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Background: Controlling Nutritional Status (CONUT) score was used for screening the preoperative nutritional status. The correlation between the CONUT score and the prognosis of patients with prostate cancer (PCa) has yet to be elucidated. Herein, we analyzed the prognostic value of CONUT scores in patients with PCa who underwent laparoscopic radical prostatectomy. Materials and methods: Data of 244 patients were retrospectively evaluated. Perioperative variables and follow-up data were analyzed. The patients were categorized into 2 groups according to their preoperative CONUT scores. Postoperative complication and incontinence rates were also compared. The Kaplan-Meier method was used to estimate the median biochemical recurrence-free survival (BCRFS) between the 2 groups. Univariate and multivariate Cox regression analyses were performed to identify the potential prognostic factors for BCRFS. Results: Patients were categorized into the low-CONUT group (CONUT score <3, n = 207) and high-CONUT group (CONUT score ≥3, n = 37). The high-CONUT group had a higher overall complication rate (40.5% vs.19.3%, p = 0.004), a higher major complication rate (10.8% vs. 3.9%, p = 0.013), and longer postoperative length of stay (8 days vs. 7 days, p = 0.017). More fever, urinary infection, abdominal infection, scrotal edema, rash, and hemorrhagic events (all p values < 0.05) were observed in the high-CONUT group. A higher rate of urinary incontinence was observed in the high-CONUT group at 1 (34.4% vs. 13.2%, p = 0.030) and 3 months (24.1% vs. 8.2%, p = 0.023) postoperatively. The high-CONUT group had shorter medium BCRFS (23.8 months vs. 54.6 months, p = 0.029), and a CONUT score ≥3 was an independent risk factor for a shorter BCRFS (hazards ratio, 1.842; p = 0.026). Conclusions: The CONUT score is a useful predictive tool for higher postoperative complication rates and shorter BCRFS in patients with PCa who undergo laparoscopic radical prostatectomy.
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PURPOSE: To develop a deep learning framework based on a hybrid dataset to enhance the quality of CBCT images and obtain accurate HU values. MATERIALS AND METHODS: A total of 228 cervical cancer patients treated in different LINACs were enrolled. We developed an encoder-decoder architecture with residual learning and skip connections. The model was hierarchically trained and validated on 5279 paired CBCT/planning CT images and tested on 1302 paired images. The mean absolute error (MAE), peak signal to noise ratio (PSNR), and structural similarity index (SSIM) were utilized to access the quality of the synthetic CT images generated by our model. RESULTS: The MAE between synthetic CT images generated by our model and planning CT was 10.93 HU, compared to 50.02 HU for the CBCT images. The PSNR increased from 27.79 dB to 33.91 dB, and the SSIM increased from 0.76 to 0.90. Compared with synthetic CT images generated by the convolution neural networks with residual blocks, our model had superior performance both in qualitative and quantitative aspects. CONCLUSIONS: Our model could synthesize CT images with enhanced image quality and accurate HU values. The synthetic CT images preserved the edges of tissues well, which is important for downstream tasks in adaptive radiotherapy.
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Gene delivery is the process by which foreign DNA is transferred to host cells, released from intracellular vesicles, and transported to the nuclei for transcription. This process is frequently inefficient and difficult to control spatiotemporally. We developed a gene delivery strategy that uses ultrasound to directly deliver plasmid DNA into nuclei via gas vesicles (GVs)-based intracellular cavitation. pDNA-binding GVs can be taken up by cells and cause intracellular cavitation when exposed to acoustic irradiation and delivering their pDNA payloads into nuclei. Importantly, GVs can remain stable in the cytoplasm in the absence of acoustic irradiation, allowing for temporally controlled nuclear gene delivery. We were able to achieve spatiotemporal control of E-cadherin nuclear gene delivery in this manner, demonstrating its efficacy in tumor invasion and metastasis inhibition. Interestingly, we discovered that nuclear gene delivery of E-cadherin during the G2/M phase of the cell cycle in C6 tumor cells inhibited tumor invasion and metastasis more effectively than during the G1 and S phases. The gene delivery of E-cadherin at the G2/M phase resulted in significantly lower expression of Fam50a, which reduced Fam50a/Runx2 interaction and led to reduced transactivation of MMP13, an important factor for epithelial-mesenchymal transition, as observed in a molecular mechanism assay. Thus, using remote acoustic control of intracellular cavitation of pDNA-GVs, we developed a high spatiotemporally controllable gene delivery strategy and achieved stronger tumor invasion and metastasis inhibition effects by delivering the E-cadherin gene at the G2/M phase.
Subject(s)
Cell Nucleus , Gene Transfer Techniques , Cell Line, Tumor , Cell Nucleus/genetics , Cell Nucleus/metabolism , Cadherins/genetics , Cadherins/metabolismABSTRACT
Cinobufacini injection (CI), an aqueous extract of Cutis Bufonis, is clinically used for cancer therapy in China, but its molecular mechanism for the treatment of osteosarcoma (OS) remains unclear. We constructed U2OS ectopic subcutaneous tumor model to verify the anti-OS effect of CI in vivo. Meanwhile, cell proliferation of U2OS and MG63 cells was monitored in vitro using the CCK-8 assay, colony formation and morphological changes. Cell cycle arrest and apoptosis were detected by flow cytometry and western blot, which showed that CI significantly inhibited proliferation, induced cell cycle arrest and apoptosis in human OS cells. The further RNA-seq results identified that the Hippo signaling pathway was involved in the anti-OS effect of CI. YAP/TAZ are two major components of the Hippo pathway in breast cancer and are positively regulated by prolyl isomerase PIN1, we assessed their role in OS using both clinicopathological sections and western blots. CI also inhibited PIN1 enzyme activity in a dose-dependent manner, which resulted in impaired PIN1, YAP, and TAZ expression in vitro and in vivo. Additionally, 15 potential compounds of CI were found to occupy the PIN1 kinase domain and inhibit its activity. In summary, CI plays an anti-OS role by down-regulating the PIN1-YAP/TAZ pathway.
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Background: The coronavirus disease 2019 (COVID-19) led to a dramatic increase in the number of cases of patients with pneumonia worldwide. In this study, we aimed to develop an AI-assisted multistrategy image enhancement technique for chest X-ray (CXR) images to improve the accuracy of COVID-19 classification. Methods: Our new classification strategy consisted of 3 parts. First, the improved U-Net model with a variational encoder segmented the lung region in the CXR images processed by histogram equalization. Second, the residual net (ResNet) model with multidilated-rate convolution layers was used to suppress the bone signals in the 217 lung-only CXR images. A total of 80% of the available data were allocated for training and validation. The other 20% of the remaining data were used for testing. The enhanced CXR images containing only soft tissue information were obtained. Third, the neural network model with a residual cascade was used for the super-resolution reconstruction of low-resolution bone-suppressed CXR images. The training and testing data consisted of 1,200 and 100 CXR images, respectively. To evaluate the new strategy, improved visual geometry group (VGG)-16 and ResNet-18 models were used for the COVID-19 classification task of 2,767 CXR images. The accuracy of the multistrategy enhanced CXR images was verified through comparative experiments with various enhancement images. In terms of quantitative verification, 8-fold cross-validation was performed on the bone suppression model. In terms of evaluating the COVID-19 classification, the CXR images obtained by the improved method were used to train 2 classification models. Results: Compared with other methods, the CXR images obtained based on the proposed model had better performance in the metrics of peak signal-to-noise ratio and root mean square error. The super-resolution CXR images of bone suppression obtained based on the neural network model were also anatomically close to the real CXR images. Compared with the initial CXR images, the classification accuracy rates of the internal and external testing data on the VGG-16 model increased by 5.09% and 12.81%, respectively, while the values increased by 3.51% and 18.20%, respectively, for the ResNet-18 model. The numerical results were better than those of the single-enhancement, double-enhancement, and no-enhancement CXR images. Conclusions: The multistrategy enhanced CXR images can help to classify COVID-19 more accurately than the other existing methods.
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The purpose was to assess the profile of subconjunctival oblique limbus incision (SCOLI) design by using anterior-segment optical coherence tomography (AS-OCT) and try to emphasize the proper technique of wound construction. The structural dimensions and integrity of the wound were acquired from the patients, who had undergone manual small-incision cataract surgery with SCOLI techniques, using a Canon OCT anterior-segment imaging system on the first postoperative day. The use of AS-OCT allowed for an in vivo evaluation of SCOLI in high definition. The radial OCT scan image showed three staggered incisions, including conjunctiva incision, scleral entrance, and inner corneal lip. A tangential scan demonstrated that the internal lip is parallel to the curvature of the peripheral cornea. The en face image showed an asymmetric 4 arc-shaped configuration rather than a symmetrical one. In conclusion, AS-OCT could be used to analyze SCOLI to determine optimal wound construction and geometry. The results of this study indicated that an asymmetric 4 arc-shaped limbus tunnel incision was superior to the conventional linear equivalent in stability and nucleus delivery.
Subject(s)
Cataract Extraction , Surgical Wound , Humans , Tomography, Optical Coherence/methods , Cataract Extraction/methods , Cornea/surgery , Sclera/surgery , Surgical Wound/surgeryABSTRACT
Clear cell renal cell carcinoma (ccRCC) is the most common histological subtype of renal cancer. Cuproptosis is suggested to be a novel therapy target for cancer treatment. However, the function of cuproptosis and its key regulator FDX1 in ccRCC remains unclear. In this study, we adequately explored the prognostic factors, clinicopathological characteristics, and function of FDX1 in ccRCC. We found that the expression of FDX1 was significantly downregulated in ccRCC samples. Patients with a higher FDX1 expression had a significantly better prognosis, including overall survival (OS) (Hazard ratio (HR): 2.54, 95% confidence interval (CI): 1.82−3.53, p < 0.001), disease-specific survival (DSS) (HR: 3.04, 95% CI: 2.04−4.54, p < 0.001), and progression-free survival (PFS) (HR: 2.54, 95% CI: 1.82−3.53, p < 0.001). FDX1 was a clinical predictor to stratify patients into the high or low risk of poor survival, independent of conventional clinical features, with the area under the ROC curve (AUC) of 0.658, 0.677, and 0.656 for predicting the 5-year OS, DSS, and PFS. The nomogram model based on FDX1 had greater predictive power than other individual prognostic parameters. FDX1 mainly participated in the oxidative-related process and mitochondrial respiration-related processes but was not associated with immune infiltration levels. In conclusion, the cuproptosis key regulator FDX1 could serve as a potential novel prognostic biomarker for ccRCC patients.
Subject(s)
Apoptosis , Carcinoma, Renal Cell , Kidney Neoplasms , Humans , Biomarkers , Carcinoma, Renal Cell/metabolism , Kidney Neoplasms/metabolism , Nomograms , Prognosis , CopperABSTRACT
The epithelial-mesenchymal transition (EMT), a process in which epithelial cells undergo a series of biochemical changes to acquire a mesenchymal phenotype, has been linked to tumor metastasis. Here, we present a novel strategy for knocking out the EMT-related Cdh2 gene, which encodes N-cadherin through CRISPR/Cas9-mediated gene editing by an ultrasound combined with biosynthetic nanobubbles (Gas Vesicles, GVs). Polyethyleneimine were employed as a gene delivery vector to deliver sgRNA into 4T1 cells that stably express the Cas9 protein, resulting in the stable Cdh2 gene- knockout cell lines. The Western blotting assay confirmed the absence of an N-cadherin protein in these Cdh2 gene-knockout 4T1 cell lines. Significantly reduced tumor cell migration was observed in the Cdh2 gene-knockout 4T1 cells in comparison with the wild-type cells. Our study demonstrated that an ultrasound combined with GVs could effectively mediate CRISPR/Cas9 gene editing of a Cdh2 gene to inhibit tumor invasion and metastasis.
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Background: Coronavirus disease 2019 (COVID-19) is a pandemic disease. Fast and accurate diagnosis of COVID-19 from chest radiography may enable more efficient allocation of scarce medical resources and hence improved patient outcomes. Deep learning classification of chest radiographs may be a plausible step towards this. We hypothesize that bone suppression of chest radiographs may improve the performance of deep learning classification of COVID-19 phenomena in chest radiographs. Methods: Two bone suppression methods (Gusarev et al. and Rajaraman et al.) were implemented. The Gusarev and Rajaraman methods were trained on 217 pairs of normal and bone-suppressed chest radiographs from the X-ray Bone Shadow Suppression dataset (https://www.kaggle.com/hmchuong/xray-bone-shadow-supression). Two classifier methods with different network architectures were implemented. Binary classifier models were trained on the public RICORD-1c and RSNA Pneumonia Challenge datasets. An external test dataset was created retrospectively from a set of 320 COVID-19 positive patients from Queen Elizabeth Hospital (Hong Kong, China) and a set of 518 non-COVID-19 patients from Pamela Youde Nethersole Eastern Hospital (Hong Kong, China), and used to evaluate the effect of bone suppression on classifier performance. Classification performance, quantified by sensitivity, specificity, negative predictive value (NPV), accuracy and area under the receiver operating curve (AUC), for non-suppressed radiographs was compared to that for bone suppressed radiographs. Some of the pre-trained models used in this study are published at (https://github.com/danielnflam). Results: Bone suppression of external test data was found to significantly (P<0.05) improve AUC for one classifier architecture [from 0.698 (non-suppressed) to 0.732 (Rajaraman-suppressed)]. For the other classifier architecture, suppression did not significantly (P>0.05) improve or worsen classifier performance. Conclusions: Rajaraman suppression significantly improved classification performance in one classification architecture, and did not significantly worsen classifier performance in the other classifier architecture. This research could be extended to explore the impact of bone suppression on classification of different lung pathologies, and the effect of other image enhancement techniques on classifier performance.
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Objective.Four-dimensional cone-beam computed tomography (4D CBCT) has unique advantages in moving target localization, tracking and therapeutic dose accumulation in adaptive radiotherapy. However, the severe fringe artifacts and noise degradation caused by 4D CBCT reconstruction restrict its clinical application. We propose a novel deep unsupervised learning model to generate the high-quality 4D CBCT from the poor-quality 4D CBCT.Approach.The proposed model uses a contrastive loss function to preserve the anatomical structure in the corrected image. To preserve the relationship between the input and output image, we use a multilayer, patch-based method rather than operate on entire images. Furthermore, we draw negatives from within the input 4D CBCT rather than from the rest of the dataset.Main results.The results showed that the streak and motion artifacts were significantly suppressed. The spatial resolution of the pulmonary vessels and microstructure were also improved. To demonstrate the results in the different directions, we make the animation to show the different views of the predicted correction image in the supplementary animation.Significance.The proposed method can be integrated into any 4D CBCT reconstruction method and maybe a practical way to enhance the image quality of the 4D CBCT.
Subject(s)
Artifacts , Spiral Cone-Beam Computed Tomography , Four-Dimensional Computed Tomography , Motion , Unsupervised Machine LearningABSTRACT
Protein tyrosine phosphatase non-receptor type 12 (PTPN12) is abnormally expressed in many human cancers. However, its role in hepatocellular carcinoma (HCC) is indeterminate. In this study, immunohistochemistry and Western blot were adopted to detect PTPN12 protein expression in HCC tissues and cell lines. MiR-106a-5p and PTPN12 mRNA expressions were determined by quantitative real-time polymerase chain reaction (qRT-PCR). siRNA was used to knockdown PTPN12 expression in HCC cells, and the multiplication, migration, and invasion of HCC cells were determined by cell counting kit 8 (CCK-8) and Transwell assays. The interaction between PTPN12 and miR-106a-5p was verified by dual-luciferase reporter gene assay and RNA immunoprecipitation (RIP) assay. In the present study, we demonstrated that PTPN12 expression in HCC tissues and cells was significantly decreased, which was associated with the tumor size, TNM stage, and lymph node metastasis of HCC patients. Functionally, knocking down PTPN12 significantly promoted the multiplication, migration, invasion, and epithelial-mesenchymal transition (EMT) of HCC cells. PTPN12 was identified as the direct target of miR-106a-5p, and its expression was negatively modulated by miR-106a-5p. Besides, PTPN12 counteracted the promoting effects of miR-106a-5p on the viability, migration, invasion, and EMT of HCC cells. In conclusion, this study substantiates that PTPN12 inhibits the growth, migration, invasion, and EMT of HCC cells, and miR-106a-5p contributes to its dysregulation in HCC.
Subject(s)
Carcinoma, Hepatocellular/genetics , Carcinoma, Hepatocellular/pathology , Gene Expression Regulation, Neoplastic/genetics , Liver Neoplasms/genetics , Liver Neoplasms/pathology , MicroRNAs/physiology , Protein Tyrosine Phosphatase, Non-Receptor Type 12/genetics , Protein Tyrosine Phosphatase, Non-Receptor Type 12/metabolism , Cell Line, Tumor , Cell Movement/genetics , Cell Survival/genetics , Disease Progression , Epithelial-Mesenchymal Transition/genetics , Gene Expression , Humans , Neoplasm Invasiveness/geneticsABSTRACT
PURPOSE: To compare perioperative results of intracorporeal ileal conduit (ICIC) and intracorporeal orthotopic neobladder (ICONB) following laparoscopic radical cystectomy. MATERIALS AND METHODS: A total of 51 ICIC patients and 32 ICONB patients were included. Propensity score matching was performed based on: age, body mass index, gender, age-adjusted Charlson comorbidity index, history of neoadjuvant chemotherapy, history of abdominal surgery, history of smoking and enhanced recovery protocols. Primary outcomes were length of stay and 30-day complications. Secondary outcomes were operative time and estimated blood loss. RESULTS: ICONB was more likely to be performed in younger patients (P < 0.001). Other baseline characteristics in the 2 groups were similar (P > 0.05). ICIC showed shorter length of stay (11 days vs. 14 days, P = 0.031) and faster pelvic drainage tube removal (6 days vs. 9 days, P = 0.014). Operative time, estimated blood loss, 30-day complications were similar in the 2 groups (P > 0.05). However, postoperative fever was significantly lower in ICIC group (19.6% vs. 62.5%, P < 0.001). After propensity score matching, ICIC still showed shorter length of stay (10 days vs. 15 days, P = 0.002) and less postoperative fever (15% vs. 65%, P = 0.003). In multivariable analysis, ICONB was independently associated with length of stay≥14 days and postoperative fever both before and after propensity score matching (P < 0.05). CONCLUSIONS: In our research, ICONB was more likely to be performed in younger patients. ICIC and ICONB showed no difference on 30-day complications, operative time and estimated blood loss. ICIC group showed shorter length of stay, faster pelvic drainage tube removal and less postoperative fever.
Subject(s)
Laparoscopy , Urinary Bladder Neoplasms , Urinary Diversion , Cystectomy/methods , Humans , Propensity Score , Treatment Outcome , Urinary Bladder Neoplasms/surgeryABSTRACT
BACKGROUND: In the radiotherapy of nasopharyngeal carcinoma (NPC), magnetic resonance imaging (MRI) is widely used to delineate tumor area more accurately. While MRI offers the higher soft tissue contrast, patient positioning and couch correction based on bony image fusion of computed tomography (CT) is also necessary. There is thus an urgent need to obtain a high image contrast between bone and soft tissue to facilitate target delineation and patient positioning for NPC radiotherapy. In this paper, our aim is to develop a novel image conversion between the CT and MRI modalities to obtain clear bone and soft tissue images simultaneously, here called bone-enhanced MRI (BeMRI). METHODS: Thirty-five patients were retrospectively selected for this study. All patients underwent clinical CT simulation and 1.5T MRI within the same week in Shenzhen Second People's Hospital. To synthesize BeMRI, two deep learning networks, U-Net and CycleGAN, were constructed to transform MRI to synthetic CT (sCT) images. Each network used 28 patients' images as the training set, while the remaining 7 patients were used as the test set (~1/5 of all datasets). The bone structure from the sCT was then extracted by the threshold-based method and embedded in the corresponding part of the MRI image to generate the BeMRI image. To evaluate the performance of these networks, the following metrics were applied: mean absolute error (MAE), structural similarity index (SSIM), and peak signal-to-noise ratio (PSNR). RESULTS: In our experiments, both deep learning models achieved good performance and were able to effectively extract bone structure from MRI. Specifically, the supervised U-Net model achieved the best results with the lowest overall average MAE of 125.55 (P<0.05) and produced the highest SSIM of 0.89 and PSNR of 23.84. These results indicate that BeMRI can display bone structure in higher contrast than conventional MRI. CONCLUSIONS: A new image modality BeMRI, which is a composite image of CT and MRI, was proposed. With high image contrast of both bone structure and soft tissues, BeMRI will facilitate tumor localization and patient positioning and eliminate the need to frequently check between separate MRI and CT images during NPC radiotherapy.
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BACKGROUND: Parkinson's disease (PD) is a progressive neurodegenerative disorder. Owing to the presence of blood-brain barrier (BBB), conventional pharmaceutical agents are difficult to the diseased nuclei and exert their action to inhibit or delay the progress of PD. Recent literatures have demonstrated that curcumin shows the great potential to treat PD. However, its applications are still difficult in vivo due to its poor druggability and low bioavailability through the BBB. METHODS: Melt-crystallization methods were used to improve the solubility of curcumin, and curcumin-loaded lipid-PLGA nanobubbles (Cur-NBs) were fabricated through encapsulating the curcumin into the cavity of lipid-PLGA nanobubbles. The bubble size, zeta potentials, ultrasound imaging capability and drug encapsulation efficiency of the Cur-NBs were characterized by a series of analytical methods. Low-intensity focused ultrasound (LIFU) combined with Cur-NB was used to open the BBB to facilitate curcumin delivery into the deep brain of PD mice, followed by behavioral evaluation for the treatment efficacy. RESULTS: The solubility of curcumin was improved by melt-crystallization methods, with 2627-fold higher than pure curcumin. The resulting Cur-NBs have a nanoscale size about 400 nm and show excellent contrast imaging performance. Curcumin drugs encapsulated into Cur-NBs could be effectively released when Cur-NBs were irradiated by LIFU at the optimized acoustic pressure, achieving 30% cumulative release rate within 6 h. Importantly, Cur-NBs combined with LIFU can open the BBB and locally deliver the curcumin into the deep-seated brain nuclei, significantly enhancing efficacy of curcumin in the Parkinson C57BL/6J mice model in comparison with only Cur-NBs and LIFU groups. CONCLUSION: In this work, we greatly improved the solubility of curcumin and developed Cur-NBs for brain delivery of curcumin against PD through combining with LIFU-mediating BBB. Cur-NBs provide a platform for these potential drugs which are difficult to cross the BBB to treat PD disease or other central nervous system (CNS) diseases.
Subject(s)
Curcumin , Nanoparticles , Animals , Blood-Brain Barrier , Brain/diagnostic imaging , Lipids , Mice , Mice, Inbred C57BL , Particle Size , UltrasonographyABSTRACT
PURPOSE: In recent years, cone-beam computed tomography (CBCT) is increasingly used in adaptive radiation therapy (ART). However, compared with planning computed tomography (PCT), CBCT image has much more noise and imaging artifacts. Therefore, it is necessary to improve the image quality and HU accuracy of CBCT. In this study, we developed an unsupervised deep learning network (CycleGAN) model to calibrate CBCT images for the pelvis to extend potential clinical applications in CBCT-guided ART. METHODS: To train CycleGAN to generate synthetic PCT (sPCT), we used CBCT and PCT images as inputs from 49 patients with unpaired data. Additional deformed PCT (dPCT) images attained as CBCT after deformable registration are utilized as the ground truth before evaluation. The trained uncorrected CBCT images are converted into sPCT images, and the obtained sPCT images have the characteristics of PCT images while keeping the anatomical structure of CBCT images unchanged. To demonstrate the effectiveness of the proposed CycleGAN, we use additional nine independent patients for testing. RESULTS: We compared the sPCT with dPCT images as the ground truth. The average mean absolute error (MAE) of the whole image on testing data decreased from 49.96 ± 7.21HU to 14.6 ± 2.39HU, the average MAE of fat and muscle ROIs decreased from 60.23 ± 7.3HU to 16.94 ± 7.5HU, and from 53.16 ± 9.1HU to 13.03 ± 2.63HU respectively. CONCLUSION: We developed an unsupervised learning method to generate high-quality corrected CBCT images (sPCT). Through further evaluation and clinical implementation, it can replace CBCT in ART.
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BACKGROUND: We aimed to examine whether body mass index (BMI) had an impact on clinical outcomes of laparoscopic radical cystectomy with intracorporeal urinary diversion. Furthermore, we analyzed the optimization of enhanced recovery protocols (ERPs) on the impact of BMI on clinical outcomes. METHODS: By searching our database, data of 83 consecutive patients were retrospectively collected, including 37 patients with a BMI <24 kg/m2 (group A) and 46 patients with a BMI ≥24 kg/m2 (group B). The baseline and peri-operative variables of the two groups were compared. Subgroup analysis was conducted for ERPs (11 patients in group A1, 18 patients in group B1) and conventional recovery protocols (CRPs; 26 patients in group A2, 28 patients in group B2). The primary outcomes were 30-day overall complication rate and ΔALBmin (reduction proportion of minimum albumin). The secondary outcomes were operative time and length of stay. RESULTS: The baseline variables were similar between the two groups (P>0.05). The 30-day overall complication rate, operative time, and length of stay were similar between the two groups (P>0.05). But post-operative nausea and vomiting (PONV) was higher in group A than in group B (32.4% vs. 8.7%, P=0.014). Group A was associated with lower serum albumin level pre-operatively and on post-operative days 1-3. ΔALBmin was higher in group A than in group B (33.08%±9.88% vs. 27.92%±8.52%, P<0.05). In the subgroup analysis, the CRPs group presented similar results, with group A2 showing higher PONV rate, lower albumin level pre- and post-operatively, and higher level of reduction proportion (P<0.05). For the ERPs group, the PONV rate, pre-operative albumin level, and reduction proportion were similar between group A1 and B1 (P>0.05). Multivariable analysis showed that PONV and CRPs were independently associated with ΔALBmin ≥34% (P<0.05). CONCLUSIONS: BMI had no impact on the 30-day overall complication rate, operative time, and length of stay of patients who underwent laparoscopic radical cystectomy with intracorporeal urinary diversion. BMI <24 kg/m2 was associated with higher PONV rate and more albumin loss, both of which could be optimized by ERPs.
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BACKGROUND: This study introduces the results of laparoscopic radical cystectomy with modified intracorporeal ileal conduit (mICIC), which was accompanied by enhanced recovery after surgery (ERAS) protocols. METHODS: From March 2014 to June 2020, 48 patients underwent mICIC. Patients were divided into ERAS (n=17) and non-ERAS groups (n=31). Baseline and perioperative variables were analyzed. The primary outcome was 90-day complications. Secondary outcomes were operative time, length of stay, two-year overall survival, cancer-specific survival, and disease-free survival. RESULTS: Forty-eight patients underwent intracorporeal ileal conduit with no transition to open surgery. Twenty-five patients (52.1%) experienced at least one complication, including 22 minor cases (45.8%) and three major cases (6.2%). The median operative time, urinary diversion time, estimated blood loss, and length of stay were 320 min, 135 min, 200 mL, and 10.5 days, respectively. The median time to flatus and normal diet were two days and three days, respectively. A comparison between ERAS and non-ERAS groups indicated that ERAS implementation was associated with less complications (29.4% vs. 64.5%, P=0.018), faster time to flatus (2 vs. 3 days, P=0.016) and liquid diet (2 vs. 4 days, P<0.001). The results of hydronephrosis and compromised renal function showed no difference between the preoperative period and six months after surgery. The mean follow-up time was 25.4 months, and the two-year overall survival, cancer-specific survival, and disease-free survival rates were 61.3%, 73.2%, and 58.4%, respectively. CONCLUSIONS: The complication rate and operative time of the mICIC were acceptable. Clinical outcomes can be optimized with ERAS pathway.
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BACKGROUND The bluetongue virus (BTV) is the prototype virus in the genus Orbivirus within the family Reoviridae. Recent studies indicate that BTVs are capable of infecting and selectively lysing human hepatic carcinoma cells (Hep-3B) and prostate carcinoma cells (pc-3). This study was designed to evaluate the oncolytic potential of BTV in experimental models of human renal cancer in vitro and in vivo. MATERIAL AND METHODS Five human renal cancer cell lines, ACHN, CAKI-1, OS-RC-2, 786-O, and A498, were used in this study to analyze BTV replication. These cells were lysed by oncolysis compared to normal control. Xenograft models were used to assess the efficacy and toxicity of BTVs in vivo. Data were analyzed by one-way ANOVA or two-sided unpaired t tests. RESULTS The results showed HPTEC cells to be relatively resistant to cytotoxic effects of BTVs and exhibited normal growth rate even at high dose of BTVs. Nonetheless, the renal cancer cells showed a remarkably higher sensitivity to BTVs. Moreover, the ultramicroscopic subcellular changes were also detected in the renal cells. The viral particles were observed in all the RCC cell lines, but not in HPTEC cells. Intratumoral injections of BTVs significantly decreased the tumor volume as compared to animals that received no virus treatment. Infection with BTVs significantly increased the percentage of apoptotic renal cancer cells but not the HPTEC cells. Moreover, BTV triggered apoptosis in renal cancer cells via a mitochondria-mediated pathway. CONCLUSIONS This study for the first time demonstrated the oncolytic potential of BTV in experimental models of human renal cancer. BTV exhibits the potential to inhibit human renal cancer cell growth in vitro and in vivo.
Subject(s)
Bluetongue virus/metabolism , Kidney Neoplasms/therapy , Kidney Neoplasms/virology , Animals , Apoptosis/physiology , Carcinoma, Renal Cell/metabolism , Carcinoma, Renal Cell/therapy , Carcinoma, Renal Cell/virology , Cell Line, Tumor , Cell Survival/physiology , Humans , Kidney Neoplasms/metabolism , Male , Mice , Mice, Inbred BALB C , Mice, Nude , Oncolytic Viruses/metabolism , Xenograft Model Antitumor Assays/methodsABSTRACT
To investigate the outcomes of transurethral seminal vesiculoscopy (TSV) for the treatment of seminal vesicle calculi (SVC), prostatic utricle calculi (PUC) and combination of them, a retrospective review on 27 patients with SVC and/or PUC who complained of intractable haematospermia was conducted. Patient demographics, disease duration, operation time, stone location and complications were recorded. The calculi in the seminal vesicle and/or prostatic utricle were removed by holmium laser lithotripsy and/or basket extraction. The stone composition was determined in 19 of 27 patients using Infrared spectroscopy. The average age and disease duration of patients were 39.4 years and 23.1 months respectively. The mean operative time was 78.5 min. We detected SVC, SVC and PUC, and PUC in 59.3% (16/27), 33.3% (9/27) and 7.4% (2/27) patients respectively. The stones were mainly composed of calcium oxalate dehydrate (COD), carbonate apatite (CA), COD and calcium oxalate monohydrate (COM), CA and magnesium ammonium phosphate, CA and COM, and COD and uric acid in 42.1% (8/19), 21.1% (4/19), 15.8% (3/19), 15.8% (3/19), 5.3% (1/19) and 5.3% (1/19) cases respectively. No intraoperative and post-operative complications were noted. These results suggested that SVC and PUC can be diagnosed and treated using TSVs.