made our source code publicly available via github.. The proposed MP method is evaluated on two datasets (21 prostate cases and 6 head and neck cases) collected as part of clinical workflow. MP is applied to both IMRT and VMAT planning and compared to a baseline of manual VMAT plans. MP in both IMRT and VMAT scenarios has comparable or better performance than manual VMAT planning for all evaluated metrics.. Our proposed MP provides a general framework for fully automated treatment planning that produces high quality treatment plans. Our MP method promises to substantially reduce the workload of treatment planners while maintaining or improving plan quality.
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http://dx.doi.org/10.1088/1361-6560/ac5672DOI Listing
March 2022

Novel-view X-ray projection synthesis through geometry-integrated deep learning.

Med Image Anal 2022 04 29;77:102372. Epub 2022 Jan 29.

Department of Electrical Engineering, Stanford University, Stanford, CA, USA; Department of Radiation Oncology, Stanford University, Stanford, CA, USA.

X-ray imaging is a widely used approach to view the internal structure of a subject for clinical diagnosis, image-guided interventions and decision-making. The X-ray projections acquired at different view angles provide complementary information of patient's anatomy and are required for stereoscopic or volumetric imaging of the subject. In reality, obtaining multiple-view projections inevitably increases radiation dose and complicates clinical workflow. Here we investigate a strategy of obtaining the X-ray projection image at a novel view angle from a given projection image at a specific view angle to alleviate the need for actual projection measurement. Specifically, a Deep Learning-based Geometry-Integrated Projection Synthesis (DL-GIPS) framework is proposed for the generation of novel-view X-ray projections. The proposed deep learning model extracts geometry and texture features from a source-view projection, and then conducts geometry transformation on the geometry features to accommodate the change of view angle. At the final stage, the X-ray projection in the target view is synthesized from the transformed geometry and the shared texture features via an image generator. The feasibility and potential impact of the proposed DL-GIPS model are demonstrated using lung imaging cases. The proposed strategy can be generalized to a general case of multiple projections synthesis from multiple input views and potentially provides a new paradigm for various stereoscopic and volumetric imaging with substantially reduced efforts in data acquisition.
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http://dx.doi.org/10.1016/j.media.2022.102372DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8916089PMC
April 2022

Generation of a pdmH1N1 2018 Influenza A Reporter Virus Carrying a mCherry Fluorescent Protein in the PA Segment.

Front Cell Infect Microbiol 2021 20;11:827790. Epub 2022 Jan 20.

State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Influenza A virus (IAV) is a major human pathogen associated with significant morbidity and mortality worldwide. Through serial passage in mice, we generated a recombinant pdmH1N1 2009 IAV, A/Guangdong/GLW/2018 (GLW/18-MA), which encodes an mCherry gene fused to the C-terminal of a polymerase acidic (PA) segment and demonstrated comparable growth kinetics to the wild-type. Nine mutations were identified in the GLW/18-MA genome: PA (I61M, E351G, and G631S), NP (E292G), HA1 (T164I), HA2 (N117S and P160S), NA (W61R), and NEP (K44R). The recombinant IAV reporter expresses mCherry, a red fluorescent protein, at a high level and maintains its genetic integrity after five generations of serial passages in Madin-Darby Canine Kidney cells (MDCK) cells. Moreover, the imaging is noninvasive and permits the monitoring of infection in living mice. Treatment with oseltamivir or baicalin followed by infection with the reporter IAV led to a decrease in fluorescent protein signal in living mice. This result demonstrates that the IAV reporter virus is a powerful tool to study viral pathogenicity and transmission and to develop and evaluate novel anti-viral drugs, inhibitors, and vaccines in the future.
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http://dx.doi.org/10.3389/fcimb.2021.827790DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8811159PMC
April 2022

Attention-guided deep learning for gestational age prediction using fetal brain MRI.

Sci Rep 2022 01 26;12(1):1408. Epub 2022 Jan 26.

Department of Radiology, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, USA.

Magnetic resonance imaging offers unrivaled visualization of the fetal brain, forming the basis for establishing age-specific morphologic milestones. However, gauging age-appropriate neural development remains a difficult task due to the constantly changing appearance of the fetal brain, variable image quality, and frequent motion artifacts. Here we present an end-to-end, attention-guided deep learning model that predicts gestational age with R score of 0.945, mean absolute error of 6.7 days, and concordance correlation coefficient of 0.970. The convolutional neural network was trained on a heterogeneous dataset of 741 developmentally normal fetal brain images ranging from 19 to 39 weeks in gestational age. We also demonstrate model performance and generalizability using independent datasets from four academic institutions across the U.S. and Turkey with R scores of 0.81-0.90 after minimal fine-tuning. The proposed regression algorithm provides an automated machine-enabled tool with the potential to better characterize in utero neurodevelopment and guide real-time gestational age estimation after the first trimester.
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http://dx.doi.org/10.1038/s41598-022-05468-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8791965PMC
January 2022

Experiment and simulation of flexible CNT/SA/PDMS electromagnetic shielding composite.

Nanotechnology 2022 Feb 1;33(17). Epub 2022 Feb 1.

School of Materials Science and Engineering, Central South University, Hunan, Changsha 410083, People's Republic of China.

Flexible electromagnetic shielding composites have a great potential for wide range applications. In this study, two flexible composites were produced by plating Ni nanoparticles on carbon nanotubes (CNTs) or infiltrating carbon nanofibers/polydimethylsiloxane (CNF/PDMS) polymer into CNT/sodium alginate (CNT/SA) sponge skeleton (CNT/SA/CNF/PDMS composites). The composites are tested under the X band in the frequency range of 8.2 - 12.4 GHz, the electromagnetic interference shielding effectiveness (EMI-SE) values of the above two composites are almost as twice as that of CNT/SA/PDMS composite at a same CNT loading. Introducing nano-sized Ni particles on CNT improved the microwave absorption capacity of the composite, while adding CNF on the PDMS matrix enhanced the conductivity of these composites. Under 10% strain, both flexible composites show stable conductivity. Simulation and calculation results shown that increasing the cladding rate of Ni nanoparticles on the surface of CNT, reducing the average size of Ni particles, and increasing the loading of CNF in PDMS matrix can significantly improve conductivity and then EMI performance of the materials. All of these could benefit for the design of flexible electromagnetic shielding composites.
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http://dx.doi.org/10.1088/1361-6528/ac4c16DOI Listing
February 2022

Correction: Blood compatibility of a new zwitterionic bare metal stent with hyperbranched polymer brushes.

J Mater Chem B 2022 Jan 19;10(3):478. Epub 2022 Jan 19.

Biofunctional Materials, College of Chemistry and Materials Science, Nanjing Normal University, Nanjing 210023, P. R. China.

Correction for 'Blood compatibility of a new zwitterionic bare metal stent with hyperbranched polymer brushes' by Xiaobo Wang , , 2013, , 5036-5044, DOI: 10.1039/C3TB20855A.
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http://dx.doi.org/10.1039/d1tb90187gDOI Listing
January 2022

Two new compounds from edible mushroom .

Nat Prod Res 2022 Jan 6:1-7. Epub 2022 Jan 6.

Internationally Cooperative Research Center of China for New Germplasm Breeding of Edible Mushroom, Ministry of Science and Technology, Jilin Agricultural University, Changchun, PR China.

Chemical investigation of the edible mushroom led to the isolation of one new highly degraded sterol (), and one new β-carboline alkaloid (), along with nine known compounds (-) for the first time from this mushroom. The structures of new compounds were elucidated using HR-ESI-MS data and NMR spectroscopy. In addition, anti-inflammatory activity of new compounds was evaluated against lipopolysaccharide-induced NO production in RAW 264.7 macrophages. Compound exhibited a good anti-inflammatory activity with IC value of 9.88 ± 0.48 μM, and compound exhibited a weak inhibitory effect with IC value of 71.36 ± 5.11 μM.
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http://dx.doi.org/10.1080/14786419.2021.2023146DOI Listing
January 2022

Relationship between non-culprit lesion plaque characteristics changes and in-stent neoatherosclerosis formation: 1-year follow-up optical coherence tomography study.

Rev Cardiovasc Med 2021 Dec;22(4):1693-1700

Department of Cardiology, The Second Affiliated Hospital of Harbin Medical University, The Key Laboratory of Myocardial Ischemia, Chinese Ministry of Education, 150000 Harbin, Heilongjiang, China.

The relationship between the in-stent neoatherosclerosis (ISNA) formation and the plaque's characteristic changes in the non-culprit lesion is unclear. We aim to investigate the plaque characteristics changes at non-culprit lesions between patients with ISNA and without ISNA formation at 1-year follow-up. We retrospectively enrolled patients who had DES implantation in de novo lesion and underwent immediately after stenting and 1-year follow-up optical coherence tomography (OCT) examination. OCT-defined ISNA was defined as the presence of lipid-laden neointima or calcification within the culprit stent with a longitudinal extension of ≥1 mm. Non-culprit lesions were divided into two groups: ISNA group (with ISNA) and non-ISNA group (without ISNA). Plaque characteristics of non-culprit lesions were evaluated at baseline and 1-year follow-up. In total, 89 patients with 89 non-culprit lesions (ISNA: n = 37; non-ISNA: n = 52) were included in the analyses. The lesions in the ISNA group show a smaller minimum lumen area compared to the non-ISNA group at 1-year follow-up (2.57 ± 1.08 mm versus 3.20 ± 1.62 mm, = 0.044). The lesions of the ISNA group show a significant decrease in minimum lumen area changes percent (-7.25% versus 6.46%, = 0.039). And there are more lesions with minimum lumen area (64.9% versus 38.5%, = 0.014) and minimum lumen diameter (64.9% versus 40.4%, = 0.023) decrease in the ISNA group. Furthermore, the lesions in ISNA group have more plaques with lipid core length increase (25.0% versus 10.0%, = 0.040), more plaques with FCT decrease (50.0% versus 74.0%, = 0.027) and less TCFA change to non-TCFA (33.3% versus 87.5%, = 0.010). The plaque characteristic changes in non-culprit lesions are closely related to ISNA formation. The ISNA formation may accompany by a tardier plaque stabilization process in non-culprit lesions.
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http://dx.doi.org/10.31083/j.rcm2204177DOI Listing
December 2021

Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy.

Comput Biol Med 2022 02 17;141:105139. Epub 2021 Dec 17.

Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA. Electronic address:

Purpose: To develop a deep unsupervised learning method with control volume (CV) mapping from patient positioning daily CT (dCT) to planning computed tomography (pCT) for precise patient positioning.

Methods: We propose an unsupervised learning framework, which maps CVs from dCT to pCT to automatically generate the couch shifts, including translation and rotation dimensions. The network inputs are dCT, pCT and CV positions in the pCT. The output is the transformation parameter of the dCT used to setup the head and neck cancer (HNC) patients. The network is trained to maximize image similarity between the CV in the pCT and the CV in the dCT. A total of 554 CT scans from 158 HNC patients were used for the evaluation of the proposed model. At different points in time, each patient had many CT scans. Couch shifts are calculated for the testing by averaging the translation and rotation from the CVs. The ground-truth of the shifts come from bone landmarks determined by an experienced radiation oncologist.

Results: The system positioning errors of translation and rotation are less than 0.47 mm and 0.17°, respectively. The random positioning errors of translation and rotation are less than 1.13 mm and 0.29°, respectively. The proposed method enhanced the proportion of cases registered within a preset tolerance (2.0 mm/1.0°) from 66.67% to 90.91% as compared to standard registrations.

Conclusions: We proposed a deep unsupervised learning architecture for patient positioning with inclusion of CVs mapping, which weights the CVs regions differently to mitigate any potential adverse influence of image artifacts on the registration. Our experimental results show that the proposed method achieved efficient and effective HNC patient positioning.
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http://dx.doi.org/10.1016/j.compbiomed.2021.105139DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8810749PMC
February 2022

Efficacy and Safety of Adding Immune Checkpoint Inhibitors to Neoadjuvant Chemotherapy Against Triple-Negative Breast Cancer: A Meta-Analysis of Randomized Controlled Trials.

Front Oncol 2021 29;11:657634. Epub 2021 Nov 29.

Department of Endocrine and Breast Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Background: Immune checkpoint inhibitors (ICIs) have shown promising anti-tumor activity in multiple malignances including breast cancer. However, the responses can vary. This meta-analysis was conducted to evaluate the efficacy and safety profile of adding ICIs to neoadjuvant chemotherapy against triple-negative breast cancer (TNBC) and assess correlation of PD-L1 tumor status with responses.

Methods: Eligible studies were retrieved from the PubMed, Embase, and Web of Science databases. Randomized controlled trials (RCTs) that investigated ICI-containing ICI-free neoadjuvant therapy were included in this study. Meta-analyses were performed using Review Manager Version 5.2 software.

Results: This study included four RCTs containing 1795 patients with early TNBC. Compared with ICI-free neoadjuvant therapy, ICI-containing neoadjuvant therapy significantly increased the pathological complete response (pCR) rates in TNBC (odds ratio [OR] = 2.14, 95% confidence interval [CI]: 1.37-3.35, < 0.001). In subgroup analysis, the addition of ICI to neoadjuvant chemotherapy was significantly associated with increased pCR rate in both PD-L1-positive TNBC (OR = 1.79, 95% CI: 1.33-2.41, < 0.001) and PD-L1-negative TNBC (OR = 1.84, 95% CI: 1.14-2.99, = 0.01). Patients with TNBC receiving ICI-containing neoadjuvant therapy had a better event-free survival (hazard ratio = 0.66, 95% CI: 0.48-0.89, = 0.007) than those who receiving ICI-free neoadjuvant therapy. A significantly higher risk of adverse events including adrenal insufficiency, increased aspartate aminotransferase, dry skin, hepatitis, hyperthyroidism, hypothyroidism, infusion related reaction, pyrexia, and stomatitis was associated with ICI-containing neoadjuvant therapy.

Conclusion: ICI-containing neoadjuvant therapy significantly increased the pCR rate in TNBC patients, independently of PD-L1 status. The addition of ICI to neoadjuvant chemotherapy may be considered an option for TNBC patients.
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http://dx.doi.org/10.3389/fonc.2021.657634DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8667776PMC
November 2021

Enhanced nuclear gene delivery via integrating and streamlining intracellular pathway.

J Control Release 2022 01 2;341:511-523. Epub 2021 Dec 2.

State Key Laboratory of Natural Medicines, Department of Pharmaceutics, China Pharmaceutical University, Nanjing 210009, China; Jiangsu Key Laboratory of Druggability of Biopharmaceuticals, China Pharmaceutical University, Nanjing 210009, China; Jiangsu Key Laboratory of Drug Screening, China Pharmaceutical University, Nanjing 210009, China; NMPA Key Laboratory for Research and Evaluation of Pharmaceutical Preparations and Excipients, China Pharmaceutical University, Nanjing 210009, China. Electronic address:

The essential challenge of gene therapy is to develop safe and efficient vectors that escort genes to target sites. However, due to the cumbersome workflow of gene transfection into cells, successive gene loss occurs. This leads to considerable reductions in nuclear gene uptake, eventually causing low gene expression. Herein, we designed a gene vector named CAS (C: N,N'-cystamine-bis-acrylamide [CBA], A: agmatine dihydrochloride [Agm], S: 4-(2-aminoethyl) benzenesulfonamide [ABS]) with excellent gene transfection ability. This vector can promote gene delivery to the nucleus via enhanced endoplasmic reticulum (ER) targeting through integrating and streamlining of the complex intracellular pathway. Briefly, ABS endowed CAS/DNA nanoparticles with not only a natural ER-targeting tendency attributed to the caveolae-mediated pathway but also direct receptor-binding capacity on the ER surface. Agm enabled CAS to enhance lysosomal escape and nuclear uptake ability. The gene delivery efficiency of CAS was significantly better than that of polyethyleneimine 25K (PEI 25K). Therefore, CAS is a promising gene carrier, and the ER-targeting strategy involving intracellular pathway integration and streamlining has potential for gene therapy.
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http://dx.doi.org/10.1016/j.jconrel.2021.11.046DOI Listing
January 2022

Characterization of excipients to improve pharmaceutical properties of sirolimus in the supercritical anti-solvent fluidized process.

Int J Pharm 2022 Jan 13;611:121240. Epub 2021 Nov 13.

The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou 510405, PR China. Electronic address:

Enhanced drug release and bioavailability of poorly soluble active pharmaceutical ingredient (API) can be achieved via a fluidized bed coating integrated with supercritical anti-solvent (SAS-FB) - a process of precipitating drug particles onto carrier granules. However, in the absence of excipients, SAS-FB often results in crystalline of the API on the surface of carriers, limiting the improvement of pharmaceutical properties. Co-processing with excipients is considered an effective approach to improve drug release in the SAS-FB process. Our study used sirolimus, an immune suppressive agent, as the model API to characterize excipients for their effect on pharmaceutical properties in the SAS-FB process. We show that co-precipitation of excipients and sirolumus impacts on carrier specific surface area and drug yield. Among the tested excipients, formulation containing polyvinylpyrrolidone K30 achieved the highest drug yield. Importantly, compared with Rapamune® tablet, our optimized formulation displayed a superior in vivo oral bioavailability by 3.05-fold in Sprague-Dawley rats and 3.99-fold in beagle dogs. A series of characterization of the processed API was performed to understand the mechanism by which excipients contributed to drug dissolution properties. Our study provides a useful guidance for the use of excipients in the SAS-FB technology to improve pharmaceutical properties of sirolimus and other poorly soluble drugs.
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http://dx.doi.org/10.1016/j.ijpharm.2021.121240DOI Listing
January 2022

Case Report: Primary Bilateral Minimally Invasive Adenocarcinoma of the Lungs in an 11-Year-Old Child: A Rare Case.

Front Surg 2021 26;8:741744. Epub 2021 Oct 26.

Department of Radiology, Taizhou First People's Hospital of Zhejiang Province, Taizhou, China.

There are many types of benign and malignant tissue, but primary lung tumor is very rare in children and often remains undiagnosed until after distant metastasis has occurred. Few cases of early lung adenocarcinoma in children have been reported. However, this case concerns an 11-year-old child with primary bilateral minimally invasive adenocarcinoma. As far as we know, this is the youngest reported case of its type.
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http://dx.doi.org/10.3389/fsurg.2021.741744DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575692PMC
October 2021
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