Recent innovations in nanomaterials inspire abundant novel tumor-targeting CRISPR-based gene therapies. However, the therapeutic efficiency of traditional targeted nanotherapeutic strategies is limited by that the biomarkers vary in a spatiotemporal-dependent manner with tumor progression. Here, we propose a self-amplifying logic-gated gene editing strategy for gene/H₂O₂-mediated/starvation multimodal cancer therapy. In this approach, a hypoxia-degradable covalent-organic framework (COF) is synthesized to coat a-ZIF-8 in which glucose oxidase (GOx) and CRISPR system are packaged. To intensify intracellular redox dyshomeostasis, DNAzymes which can cleave catalase mRNA are loaded as well. When the nanosystem gets into the tumor, the weakly acidic and hypoxic microenvironment degrades the ZIF-8@COF to activate GOx, which amplifies intracellular H⁺ and hypoxia, accelerating the nanocarrier degradation to guarantee available CRISPR plasmid and GOx release in target cells. These tandem reactions deplete glucose and oxygen, leading to logic-gated-triggered gene editing as well as synergistic gene/H₂O₂-mediated/starvation therapy. Overall, this approach highlights the biocomputing-based CRISPR delivery and underscores the great potential of precise cancer therapy.

There is no unified international guidelines or consensus on seizures and epilepsy following acute stroke reperfusion therapy so far.In this review,we briefly summarize its definitions and mechanisms.Post stroke epilepsy after reperfusion treatment is defined as patients with ischemic stroke who have received intravenous thrombolysis and/or endovascular therapy,without other definitive causes or epilepsy history before stroke,have at least two epileptic seizures occurred within 7 days of stroke onset,or at least one epileptic seizures occurred within 30 days of stroke onset.The incidence rate of epilepsy after intravenous thrombolysis is about 6.4%-20.6%,and arterial thrombectomy is about 5%.The pathophysiological mechanism of post stroke epilepsy after reperfusion treatment may be related to local hyperfusion,epileptogenic properties of tPA and hemorrhagic transformation.Higher stroke severity,cortical involvement,middle cerebral artery infarction,and early post-stroke seizures may be predictive factors for post-stroke epilepsy after reperfusion therapy.Levetiracetam and lamotrigine may be effective drugs for post-stroke epilepsy after reperfusion therapy.Sustained seizures after thrombolysis may increase the risk of death.

Objective:To explore the effectiveness of deep learning image reconstruction (DLIR) algorithm compared to adaptive statistical iterative reconstruction (ASIR-V) algorithm in improving the quality of low-dose brain CT images.Methods:Retrospective inclusion of patients who underwent brain CT examination in the People's Liberation Army General Hospital from November 2021 to August 2022. Four different algorithms were used to reconstruct low-dose CT scans of all patients to obtain 30% intensity ASIR-V (ASIR-V-30%) images, low intensity DLIR (DLIR-L) images, medium intensity DLIR (DLIR-M) images, and high intensity DLIR (DLIR-H) images. The regions of interest were selected from four sets of images, including superficial white matter, superficial gray matter, deep white matter, and deep gray matter, and their CT values and standard deviations were measured for calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).Subjective evaluation of image quality was conducted by three neuroimaging physicians based on the Likert 5-component scale. The objective and subjective scores of the 4 groups of images were analyzed using ANOVA or Kruskal Wallis. If there are overall differences, pairwise comparisons were conducted within the group.Results:A total of 109 patients were enrolled, including 104 males and 5 females, aged 65-110 years (89.16 ± 9.53) years. The radiation exposure of brain CT low-dose scanning was (0.93 ± 0.01)mSv, significantly lower than that of conventional scanning (2.92 ± 0.01) mSv ( t = 56.15, P < 0.05). The differences in objective image quality analysis of ASIR-V-30%, DLIR-L, DLIR-M, and DLIR-H images of low-dose CT in SNR deep gray matter, SNR deep white matter, SNR superficial gray matter, SNR superficial white matter, CNR deep gray white matter, and CNR superficial gray white matter were statistically significant( F =98.23, 72.95, 68.43, 58.24, 241.13, 289.91, P < 0.05). Among them, DLIR-H images had the lowest noise in deep gray matter, deep white matter, superficial gray matter, and superficial white matter, and had statistically significant differences compared to other image groups ( t = 167.43, 275.46, 182.32, 361.54, P < 0.05). The subjective score of DLIR-H image quality was superior to ASIR-V-30%, DLIR-L, and DLIR-M, with the statistically significant difference ( t = 7.25, 8.32, 9.63, P < 0.05). Conclusions:Compared with ASIR-V, DLIR algorithm can effectively reduce image noise and artifacts in low-dose brain CT, and improve SNR and CNR. The subjective and objective image quality evaluation of DLIR-H is the best.

Objective:To investigate the effects of CT images reconstructed using different field of view (FOV) sizes on the automatic segmentation of organs at risk and dose calculation accuracy in radiotherapy after radical mastectomy.Methods:Under the same scanning conditions, CT values-electron density conversion curves were established by reconstructing the original CT images of a phantom placed at the isocenter and extended FOV (eFOV) positions using FOV sizes of 50, 60, 70 and 80 cm. Then, these curves were compared. A standard phantom with a known volume was scanned, and the automatic segmentation result of the phantom on CT images reconstructed using different FOV sizes was compared. A total of 30 patients in Guangdong Second Provincial General Hospital from January 2020 to June 2022 with breast cancer were randomly selected. Through simulated positioning, their CT images were reconstructed using different FOV sizes for the purpose of automatic segmentation of organs at risk, followed by comparison between the outcomes of automatic segmentation and physicians′segmentation. The treatment plan established based on CT images reconstructed using a FOV size of 50 cm (FOV 50 images for short) was applied to CT images reconstructed using FOV sizes of 60, 70 and 80 cm (FOV 60, FOV 70 and FOV 80 images for short) for dose calculation, and the dose calculation result were compared. Results:The CT values - electron density conversion curves derived from CT images reconstructed using different FOV sizes were roughly consistent. At the isocenter, the difference between the segmented volume and actual volume of the standard phantom increased up to a maximum of 6 cm 3 (4.8%) with an increase in the FOV size. As indicated by the automatic segmentation result, the segmentation accuracy of the spinal cord, trachea, esophagus, thyroid, healthy mammary gland, and skin decreased with an increase in the FOV size ( t = -28.43-8.23, P < 0.05). The comparison of dose calculated based on CT images reconstructed using different FOV sizes showed that there was no statistically significant differences( P>0.05) in the dose to target volume ( V95) and the maximum and average doses in the supraclavicular lymph node region, as well as the dose to organs at risk. The coverage for planned target volume decreased with an increase in the FOV size, with a maximum difference of 4.06%. Conclusions:It is recommended that, for radiotherapy after radical mastectomy, FOV 50 images should be selected for the automatic segmentation of organs at risk, CT-values-electron density conversion curves should be established based on the electron density phantom images of the eFOV region, and the eFOV 80 images should be preferred for dose calculation.

In 2020, two formulations of botulinum toxin type A (BoNT-A)named AbobotulinumtoxinA(Dysport ?) and LetibotulinumtoxinA(Letybo ?) have been officially approved by National Medical Products Administration to come on the market. To compare BoNT-As with different formulations, three BoNT-As[AbobotulinumtoxinA, OnabotulinumtoxinA(Botox ?), IncobotulinumtoxinA(Xeomin ?)] with relatively more clinical evidences internationally and two domestic BoNT-As[LanbotulinumtoxinA(Prosigne ?), LetibotulinumtoxinA] were included. Diffusion scale, conversion ratio, onset, duration and immunogenicity of different BoNT-As were reviewed in detail to provide reference for clinical practice.

Small renal cell carcinoma refers to a renal malignant tumor with a maximum diameter of 4 cm.Due to the small size, its diagnosis and differential diagnosis have been difficult points in clinical work. CT texture analysis is an emerging technique, it determines the tumor heterogeneity by analyzing the distribution and relationship of pixel or voxel gray-scale levels in the CT images, it acts to more accurately predict the benign and malignant tumors and the classification of tumors.This paper reviews CT texture analysis on the diagnosis and differential diagnosis of small renal cell carcinoma, in order to guide the correct diagnosis of doctors and effectively clinical treatment.

In 2020, two formulations of botulinum toxin type A (BoNT-A)named AbobotulinumtoxinA(Dysport ?) and LetibotulinumtoxinA(Letybo ?) have been officially approved by National Medical Products Administration to come on the market. To compare BoNT-As with different formulations, three BoNT-As[AbobotulinumtoxinA, OnabotulinumtoxinA(Botox ?), IncobotulinumtoxinA(Xeomin ?)] with relatively more clinical evidences internationally and two domestic BoNT-As[LanbotulinumtoxinA(Prosigne ?), LetibotulinumtoxinA] were included. Diffusion scale, conversion ratio, onset, duration and immunogenicity of different BoNT-As were reviewed in detail to provide reference for clinical practice.

Objective:To evaluate the feasibility of magnetic resonance (MR) perfusion imaging for sub-region segmentation of brain metastases (BMs), and to provide reference for individualized radiotherapy based on blood flow perfusion heterogeneity in BMs patients.Methods:96 BMs patients were selected, including 55 patients with necrosis and 41 without necrosis. Each patient was scanned with CT simulation and MR simulation before radiotherapy. MIM Maestro 6.8.8 software was used to delineate the gross tumor volume (GTV) and necrosis GTV (GTV N) from enhanced T 1W images and T 2 Propeller images, respectively, and the solid GTV (GTV S) was obtained by the subtraction of the two. Then, the cerebral blood flow map of three dimensional arterial spin labeling (3D-ASL) was employed to determine the high perfused GTV (GTV H) and low perfused GTV (GTV L). The volume and proportion of sub-regions were counted and compared between two groups and the correlation of each sub-region was analyzed. Results:The volume of GTV in the necrosis and non-necrosis groups was 19.56 and 7.34 cm 3, respectively. Besides, the AUC of the ROC between GTV volume and necrosis was 0.749. In the necrosis group, the ratio of GTV N, GTV S, GTV H and GTV L to GTV was 20.47%, 79.53%, 33.03% and 46.50%, respectively (all P<0.05). Among them, the r value between GTV S and GTV was 0.963, 0.849 for GTV L and GTV, and 0.840 for GTV L and GTV S, significantly higher than 0.683 for GTV H and GTV and 0.764 for GTV H and GTV S (all P<0.05). In the non-necrosis group, the ratio of GTV H to GTV was higher than that in the necrosis group (58.95% vs. 33.03%, P<0.05). In addition, the ratio of GTV L to GTV was slightly lower than that in the necrosis group (41.05% vs. 46.50%, P>0.05). The r value between GTV H and GTV was 0.776, significantly higher than 0.574 between GTV L and GTV ( P<0.05). Conclusion:MR-3D-ASL can quantitatively analyze the heterogeneous blood perfusion of BMs, which could guide the sub-region segmentation and local dose escalation of tumors.

Objective:To evaluate the feasibility of delineating subvolume target in radiotherapy for brain tumors using Gd-based contrast clearance difference.Methods:Twenty-six patients with malignant brain tumors were scanned with MRI. The first and second acquisitions of standard T 2-weighted images (T 2WI) and T 1-weighted images (T 1WI) were performed at 5 min and 60 min after injection of contrast agent. Delayed contrast extravasation (DCEM) MRI computed by Brainlab comprised regions of contrast agent clearance representing active tumors and regions of contrast accumulation representing non-tumor tissues. Based on T 2WI images, 14 patients with liquefaction necrosis were divided into group A, and 12 patients without liquefaction necrosis into group B, respectively. Then, gross target volume (GTV) was delineated on T 1WI images. Based on the GTV, active tumor (GTV tumor) and non-tumor regions (GTV non-tumor) were delineated on T 1WI-DCEM fusion images, while liquefaction necrosis (GTV liquefaction) and non-liquefaction (GTV non-liquefaction) were delineated on T 1-T 2WI fusion images. Finally, the differences between different subvolumes were compared by paired t-test. Results:In group A, the GTV non-liquefaction and GTV liquefaction were (13.65±18.15) cm 3 and (6.30±7.57) cm 3. The GTV tumor was (10.40±13.52) cm 3 and the GTV non-tumor was (9.55±14.57) cm 3. The GTV non-liquefaction was significantly increased by 16.3% on average compared with the GTV tumor ( P<0.05). The GTV non-tumor was significantly increased by 16.3% on average compared with the GTV liquefaction ( P<0.05). In group B, The GTV non-tumor was significantly reduced by 68.8% on average compared with the GTV tumor ( P<0.05). Conclusions:Compared with T 2WI, DCEM has advantages in identifying the liquefaction area and can clearly differentiate the subvolume of active tumors from non-liquefaction necrosis. DCEM provides evidence for guiding the delineation of subvolume in primary and metastatic brain tumors.

【Objective】 To estimate the application value of washed red blood cells (RBC) in perioperative patients with liver cancer. 【Methods】 86 perioperative patients with liver cancer who met the inclusion/exclusion criteria were divided into observation group (n=42) and control group (n=44). In the observation group, 22 patients were transfused with RBC and 20 with washed RBC. Patients without RBC transfusion worked as the controls. The name of disease, tumor stage, tumor size, Hb before and after blood transfusion, transfusion volume and blood components, adverse reaction to blood transfusion, operation time and blood loss during surgery, systemic infection, tumor recurrence and metastasis, and survival time were recorded. Blood transfusion efficacy, survival time, adverse reaction to blood transfusion, tumor recurrence and metastasis among these groups were compared. 【Results】 Among the non-transfusion group, washed RBC group and RBC group, the Hb(g/L)were 93.9±16.5 vs 80.4±24.5 vs 74.7±26.1, operative time (h) 2.8±0.7 vs 4.3±1.6 vs 3.9±2.0, operative blood loss(mL) 291.0±0.3 vs 388.0±165.8 vs 466.3±198.4 respectively before blood transfusion (all P<0.05). There were no significant differences in the efficacy of blood transfusion and survival time among the three groups (P>0.05). There were significant differences in tumor metastasis (50% vs 43%) and recurrence (50% vs 43.1%) between blood transfusion group and non-blood transfusion group (P<0.05). There was no difference in tumor metastasis (50% vs 48%) and recurrence (50% vs 49%) between the washed RBC group and RBC group (P>0.05). The nosocomial infection rate in washed RBC group (36%) was significantly lower that that in RBC group (88.6%) and non-transfusion group (50%) (P<0.05). 【Conclusion】 Blood transfusion caused by hypoxia may increase tumor metastasis and recurrence in perioperative patients with liver cancer. Transfusion of washed RBC can achieve the curative effect and reduce adverse reactions to blood transfusion, but has no significant impact on the survival time.