Single- versus triple-agent intra-arterial chemotherapy for retinoblastoma.

PURPOSE: To compare the ocular and systemic outcomes of single- (melphalan) versus triple-agent (melphalan, topotecan, carboplatin) intra-arterial chemotherapy (IAC) for retinoblastoma (RB) eye salvage. DESIGN: Retrospective single-institutional clinical cohort study. METHODS: Children <18 years with RB who underwent one or more IAC procedures between 2016 and 2024 with minimum 6-month follow-up were reviewed. Data included clinical features, IAC procedural details, additional eye-saving treatments, complications, and follow-up. Primary outcomes included ocular and systemic complications of IAC, intraocular recurrence, extraocular extension, metastasis, and death. Secondary outcomes were tumor response, ocular survival, and recurrence-free ocular survival. Comparative analysis was performed for single- versus triple-agent groups. A SWIMMERrb plot graphically illustrated additional treatments following IAC. RESULTS: Thirty-eight eyes of 37 children (24 unilateral RB) were reviewed. Two eyes (2 children) had single- followed by multi-agent IAC and were excluded. Of 35 included children, one had bilateral triple-agent IAC. IAC (median, 3 doses; range, 1-4) was employed as primary (n=21 eyes) or secondary (n=15 eyes) treatment. Chemotherapy was single-agent in 13 eyes and triple-agent in 23 eyes. Following IAC, 25 eyes required additional eye-saving treatments (69% single- v 70% triple-agent, p=0.983). At final follow-up, the triple-agent group was more likely to achieve very good partial or complete tumor response (91% v 62%, p=0.030). Two-year recurrence-free ocular survival was 63.3% (95% CI 45.7-80.9), similar for both groups (p=0.700). Globe salvage was 72%. Two-year ocular survival was 72.2% (95% CI 57.2-87.2), higher for the triple-agent group (82.6% v 53.8%; p=0.059). Ocular complications occurred in 31% of eyes in the single- and 52% of eyes in the triple-agent group (p=0.215). The rate of systemic complications was 38% v 74% in the single- versus triple-agent groups, respectively (p=0.036). No extraocular extension, metastasis, or death were observed at median 34.2 months (range, 14.5-87.0) follow-up. CONCLUSIONS: Triple-agent IAC was associated with improved RB tumor response and ocular survival, though similar recurrence-free ocular survival compared to single-agent. While there were more complications with triple-agent IAC, most were mild or transient.

An Enzymatic Oxidation Cascade Converts δ-Thiolactone Anthracene to Anthraquinone in the Biosynthesis of Anthraquinone-Fused Enediynes.

Anthraquinone-fused enediynes are anticancer natural products featuring a DNA-intercalating anthraquinone moiety. Despite recent insights into anthraquinone-fused enediyne (AQE) biosynthesis, the enzymatic steps involved in anthraquinone biogenesis remain to be elucidated. Through a combination of in vitro and in vivo studies, we demonstrated that a two-enzyme system, composed of a flavin adenine dinucleotide (FAD)-dependent monooxygenase (DynE13) and a cofactor-free enzyme (DynA1), catalyzes the final steps of anthraquinone formation by converting δ-thiolactone anthracene to hydroxyanthraquinone. We showed that the three oxygen atoms in the hydroxyanthraquinone originate from molecular oxygen (O2), with the sulfur atom eliminated as H2S. We further identified the key catalytic residues of DynE13 and A1 by structural and site-directed mutagenesis studies. Our data support a catalytic mechanism wherein DynE13 installs two oxygen atoms with concurrent desulfurization and decarboxylation, whereas DynA1 acts as a cofactor-free monooxygenase, installing the final oxygen atom in the hydroxyanthraquinone. These findings establish the indispensable roles of DynE13 and DynA1 in AQE biosynthesis and unveil novel enzymatic strategies for anthraquinone formation.

Artificial intelligence applied to 'omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment.

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.

Influence of tumor thrombus morphology on the surgical complexity in renal cell carcinoma with inferior vena cava tumor thrombus: a single-center, large-sample study from China.

BACKGROUND: The morphology of tumor thrombus varies from person to person and it may affect surgical methods and tumor prognosis. However, studies on the morphology of tumor thrombus are limited. The purpose of our study was to evaluate the impact of tumor thrombus morphology on surgical complexity. METHODS: We retrospectively reviewed the clinical data of 229 patients with renal cell carcinoma combined with inferior vena cava (IVC) tumor thrombus who underwent surgical treatment at Peking University Third Hospital between January 2014 and December 2021. The patients were divided into floating morphology (107 patients) and filled morphology (122 patients) tumor thrombi groups. Chi-square and Mann-Whitney U tests were used for categorical and continuous variables, respectively. Postoperative complications were evaluated using the Clavien-Dindo surgical complication classification method. RESULTS: Patients with filled morphology tumor thrombus required more surgical techniques than those with floating morphology tumor thrombus, which was reflected in more open surgeries (P < 0.001), more IVC interruptions (P <0.001), lesser use of the delayed occlusion of the proximal inferior vena cava (DOPI) technique (P < 0.001), and a greater need for cut-off of the short hepatic vein (P < 0.001) and liver dissociation (P = 0.001). Filled morphology significantly increased the difficulty of surgery in patients with renal cell carcinoma with tumor thrombus, reflected in longer operation time (P < 0.001), more surgical blood loss (P <0.001), more intra-operative blood transfusion (P < 0.001), and longer postoperative hospital stay (P < 0.001). Filled morphology tumor thrombus also led to more postoperative complications (53% vs. 20%; P < 0.001). CONCLUSION: Compared with floating morphology thrombus, filled morphology thrombus significantly increased the difficulty of surgery in patients with renal cell carcinoma with IVC tumor thrombus.

Whole-genome Sequencing Reveals Autooctoploidy in Chinese Sturgeon and Its Evolutionary Trajectories.

The order Acipenseriformes, which includes sturgeons and paddlefishes, represents "living fossils" with complex genomes that are good models for understanding whole-genome duplication (WGD) and ploidy evolution in fishes. Here, we sequenced and assembled the first high-quality chromosome-level genome for the complex octoploid Acipenser sinensis (Chinese sturgeon), a critically endangered species that also represents a poorly understood ploidy group in Acipenseriformes. Our results show that A. sinensis is a complex autooctoploid species containing four kinds of octovalents (8n), a hexavalent (6n), two tetravalents (4n), and a divalent (2n). An analysis taking into account delayed rediploidization reveals that the octoploid genome composition of Chinese sturgeon results from two rounds of homologous WGDs, and further provides insights into the timing of its ploidy evolution. This study provides the first octoploid genome resource of Acipenseriformes for understanding ploidy compositions and evolutionary trajectories of polyploid fishes.

Deep learning-based pathway-centric approach to characterize recurrent hepatocellular carcinoma after liver transplantation.

BACKGROUND: Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15-20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology. MATERIALS AND METHODS: We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC. RESULTS: The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence. CONCLUSION: Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

Radiomic signatures associated with tumor immune heterogeneity predict survival in locally recurrent nasopharyngeal carcinoma.

BACKGROUND: The prognostic value of traditional clinical indicators for locally recurrent nasopharyngeal carcinoma is limited because of their inability to reflect intratumor heterogeneity. We aimed to develop a radiomic signature to reveal tumor immune heterogeneity and predict survival in locally recurrent nasopharyngeal carcinoma. METHODS: This multicenter, retrospective study included 921 patients with locally recurrent nasopharyngeal carcinoma. A machine learning signature and nomogram based on pretreatment magnetic resonance imaging features were developed for predicting overall survival in a training cohort and validated in 2 independent cohorts. A clinical nomogram and an integrated nomogram were constructed for comparison. Nomogram performance was evaluated by concordance index and receiver operating characteristic curve analysis. Accordingly, patients were classified into risk groups. The biological characteristics and immune infiltration of the signature were explored by RNA-sequencing analysis. RESULTS: The machine learning signature and nomogram demonstrated comparable prognostic ability to a clinical nomogram, achieving concordance indexes of 0.729, 0.718, and 0.731 in the training, internal, and external validation cohorts, respectively. Integration of the signature and clinical variables statistically improved the predictive performance. The proposed signature effectively distinguished patients between risk groups with statistically distinct overall survival rates. Subgroup analysis indicated the recommendation of local salvage treatments for low-risk patients. Exploratory RNA-sequencing analysis revealed differences in interferon response and lymphocyte infiltration between risk groups. CONCLUSIONS: A magnetic resonance imaging-based radiomic signature predicted overall survival more accurately. The proposed signature associated with tumor immune heterogeneity may serve as a valuable tool to facilitate prognostic stratification and guide individualized management for locally recurrent nasopharyngeal carcinoma patients.

Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data.

Quantifying the relationship between light and stands or individual trees is of great significance in understanding tree competition, improving forest productivity, and comprehending ecological processes. However, accurately depicting the spatiotemporal variability of light under complex forest structural conditions poses a challenge, especially for precise forest management decisions that require a quantitative study of the relationship between fine-scale individual tree structure and light. 3D RTMs (3-dimensional radiative transfer models), which accurately characterize the interaction between solar radiation and detailed forest scenes, provide a reliable means for depicting such relationships. This study employs a 3D RTM and LiDAR (light detection and ranging) data to characterize the light environment of larch plantations at a fine spatiotemporal scale, further investigating the relationship between absorbed photosynthetically active radiation (APAR) and forest structures. The impact of specific tree structural parameters, such as crown diameter, crown area, crown length, crown ratio, crown volume, tree height, leaf area index, and a distance parameter assessing tree competition, on the daily-scale cumulative APAR per tree was investigated using a partial least squares regression (PLSR) model. Furthermore, variable importance in projection (VIP) was also calculated from the PLSR. The results indicate that among the individual tree structure parameters, crown volume is the most important one in explaining individual tree APAR (VIP = 4.19), while the competition from surrounding trees still plays a role in explaining individual tree APAR to some extent (VIP = 0.15), and crown ratio contributes the least (VIP = 0.03). Regarding the spatial distribution of trees, the average cumulative APAR per tree of larch plots does not increase with an increase in canopy gap fraction. Tree density and average cumulative APAR per tree were fitted using a natural exponential equation, with a coefficient of determination (R2 = 0.89), and a small mean absolute percentage error (MAPE = 0.03). This study demonstrates the potential of combining 3D RTM with LiDAR data to quantify fine-scale APAR in plantations, providing insights for optimizing forest structure, enhancing forest quality, and implementing precise forest management practices, such as selective breeding for superior tree species.

Factors predicting indistinct plane of surgical capsule in patients underwent HoLEP procedures.

PURPOSE: To evaluate factors that effectively predict indistinct plane (IP) in patients who underwent holmium laser enucleation of the prostate (HoLEP). METHODS: Data of 208 consecutive patients from our HoLEP database were reviewed and analyzed. IP was defined in 107 cases, as the plane could be identified only depending on endoscopic beak dissection rather than laser dissection in the initial stage of HoLEP, whereas the control group consisted of 101 cases. Variables including age, body mass index, prostatic volume (PV), intravesical prostatic protrusion, prostate-specific antigen, prostate-specific antigen density, bladder stones, urinary tract infection, microscopic hematuria, prior biopsy (PB), diabetes, hypertension, history of acute urinary retention, 5-alpha reductase inhibitor treatment, catheter dependency, residual urine, region, smoking, and alcohol consumption were compared between the two groups. The risk factors for predicting the presence of IP were determined using a multivariable binary logistic regression model using a forward selection approach with a focus on improvement in the area under the receiver operating characteristic curve (AUC). RESULTS: The incidence of IP was 51.4% (107/208). PV (OR = 0.977, p < 0.001) and PB (OR = 0.297, p = 0.028) were identified as the independent predictors of capsule plane status. PV with a cutoff of 54 ml had the best predictive effectiveness for IP based on AUC (0.727; 95% CI 0.659-0.795). The specificity and sensitivity of this cutoff were 82.2% and 53.3%, respectively. CONCLUSION: PV is the most reliable factor to predict IP during HoLEP procedures. There is a high possibility of IP in patients with a PV less than 54 ml.

Deep learning-based radiomics model can predict extranodal soft tissue metastasis in gastric cancer.

BACKGROUND: The potential prognostic value of extranodal soft tissue metastasis (ESTM) has been confirmed by increasing studies about gastric cancer (GC). However, the gold standard of ESTM is determined by pathologic examination after surgery, and there are no preoperative methods for assessment of ESTM yet. PURPOSE: This multicenter study aimed to develop a deep learning-based radiomics model to preoperatively identify ESTM and evaluate its prognostic value. METHODS: A total of 959 GC patients were enrolled from two centers and split into a training cohort (N = 551) and a test cohort (N = 236) for ESTM evaluation. Additionally, an external survival cohort (N = 172) was included for prognostic analysis. Four models were established based on clinical characteristics and multiphase computed tomography (CT) images for preoperative identification of ESTM, including a deep learning model, a hand-crafted radiomic model, a clinical model, and a combined model. C-index, decision curve, and calibration curve were utilized to assess the model performances. Survival analysis was conducted to explore the ability of stratifying overall survival (OS). RESULTS: The combined model showed good discrimination of the ESTM [C-indices (95% confidence interval, CI): 0.770 (0.729-0.812) and 0.761 (0.718-0.805) in training and test cohorts respectively], which outperformed deep learning model, radiomics model, and clinical model. The stratified analysis showed this model was not affected by patient's tumor size, the presence of lymphovascular invasion, and Lauren classification (p < 0.05). Moreover, the model score showed strong consistency with the OS [C-indices (95%CI): 0.723 (0.658-0.789, p < 0.0001) in the internal survival cohort and 0.715 (0.650-0.779, p < 0.0001) in the external survival cohort]. More interestingly, univariate analysis showed the model score was significantly associated with occult distant metastasis (p < 0.05) that was missed by preoperative diagnosis. CONCLUSIONS: The model combining CT images and clinical characteristics had an impressive predictive ability of both ESTM and prognosis, which has the potential to serve as an effective complement to the preoperative TNM staging system.

The Application of CT Radiomics in the Diagnosis of Vein Wall Invasion in Patients With Renal Cell Carcinoma Combined With Tumor Thrombus.

OBJECTIVE: The objective of this study was to explore the application of radiomics combined with machine learning to establish different models to assist in the diagnosis of venous wall invasion in patients with renal cell carcinoma and venous tumor thrombus and to evaluate the diagnostic efficacy. MATERIALS AND METHODS: We retrospectively reviewed the data of 169 patients in Peking University Third Hospital from March 2015 to January 21, who was diagnosed as renal mass with venous invasion. According to the intraoperative findings, 111 patients were classified to the venous wall invasion group and 58 cases in the non-invasion group. ITK-snap was used for tumor segmentation and PyRadiomics 3.0.1 package was used for feature extraction. A total of 1598 features could be extracted from each CT image. The patients were divided into training set and testing set by time. The elastic-net regression with 4-fold cross-validation was used as a dimension-reduction method. After feature selection, a support vector machines (SVM) model, a logistic regression (LR) model, and an extra trees (ET) model were established. Then the sensitivity, specificity, accuracy, and the area under the curve (AUC) were calculated to evaluate the diagnostic performance of each model on the testing set. RESULTS: Patients before September 2019 were divided into the training set, of which 88 patients were in the invasion group and 42 patients were in the non-invasion group. The others were in the testing set, of which 32 patients were in the invasion group and 16 patients were in the non-invasion group. A total of 34 radiomics features were obtained by the elastic-net regression. The SVM model had an AUC value of 0.641 (95% CI, 0.463-0.769), a sensitivity of 1.000, and a specificity of 0.062. The LR model had an AUC value of 0.769 (95% CI, 0.620-0.877), a sensitivity of 0.913, and a specificity of 0.312. The ET model had an AUC value of 0.853 (95% CI, 0.734-0.948), a sensitivity of 0.783, and a specificity of 0.812. Among the 3 models, the ET model had the best diagnostic effect, with a good balance of sensitivity and specificity. And the higher the tumor thrombus grade, the better the diagnostic efficacy of the ET model. In inferior vena cava tumor thrombus, the sensitivity, specificity, accuracy, and AUC of ET model can be improved to 0.889, 0.800, 0.857, 0.878 (95% CI, 0.745-1.000). CONCLUSION: Machine learning combined with radiomics method can effectively identify whether venous wall was invaded by tumor thrombus and has high diagnostic efficacy with an AUC of 0.853 (95% CI, 0.734-0.948).

Radiomics and Deep Learning in Nasopharyngeal Carcinoma: A Review.

Nasopharyngeal carcinoma is a common head and neck malignancy with distinct clinical management compared to other types of cancer. Precision risk stratification and tailored therapeutic interventions are crucial to improving the survival outcomes. Artificial intelligence, including radiomics and deep learning, has exhibited considerable efficacy in various clinical tasks for nasopharyngeal carcinoma. These techniques leverage medical images and other clinical data to optimize clinical workflow and ultimately benefit patients. In this review, we provide an overview of the technical aspects and basic workflow of radiomics and deep learning in medical image analysis. We then conduct a detailed review of their applications to seven typical tasks in the clinical diagnosis and treatment of nasopharyngeal carcinoma, covering various aspects of image synthesis, lesion segmentation, diagnosis, and prognosis. The innovation and application effects of cutting-edge research are summarized. Recognizing the heterogeneity of the research field and the existing gap between research and clinical translation, potential avenues for improvement are discussed. We propose that these issues can be gradually addressed by establishing standardized large datasets, exploring the biological characteristics of features, and technological upgrades.

Prevention, incidence, and risk factors of chyle leak after radical nephrectomy and thrombectomy.

BACKGROUND: To define the incidence and risk factors of chyle leak (CL) after radical nephrectomy and thrombectomy and to determine the impact of chyle leak on oncological outcomes. PATIENTS AND METHODS: A total of 445 patients who underwent radical nephrectomy and thrombectomy between January 2014 and January 2023 were included. CL is defined as the drainage of chyle with a triglyceride level greater than 110 mg/dL after oral intake or enteral nutrition. Multivariate logistic regression analysis was performed to identify the risk factors of postoperative (CL). The Kaplan-Meier curves were used to compare overall survival and cancer-specific survival. RESULTS: 44 patients (9.9%) were diagnosed as (CL). All patients developed CL within 6 days after the operation with a median time of 3 days. In multivariate logistic regression analysis, Mayo grade and side were independent patient-related risk factors. In addition, operation approach, operation time, and number of lymph nodes harvested were independent surgery-related risk factors. Between the CL group and the non-CL group, neither overall survival nor cancer-specific survival showed statistical differences. CONCLUSION: Based on this retrospective study of renal cell carcinoma and tumor thrombus patients in our center, we found that the risk factors were Mayo grade, side, operation approach, operation time, and number of lymph nodes harvested, and the occurrence of CL significantly prolonged hospital stay, but had no effect on long-term oncological outcomes.

Risk of ocular adverse events with aromatase inhibitors.

OBJECTIVE: Aromatase inhibitors (AIs) are a class of medications used for adjuvant treatment of breast cancer. Recent case reports suggest that AIs may be associated with various ocular adverse events (AEs). This study evaluates the risk of ocular AEs in patients who take AIs. METHOD: Disproportionality analysis was performed using data from the U.S. Food and Drug Administration's Adverse Events Reporting System database from 2004 to 2022. All cases of vitreomacular traction, macular edema, retinal deposits, retinal artery occlusion, macular hole, retinal hemorrhage, uveitis, retinal tear, retinal detachment, dry eye disease, blepharitis, and optic neuropathy were searched for the 3 AIs anastrozole, letrozole, and exemestane. A search also was performed on trastuzumab as a control. Reported odds ratios (RORs) and corresponding 95% CIs were computed. RESULTS: We identified 322 ocular AEs of interest for the 3 AIs and 55 for trastuzumab. Anastrozole had the most AEs (n = 163) and was found to have strong associations with vitreomacular traction (ROR = 665; 95% CI, 352-1255), macular edema (ROR = 37; 95% CI, 25-54), retinal deposits (ROR = 11; 95% CI, 2-77), and uveitis (ROR = 6; 95% CI, 4-9). Letrozole had strong associations with retinal deposits (ROR = 8, 95% CI, 1-57) and retinal artery occlusion (ROR = 6; 95% CI, 3-11). Exemestane had a strong association with macular holes (ROR = 10; 95% CI, 3-30). CONCLUSION: Disproportionality analysis revealed an increased risk of ocular AEs with each of the AIs. This study calls for clinicians, especially oncologists and ophthalmologists, to be vigilant in patients who are on AI therapy, allowing them to provide prompt interventions to mitigate further ocular morbidities.

Gas Evolution Principle during Gas Drainage from a Drill Hole along the Coal Seam and Reasonable Borehole Layout Spacing.

The efficiency of coal seam gas drainage can be further improved by the accurate mastery of the gas evolution principle during gas drainage from the drill hole along the coal seam and reasonable optimization of borehole layout spacing. Based on the actual geological conditions of the no. 2 coal seam in a coal mine in Guizhou, China, and relevant control equations, a fluid-structure interaction model of gas drainage from a drill hole along the coal seam was established in this paper. Besides, numerical simulation research on the gas evolution principle during gas drainage along the coal seam and optimization of the borehole layout spacing was carried out with the COMSOL simulation software; and these were verified in combination with the project site. The results showed that in the early stage of gas drainage the gas pressure in the area near the drill holes decreased significantly. As the gas drainage went on, the degree of influence decreased gradually. During the gas drainage from adjacent drill holes, the gas pressure in the coal body between the holes decreased rapidly, and the migration was obvious. With the increase of the spacing between the drill holes, the drainage superposition effect between these holes gradually decreased until the influence area around a single hole is independently distributed in a circle-like shape, indicating that the optimization and the reasonable spacing of the drill holes are directly related to the effect of the gas drainage. With the increase of drilling spacing, the superposition effect of extraction between the holes gradually decreased until the influence area around a single hole is independently distributed in the shape of a circle, indicating that the optimization of drilling spacing is directly related to the effect of gas drainage. The results of numerical simulation were verified by analyzing the three-dimensional map of the gas pressure during the period of gas drainage at the project site and by comparing and examining the rational borehole layout spacing of the drill hole along the coal seam. The results of this study can be used to determine the spacing of gas extraction boreholes and improve the efficiency of gas extraction in the no. 2 coal seam of a coal mine in Guizhou, China, as well as to provide a reference for the gas pressure evolution, velocity field distribution, the prediction of effective drainage area, and the selection of rational borehole layout spacing during gas drainage.

Radiomic signatures reveal multiscale intratumor heterogeneity associated with tissue tolerance and survival in re-irradiated nasopharyngeal carcinoma: a multicenter study.

BACKGROUND: Post-radiation nasopharyngeal necrosis (PRNN) is a severe adverse event following re-radiotherapy for patients with locally recurrent nasopharyngeal carcinoma (LRNPC) and associated with decreased survival. Biological heterogeneity in recurrent tumors contributes to the different risks of PRNN. Radiomics can be used to mine high-throughput non-invasive image features to predict clinical outcomes and capture underlying biological functions. We aimed to develop a radiogenomic signature for the pre-treatment prediction of PRNN to guide re-radiotherapy in patients with LRNPC. METHODS: This multicenter study included 761 re-irradiated patients with LRNPC at four centers in NPC endemic area and divided them into training, internal validation, and external validation cohorts. We built a machine learning (random forest) radiomic signature based on the pre-treatment multiparametric magnetic resonance images for predicting PRNN following re-radiotherapy. We comprehensively assessed the performance of the radiomic signature. Transcriptomic sequencing and gene set enrichment analyses were conducted to identify the associated biological processes. RESULTS: The radiomic signature showed discrimination of 1-year PRNN in the training, internal validation, and external validation cohorts (area under the curve (AUC) 0.713-0.756). Stratified by a cutoff score of 0.735, patients with high-risk signature had higher incidences of PRNN than patients with low-risk signature (1-year PRNN rates 42.2-62.5% vs. 16.3-18.8%, P < 0.001). The signature significantly outperformed the clinical model (P < 0.05) and was generalizable across different centers, imaging parameters, and patient subgroups. The radiomic signature had prognostic value concerning its correlation with PRNN-related deaths (hazard ratio (HR) 3.07-6.75, P < 0.001) and all causes of deaths (HR 1.53-2.30, P < 0.01). Radiogenomics analyses revealed associations between the radiomic signature and signaling pathways involved in tissue fibrosis and vascularity. CONCLUSIONS: We present a radiomic signature for the individualized risk assessment of PRNN following re-radiotherapy, which may serve as a noninvasive radio-biomarker of radiation injury-associated processes and a useful clinical tool to personalize treatment recommendations for patients with LANPC.

Adjuvant Chemotherapy Improves Survival for Children With Massive Choroidal Invasion of Retinoblastoma.

Purpose: The purpose of this study was to investigate the effect of adjuvant chemotherapy on outcomes of children with massive choroidal invasion (MCI). Methods: In this study, we reviewed the 5-year relapse-free survival (RFS) and overall survival (OS) of children diagnosed with MCI, managed with or without adjuvant chemotherapy. Excluded were children with additional other high-risk features (post-laminar optic nerve invasion, scleral invasion, or overt extraocular disease). Results: Of 3566 children diagnosed with retinoblastoma, 2023 had enucleation, and 60 eyes of 60 children had pathology showing MCI without concomitant high-risk features. Enucleation was primary (22, 37%), or secondary (38, 63%) after failed eye salvage. Adjuvant systemic chemotherapy (median = 4, range = 1-8 cycles) was given to 48 of 60 (80%) children; 12 of 60 (20%) children had no adjuvant therapy. Five-year RFS was 88.5% (95% confidence interval [CI] = 79.7%-97.3%) and 5-year OS was 90.1% (95% CI = 81.7%-98.5%). Pre-enucleation chemotherapy did not affect RFS (89.7% vs. 75.0%; P = 0.657). Adjuvant chemotherapy improved RFS (97.2% vs. 55.6%; P < 0.001) and OS (97.2% vs. 66.7%; P < 0.001). In subgroup analysis, adjuvant chemotherapy improved RFS for both primarily enucleated (5-year RFS 100% vs. 50.0%; P = 0.002) and secondarily enucleated children (5-year RFS 95.8% vs. 60.0%; P = 0.005). The number of children treated with adjuvant chemotherapy to prevent one post-enucleation systemic relapse or death is three. Conclusions: Adjuvant chemotherapy significantly decreased the risk of tumor relapse and death for children with pathological MCI. For every three children treated with adjuvant chemotherapy, one systemic relapse or death could be prevented.

Human umbilical cord mesenchymal stem cell-derived exosomes combined with gelatin methacryloyl hydrogel to promote fractional laser injury wound healing.

To investigate whether human umbilical cord mesenchymal stem cell-derived exosomes combined with gelatin methacryloyl (GelMA) hydrogel are beneficial in promoting healing of laser-injured skin wounds in mice. Supernatants of cultured human umbilical cord mesenchymal stem cells (HUC-MSCs) were collected to obtain human umbilical cord MSC-derived exosomes (HUC-MSCs-Exos), which were combined with GelMA hydrogel complex to treat a mouse fractional laser injury model. The study was divided into PBS group, EX (HUC-MSCs-Exos) group, GEL (GelMA hydrogel) group and EX+GEL (HUC-MSCs-Exos combined with GelMA hydrogel) group. The healing of laser-injured skin in each group was observed by gross view and dermatoscopy, and changes in skin structure, angiogenesis and proliferation-related indexes were observed during the healing process of laser-injured skin in each group. The results of the animal experiments showed that the EX and GEL groups alone and the EL+EX group exhibited less inflammatory response compared to the PBS group. The EX and GEL groups showed marked tissue proliferation and favourable angiogenesis, which promoted the wound healing well. The GEL+EX group had the most significant promotion of wound healing compared to the PBS group. qPCR results showed that the expression levels of proliferation-related factors, including KI67 and VEGF and angiogenesis-related factor CD31, were significantly higher in the GEL+EX group than in the other groups, with a time-dependent effect. The combination of HUC-MSCs-Exos and GelMA hydrogel is beneficial in reducing the early inflammatory response of laser-injured skin in mice and promoting its proliferation and angiogenesis, which in turn promotes wound healing.

Long-term outcomes after cytoreductive nephrectomy and thrombectomy of patients with metastatic renal cell carcinoma with venous tumor thrombus: a retrospective study from a large Chinese center.

BACKGROUND: Targeted therapy combined with immunotherapy is the current first-line treatment for metastatic renal cell carcinoma (mRCC), but patients with tumor thrombus (TT) may suffer from lower limb edema or even sudden cardiac death, so the purpose of this study is to investigate the efficacy and safety of surgical treatment in patients with mRCC and TT and explore worse factors to affect the prognosis in this series of patients. PATIENTS AND METHODS: A total of 85 mRCC patients with TT who received cytoreductive nephrectomy and thrombectomy at our medical center from 2014 to 2023 are included. All patients received postoperative systemic therapy. Overall survival (OS) is defined as the time from surgery to death due to any reason or the last follow-up. Kaplan-Meier analysis was performed to evaluate OS and differences among groups were tested by log-rank. Multivariable Cox proportional hazards analysis was performed to ascertain independent relationships between clinicopathological factors and OS. RESULTS: The median age of patients was 58 years old. Eleven patients (12.9%) had no symptoms, 39 patients (45.9%) had local symptoms, 15 patients (17.6%) had systemic symptoms, and 20 patients (23.5%) had both. Mayo grade of TT was 0, 1, 2, 3, and 4 for 12, 27, 31, 7, and 8 patients respectively. Fifty-five patients had lung metastasis, 23 had bone metastasis, 16 had liver metastasis, 13 had adrenal metastasis, and 9 had lymph node metastasis. Of all patients, 17 patients had multiple metastases. The median operation time is 289 min and the median intraoperative hemorrhage is 800 ml. Twenty-eight patients experienced postoperative complications, 8 of which were serious complications of modified Clavien grade III or higher. The median OS of all patients was 33 months and median follow up time was 26 months. In multivariate analysis, systemic symptom (p = 0.00753), pathological type (p = 0.0166), sarcomatous degeneration (p = 0.0334), and perirenal fat infiltration (p = 0.0202) are independent predictors of OS. CONCLUSION: Cytoreductive nephrectomy and thrombectomy is relatively safe and effective for patients with mRCC accompanied by TT. In this series of patients, the worse prognosis is associated with systemic symptoms, non-clear cell carcinoma, sarcomatous degeneration and perirenal fat infiltration.