Predicting lymphovascular invasion in non-small cell lung cancer using deep convolutional neural networks on preoperative chest CT.

RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images with deep learning technology. MATERIALS AND METHODS: This retrospective observational study included a series of consecutive patients who underwent surgical resection for non-small cell lung cancer (NSCLC) and received pathologically confirmed diagnoses. The cohort was randomly divided into a training group comprising 70 % of the patients and a validation group comprising the remaining 30 %. Four distinct deep convolutional neural network (DCNN) prediction models were developed, incorporating different combination of two-dimensional (2D) and three-dimensional (3D) CT imaging features as well as clinical-radiological data. The predictive capabilities of the models were evaluated by receiver operating characteristic curves (AUC) values and confusion matrices. The Delong test was utilized to compare the predictive performance among the different models. RESULTS: A total of 3034 patients with NSCLC were recruited in this study including 106 LVI+ patients. In the validation cohort, the Dual-head Res2Net_3D23F model achieved the highest AUC of 0.869, closely followed by the models of Dual-head Res2Net_3D3F (AUC, 0.868), Dual-head Res2Net_3D (AUC, 0.867), and EfficientNet-B0_2D (AUC, 0.857). There was no significant difference observed in the performance of the EfficientNet-B0_2D model when compared to the Dual-head Res2Net_3D3F and Dual-head Res2Net_3D23F. CONCLUSION: Findings of this study suggest that utilizing deep convolutional neural network is a feasible approach for predicting pathological LVI in patients with NSCLC.

Overexpression of NtEXPA7 promotes seedling growth and resistance to root-knot nematode in tobacco.

Root-knot nematode (RKN) is one of the most damaging plant pathogen in the world. They exhibit a wide host range and cause serious crop losses. The cell wall, encasing every plant cell, plays a crucial role in defending of RKN invasion. Expansins are a group of cell wall proteins inducing cell wall loosening and extensibility. They are widely involved in the regulation of plant growth and the response to biotic and abiotic stresses. In this study, we have characterized the biological function of tobacco (Nicotiana tabacum) NtEXPA7, the homologue of Solyc08g080060.2 (SlEXPA18), of which the transcription level was significantly reduced in susceptible tomato upon RKN infection. The expression of NtEXPA7 was up-regulated after inoculation of RKNs. The NtEXPA7 protein resided in the cell wall. Overexpression of NtEXPA7 promoted the seedling growth of transgenic tobacco. Meanwhile the increased expression of NtEXPA7 was beneficial to enhance the resistance against RKNs. This study expands the understanding of biological role of expansin in coordinate plant growth and disease resistance.

Convolutional neural network applied to preoperative venous-phase CT images predicts risk category in patients with gastric gastrointestinal stromal tumors.

OBJECTIVE: The risk category of gastric gastrointestinal stromal tumors (GISTs) are closely related to the surgical method, the scope of resection, and the need for preoperative chemotherapy. We aimed to develop and validate convolutional neural network (CNN) models based on preoperative venous-phase CT images to predict the risk category of gastric GISTs. METHOD: A total of 425 patients pathologically diagnosed with gastric GISTs at the authors' medical centers between January 2012 and July 2021 were split into a training set (154, 84, and 59 with very low/low, intermediate, and high-risk, respectively) and a validation set (67, 35, and 26, respectively). Three CNN models were constructed by obtaining the upper and lower 1, 4, and 7 layers of the maximum tumour mask slice based on venous-phase CT Images and models of CNN_layer3, CNN_layer9, and CNN_layer15 established, respectively. The area under the receiver operating characteristics curve (AUROC) and the Obuchowski index were calculated to compare the diagnostic performance of the CNN models. RESULTS: In the validation set, CNN_layer3, CNN_layer9, and CNN_layer15 had AUROCs of 0.89, 0.90, and 0.90, respectively, for low-risk gastric GISTs; 0.82, 0.83, and 0.83 for intermediate-risk gastric GISTs; and 0.86, 0.86, and 0.85 for high-risk gastric GISTs. In the validation dataset, CNN_layer3 (Obuchowski index, 0.871) provided similar performance than CNN_layer9 and CNN_layer15 (Obuchowski index, 0.875 and 0.873, respectively) in prediction of the gastric GIST risk category (All P >.05). CONCLUSIONS: The CNN based on preoperative venous-phase CT images showed good performance for predicting the risk category of gastric GISTs.

Radiomics analysis of contrast-enhanced computerized tomography for differentiation of gastric schwannomas from gastric gastrointestinal stromal tumors.

PURPOSE: To assess the performance of radiomics-based analysis of contrast-enhanced computerized tomography (CE-CT) images for distinguishing GS from gastric GIST. METHODS: Forty-nine patients with GS and two hundred fifty-three with GIST were enrolled in this retrospective study. CT features were evaluated by two associate chief radiologists. Radiomics features were extracted from portal venous phase images using Pyradiomics software. A non-radiomics dataset (combination of clinical characteristics and radiologist-determined CT features) and a radiomics dataset were used to build stepwise logistic regression and least absolute shrinkage and selection operator (LASSO) logistic regression models, respectively. Model performance was evaluated according to sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve, and Delong's test was applied to compare the area under the curve (AUC) between different models. RESULTS: A total of 1223 radiomics features were extracted from portal venous phase images. After reducing dimensions by calculating Pearson correlation coefficients (PCCs), 20 radiomics features, 20 clinical characteristics + CT features were used to build the models, respectively. The AUC values for the models using radiomics features and those using clinical features were more than 0.900 for both the training and validation groups. There were no significant differences in predictive performance between the radiomic and clinical data models according to Delong's test. CONCLUSION: A radiomics-based model applied to CE-CT images showed comparable predictive performance to senior physicians in the differentiation of GS from GIST.

Resistance to Planthoppers and Southern Rice Black-streaked Dwarf Virus in Rice Germplasms.

The damage caused by white-back planthopper (WBPH, Sogatella furcifera) and brown planthopper (BPH, Nilaparvata lugens), as well as southern rice black-streaked dwarf virus (SRBSDV), considerably decreases grain yield of rice. Identification of rice germplasms with sufficient resistance to planthoppers and SRBSDV is essential to the breeding and deployment of resistant varieties and hence the control of the pests and disease. In this study, 318 rice accessions were evaluated for their reactions to the infestation of both BPH and WBPH at the seedling stage using the standard seed-box screening test (SSST) method, insect quantification was further conducted at the end of tillering and grain-filling stages in field trials. Accessions HN12-239 and HN12-328 were resistant to both BPH and WBPH at all tested stages. Field trials were conducted to identify resistance in the collection to SRBSDV based on the virus infection rate under artificial inoculation. RHT and HN12-239 were moderately resistant to SRBSDV. In addition, we found that WBPH did not penetrate stems with stylets, but did more probing bouts and then xylem sap ingestion when feeding on HN12-239 than the susceptible control rice TN1. The resistance of rice accessions HN12-239, HN12-328 and RHT to BPH, WBPH and/or SRBSDV, should be valuable to the development of resistant rice varieties.

Cutoff value of IC50 for drug sensitivity in patient-derived tumor organoids in colorectal cancer.

Patient-derived tumor organoids (PDTOs) have the potential to be used to predict the patient response to chemotherapy. However, the cutoff value of the half-maximal inhibition concentration (IC50) for PDTO drug sensitivity has not been validated with clinical cohort data. We established PDTOs and performed a drug test in 277 samples from 242 CRC patients who received FOLFOX or XELOX chemotherapy. After follow-up and comparison of the PDTO drug test and final clinical outcome results, the optimal IC50 cutoff value for PDTO drug sensitivity was 43.26 µmol/L. This PDTO drug test-defined cutoff value could predict patient response with 75.36% sensitivity, 74.68% specificity, and 75% accuracy. Moreover, this value distinguished groups of patients with significant differences in survival benefit. Our study is the first to define the IC50 cutoff value for the PDTO drug test to effectively distinguish CRC patients with chemosensitivity or nonsensitivity and predict survival benefits.

Use of Carbon Nanoparticles to Improve the Efficiency of Harvesting Lymph Nodes in Rectal Cancer.

BACKGROUND: The accurate determination of lymph node status in patients with rectal cancer requires harvesting a certain number of lymph nodes. This study investigated whether using carbon nanoparticles (CNs) could improve the efficiency of harvesting lymph nodes in rectal cancer patients. MATERIALS AND METHODS: Data from patients with rectal cancer treated with radical resection were collected from Nanfang Hospital between January 2014 and June 2021. Patients in the CN group received a CN suspension 1 day before surgery, which was endoscopically injected around the tumor. A 1:1 case-matched study was performed using the propensity score. The efficiency of harvesting lymph nodes was investigated by comparing the number of total nodes, total time, and percentage of nodes <5 mm in size between the CN and non-CN groups. RESULTS: A total of 768 patients were included, with 246 patients who underwent CN injection and 522 patients who did not. After matching, 246 pairs of patients were analyzed. After matching, the number of total nodes of each sample was significantly higher in the CN group than in the non-CN group ( P <0.001). The total time for node detection ( P <0.001) was significantly shorter in the CN group. The percentage of nodes <5 mm in size was increased significantly in the CN group ( P <0.001). Among patients with clinical staging I/II, the difference in positive LNs was significant (21.79% vs. 11.95%, P =0.029). CONCLUSIONS: The application of CNs improved the efficiency of harvesting lymph nodes during rectal cancer surgery.

Wave Attenuation in Additively Manufactured Polymer Acoustic Black Hole Structures Considering the Viscoelastic Effect.

The acoustic black hole (ABH) is a feature commonly found in thin-walled structures that is characterized by a diminishing thickness and damping layer with an efficient wave energy dissipation effect, which has been extensively studied. The additive manufacture of polymer ABH structures has shown promise as a low-cost method to manufacture ABHs with complex geometries, exhibiting even more effective dissipation. However, the commonly used elastic model with viscous damping for both the damping layer and polymer ignores the viscoelastic changes that occur due to variations in frequency. To address this, we used Prony exponential series expansion to describe the viscoelastic behavior of the material, where the modulus is represented by a summation of decaying exponential functions. The parameters of the Prony model were obtained through experimental dynamic mechanical analysis and applied to finite element models to simulate wave attenuation characteristics in polymer ABH structures. The numerical results were validated by experiments, where the out-of-plane displacement response under a tone burst excitation was measured by a scanning laser doppler vibrometer system. The experimental results illustrated good consistency with the simulations, demonstrating the effectiveness of the Prony series model in predicting wave attenuation in polymer ABH structures. Finally, the effect of loading frequency on wave attenuation was studied. The findings of this study have implications for the design of ABH structures with improved wave attenuation characteristics.

Activation of Sphingomyelin Phosphodiesterase 3 in Liver Regeneration Impedes the Progression of Colorectal Cancer Liver Metastasis Via Exosome-Bound Intercellular Transfer of Ceramides.

BACKGROUND & AIMS: The machinery that prevents colorectal cancer liver metastasis (CRLM) in the context of liver regeneration (LR) remains elusive. Ceramide (CER) is a potent anti-cancer lipid involved in intercellular interaction. Here, we investigated the role of CER metabolism in mediating the interaction between hepatocytes and metastatic colorectal cancer (CRC) cells to regulate CRLM in the context of LR. METHODS: Mice were intrasplenically injected with CRC cells. LR was induced by 2/3 partial hepatectomy (PH) to mimic the CRLM in the context of LR. The alteration of corresponding CER-metabolizing genes was examined. The biological roles of CER metabolism in vitro and in vivo were examined by performing a series of functional experiments. RESULTS: Induction of LR augmented apoptosis but promoted matrix metalloproteinase 2 (MMP2) expression and epithelial-mesenchymal transition (EMT) to increase the invasiveness of metastatic CRC cells, resulting in aggressive CRLM. Up-regulation of sphingomyelin phosphodiesterase 3 (SMPD3) was determined in the regenerating hepatocytes after LR induction and persisted in the CRLM-adjacent hepatocytes after CRLM formation. Hepatic Smpd3 knockdown was found to further promote CRLM in the context of LR by abolishing mitochondrial apoptosis and augmenting the invasiveness in metastatic CRC cells by up-regulating MMP2 and EMT through promoting the nuclear translocation of ß-catenin. Mechanistically, we found that hepatic SMPD3 controlled the generation of exosomal CER in the regenerating hepatocytes and the CRLM-adjacent hepatocytes. The SMPD3-produced exosomal CER critically conducted the intercellular transfer of CER from the hepatocytes to metastatic CRC cells and impeded CRLM by inducing mitochondrial apoptosis and restricting the invasiveness in metastatic CRC cells. The administration of nanoliposomal CER was found to suppress CRLM in the context of LR substantially. CONCLUSIONS: SMPD3-produced exosomal CER constitutes a critical anti-CRLM mechanism in LR to impede CRLM, offering the promise of using CER as a therapeutic agent to prevent the recurrence of CRLM after PH.

Development and validation of a collagen signature to predict the prognosis of patients with stage II/III colorectal cancer.

The tumor, nodes and metastasis (TNM) classification system provides useful but incomplete prognostic information and lacks the assessment of the tumor microenvironment (TME). Collagen, the main component of the TME extracellular matrix, plays a nonnegligible role in tumor invasion and metastasis. In this cohort study, we aimed to develop and validate a TME collagen signature (CSTME) for prognostic prediction of stage II/III colorectal cancer (CRC) and to compare the prognostic values of "TNM stage + CSTME" with that of TNM stage alone. Results indicated that the CSTME was an independent prognostic risk factor for stage II/III CRC (hazard ratio: 2.939, 95% CI: 2.180-3.962, p < 0.0001), and the integration of the TNM stage and CSTME had a better prognostic value than that of the TNM stage alone (AUC(TNM+CSTME) = 0.772, AUC TNM = 0.687, p < 0.0001). This study provided an application of "seed and soil" strategy for prognosis prediction and individualized therapy.

Sex-specific bone and muscular morphological features in ischiofemoral impingement: A three-dimensional study.

The study aimed to investigate how hip bone and muscular morphology features differ between ischiofemoral impingement (IFI) patients and healthy subjects among males and females. Three-dimensional models were reconstructed based on magnetic resonance imaging images from IFI patients and healthy subjects of different sexes. Bone morphological parameters and the cross-sectional area of the hip abductors were measured. The diameter and angle of the pelvis were compared between patients and healthy subjects. Bone parameters of the hip and cross-sectional area of the hip abductors were compared between affected and healthy hips. The comparison results of some parameters were significant for females but not males. For females, the comparison results of pelvis parameters showed that the anteroposterior diameter of the pelvic inlet (p = 0.001) and intertuberous distance (p < 0.001) were both larger in IFI patients than in healthy subjects. Additionally, the comparison results of hip parameters showed that the neck shaft angle (p < 0.001) and the cross-sectional area of the gluteus medius (p < 0.001) and gluteus minimus (p = 0.005) were smaller, while the cross-sectional area of the tensor fasciae latae (p < 0.001) was significantly larger in affected hips. Morphological changes in IFI patients demonstrated sexual dimorphism, including bone and muscular morphology. Differences in the anteroposterior diameter of the pelvic inlet, intertuberous distance, neck shaft angle, gluteus medius, and gluteus minimus may explain why females are more susceptible to IFI.

A Clinicopathological Feature-Based Nomogram for Predicting the Likelihood of D3 Lymph Node Metastasis in Right-Sided Colon Cancer Patients.

BACKGROUND: Despite advancements in treating right-sided colon cancer patients, the ideal scope of lymphadenectomy remains controversial. OBJECTIVE: Our objective was to investigate the likelihood of D3 lymph node metastasis in right-sided colon cancer patients and develop a clinicopathological feature-based nomogram for D3 lymphadenectomy. DESIGN: We retrospectively analyzed 286 right-sided colon cancer patients who underwent D3 lymphadenectomy. The patients were divided into 2 groups based on whether D3 lymph node metastasis was positive. Then, univariable and multivariable logistic regression analyses were performed to obtain independent risk factors for predicting D3 lymph node metastasis. Moreover, we performed receiver operating characteristic curve analyses to evaluate the predictive power of the model. SETTING: This study was conducted at Nanfang Hospital of Southern Medical University in China. PATIENTS: A total of 286 consecutive patients who underwent right hemicolectomy and D3 lymphadenectomy as a primary treatment for right-sided colon cancer between January 2016 and December 2019 were enrolled in this study. MAIN OUTCOME MEASURES: The primary measures were independent risk factors for predicting D3 lymph node metastasis in right-sided colon cancer. RESULTS: The D3 lymph node metastasis rate in right-sided colon cancer patients was 16.1% (46/286). D3 lymphadenectasis on CT, lymphatic invasion, and T4 tumors were filtered out as independent risk factors for D3 lymph node metastasis according to the multivariable logistic regression analysis. We established a nomogram that predicted D3 lymph node metastasis of right-sided colon cancer on the combination of the 3 factors with an area under the curve of 0.717 (95% CI, 0.629-0.806). LIMITATIONS: This was a retrospective study from a single center. CONCLUSIONS: We developed a valuable clinicopathological feature-based nomogram to predict the incidence of D3 lymph node metastasis in right-sided colon cancer patients. Patients with D3 lymphadenectasis on CT, preoperative T4 tumors, and lymphatic invasion should undergo D3 lymphadenectomy. See Video Abstract at http://links.lww.com/DCR/B852 . UN NOMOGRAMA BASADO EN CARACTERSTICAS CLNICOPATOLGICAS PARA PREDECIR LA PROBABILIDAD DE METSTASIS EN GANGLIOS LINFTICOS D EN PACIENTES CON CNCER DE COLON DERECHO: ANTECEDENTES:A pesar de los avances en el tratamiento de pacientes con cáncer de colon derecho, el ámbito ideal de la linfadenectomía sigue siendo controvertido.OBJETIVO:Investigar la probabilidad de metástasis en los ganglios linfáticos D3 en pacientes con cáncer de colon derecho y desarrollar un nomograma basado en características clínico-patológicas basado para la linfadenectomía D3.DISEÑO:Analizamos retrospectivamente a 286 pacientes con cáncer de colon derecho que se sometieron a linfadenectomía D3. Los pacientes se dividieron en dos grupos en función de si eran positivos para metástasis en los ganglios linfáticos D3. Luego, se realizaron análisis de regresión logística univariable y multivariable para obtener factores de riesgo independientes para predecir metástasis en los ganglios linfáticos D3. Además, realizamos análisis de las curvas de características operatorias del receptor para evaluar el poder predictivo del modelo.SEDE:Este estudio se realizó en el Hospital Nanfang de la Universidad Médica del Sur en China.PACIENTES:Un total de 286 pacientes consecutivos que se sometieron a hemicolectomía derecha y linfadenectomía D3 como tratamiento primario para el cáncer de colon derecho entre enero de 2016 y diciembre de 2019 se inscribieron en este estudio.PRINCIPALES MEDIDAS DE RESULTADO:Las medidas primarias fueron factores de riesgo independientes para predecir las metástasis en ganglios linfáticos D3 en el cáncer de colon derecho.RESULTADOS:La tasa de metástasis en los ganglios linfáticos D3 en pacientes con cáncer de colon del lado derecho fue del 16,1% (46/286). El aumento de tamaño de ganglios D3 en la TC, la invasión linfática y los tumores T4 se filtraron como factores de riesgo independientes de metástasis en los ganglios linfáticos D3 de acuerdo con el análisis de regresión logística multivariable. Establecimos un nomograma que predijo metástasis en los ganglios linfáticos D3 del cáncer de colon derecho en la combinación de los tres factores con un área bajo la curva de 0,717 (IC del 95%, 0,629-0,806).LIMITACIONES:Este fue un estudio retrospectivo de un solo centro.CONCLUSIONES:Desarrollamos un valioso nomograma basado en características clínico-patológicas para predecir la incidencia de metástasis en los ganglios linfáticos D3 en pacientes con cáncer de colon derecho. Los pacientes con crecimiento de ganglios D3 en TC, tumores con clasificación preoperatoria T4 e invasión linfática, deben ser sometidos a linfadenectomía D3. Consulte Video Resumen en http://links.lww.com/DCR/B852 . (Traducción-Dr. Juan Carlos Reyes ).

Indocyanine green for radical lymph node dissection in patients with sigmoid and rectal cancer: randomized clinical trial.

BACKGROUND: D3 lymph node dissection is recommended for patients with advanced sigmoid and rectal cancer in Japan. This trial aimed to investigate the feasibility of indocyanine green (ICG) as a tracer to increase the nodal harvest during D3 lymph node dissection in patients with sigmoid and rectal cancer. METHODS: This prospective randomized clinical trial was performed between May 2021 and April 2022. The inclusion criteria were patients with stage I-III sigmoid or rectal cancer eligible for laparoscopic resection. Patients were 1: 1 randomized to either the ICG group (endoscopic ICG injection at the tumour site and intraoperative imaging to guide dissection) or the control group (routine laparoscopic white-light imaging). All patients were treated with D3 dissection, and the primary outcome was the number of harvested lymph nodes at the D3 level. RESULTS: Out of 210 patients screened, a total of 66 patients were enrolled and randomized. Patients in the two groups presented similar ages and clinical stages (ICG group versus control group, median age of 58.0 versus 58.5 years; stage III 36.4 per cent versus 36.4 per cent, whereas the rate of rectal cancer was 27.3 per cent versus 48.5 per cent respectively). ICG imaging was helpful for completely dissecting D3 lymph nodes and could identify a median of more than 2 (range 1-6) D3 lymph nodes neglected by routine laparoscopic white-light imaging during surgery. The median number of D3 lymph nodes harvested in the ICG group was significantly higher than that in the control group (7.0 versus 5.0, P = 0.003); however, there was no significant difference in the median numbers of positive D1, D2, and D3 lymph nodes between the two groups. CONCLUSION: ICG is safe and feasible to guide D3 lymph node dissection and can increase the number of harvested D3 lymph nodes in patients with sigmoid and rectal cancer. Registration number: NCT04848311 (http://www.clinicaltrials.gov).

Pantranscriptome combined with phenotypic quantification reveals germplasm kinship and regulation network of bract color variation in Bougainvillea.

Bracts are the metamorphic non-flower organ in angiosperm plants. The variation of the color and shape of bracts was found to be neo-functionalized (i.e., similar to petals), garnering research interest as a pollinator attractor. Bougainvillea is known for its specialized, large, and colorful bracts, which contrast with its tiny colorless flowers. As a plant whose bracts vary greatly in terms of coloration, the molecular mechanisms for Bougainvillea bract coloration and polychroism are largely unknown. The lack of genomic information for Bougainvillea largely hinders studies into the evolution and genetic basis of bract color variation. In this study, a pan-transcriptome of bracts obtained from 18 Bougainvillea glabra accessions was employed to investigate the global population-level germplasm kinship and the gene regulation network for bract color variation. Our results showed that the bracts of B. glabra accessions have largely differentiated International Commission on Illumination (CIE) L-a-b values. Moreover, germplasm kinship detected using principal component analysis, phylogeny, and admixture analysis showed three optimal subgroups, two of them distinctly clustered, which were not directly correlated with bract color variation at the population level. Differentially expressed genes (DEGs) between accessions of high vs. low L-a-b values revealed several considerable upregulated genes related to bract color L-a-b variation. A weighted gene co-expression network was constructed, and eight co-expressed regulation modules were identified that were highly correlated with variation in bract CIE L-a-b color values. Several candidate DEGs and co-expressed hub genes (e.g., GERD, SGR, ABCA3, GST, CYP76AD1, CYP76C, and JAZ) that were tightly associated with bract color variation were eventually determined responsible for L-a-b colorations, which might be the core regulation factors contributing to the B. glabra bract color variation. This study provides valuable insights into the research on germplasm kinship, population-level pan-transcriptome expression profiles, and the molecular basis of color variation of key innovative bracts in horticultural Bougainvillea.

Laser-Generated Guided Waves for Damage Detection in Metal-Lined Composite-Overwrapped Pressure Vessels.

This paper characterizes laser-generated guided waves in a metal-lined composite-overwrapped pressure vessel (COPV) to assess typical damage, including interfacial debonding and low-velocity impact damage. First, an eigenfrequency approach that avoids additional coding is utilized to theoretically analyze the dispersion characteristics of a COPV. The theoretical results show that interfacial debonding significantly alters dispersion curves, and the wavenumber of the L(0, 1) mode is sensitive to impact damage. Experimental verifications were conducted based on the full wavefield acquired using a scanning laser-ultrasonic system with a repetition rate of 1 kHz. By comparing the experimental dispersion curves with the theoretical ones, it was found that the metal-composite interface was not bonded. In addition, a local wavenumber estimation method was established to detect the impact damage by obtaining the spatial distribution of the wavenumber of the L(0, 1) mode.

Limited accumulation of high-frequency somatic mutations in a 1700-year-old Osmanthus fragrans tree.

Lifespan varies greatly between and within species. Mutation accumulation is considered an important factor explaining this life-history trait. However, direct assessment of somatic mutations in long-lived species is still rare. In this study, we sequenced a 1700-year-old sweet olive tree and analysed the high-frequency somatic mutations accumulated in its six primary branches. We found the lowest per-year mutation accumulation rate in this oldest tree among those studied via the whole-genome sequencing approach. Investigation of mutation profiles suggests that this low rate of high-frequency mutation was unlikely to result from strong purifying selection. More intriguingly, on a per-branching scale, the high-frequency mutation accumulation rate was similar among the long-lived individuals such as oak, wild peach and sweet olive investigated here. We therefore suggest the possibility that the accumulation of high-frequency somatic mutations in very long-lived trees might have an upper boundary due to both the possible limited number of stem cell divisions and the early segregation of the stem cell lineage.

Automated quality assessment of chest radiographs based on deep learning and linear regression cascade algorithms.

OBJECTIVES: Develop and evaluate the performance of deep learning and linear regression cascade algorithms for automated assessment of the image layout and position of chest radiographs. METHODS: This retrospective study used 10 quantitative indices to capture subjective perceptions of radiologists regarding image layout and position of chest radiographs, including the chest edges, field of view (FOV), clavicles, rotation, scapulae, and symmetry. An automated assessment system was developed using a training dataset consisting of 1025 adult posterior-anterior chest radiographs. The evaluation steps included: (i) use of a CNN framework based on ResNet - 34 to obtain measurement parameters for quantitative indices and (ii) analysis of quantitative indices using a multiple linear regression model to obtain predicted scores for the layout and position of chest radiograph. In the testing dataset (n = 100), the performance of the automated system was evaluated using the intraclass correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute difference (MAD), and mean absolute percentage error (MAPE). RESULTS: The stepwise regression showed a statistically significant relationship between the 10 quantitative indices and subjective scores (p < 0.05). The deep learning model showed high accuracy in predicting the quantitative indices (ICC = 0.82 to 0.99, r = 0.69 to 0.99, MAD = 0.01 to 2.75). The automatic system provided assessments similar to the mean opinion scores of radiologists regarding image layout (MAPE = 3.05%) and position (MAPE = 5.72%). CONCLUSIONS: Ten quantitative indices correlated well with the subjective perceptions of radiologists regarding the image layout and position of chest radiographs. The automated system provided high performance in measuring quantitative indices and assessing image quality. KEY POINTS: • Objective and reliable assessment for image quality of chest radiographs is important for improving image quality and diagnostic accuracy. • Deep learning can be used for automated measurements of quantitative indices from chest radiographs. • Linear regression can be used for interpretation-based quality assessment of chest radiographs.

CT-based radiomic nomogram for predicting the severity of patients with COVID-19.

BACKGROUND: The coronavirus disease 2019 (COVID-19) is a pandemic now, and the severity of COVID-19 determines the management, treatment, and even prognosis. We aim to develop and validate a radiomics nomogram for identifying patients with severe COVID-19. METHODS: There were 156 and 104 patients with COVID-19 enrolled in primary and validation cohorts, respectively. Radiomics features were extracted from chest CT images. Least absolute shrinkage and selection operator (LASSO) method was used for feature selection and radiomics signature building. Multivariable logistic regression analysis was used to develop a predictive model, and the radiomics signature, abnormal WBC counts, and comorbidity were incorporated and presented as a radiomics nomogram. The performance of the nomogram was assessed through its calibration, discrimination, and clinical usefulness. RESULTS: The radiomics signature consisting of four selected features was significantly associated with clinical condition of patients with COVID-19 in the primary and validation cohorts (P < 0.001). The radiomics nomogram including radiomics signature, comorbidity and abnormal WBC counts showed good discrimination of severe COVID-19, with an AUC of 0.972, and good calibration in the primary cohort. Application of the nomogram in the validation cohort still gave good discrimination with an AUC of 0.978 and good calibration. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful to identify the severe COVID-19. CONCLUSION: We present an easy-to-use radiomics nomogram to identify the patients with severe COVID-19 for better guiding a prompt management and treatment.

Artificial intelligence X-ray measurement technology of anatomical parameters related to lumbosacral stability.

PURPOSE: To develop a deep learning-based model for measuring automatic lumbosacral anatomical parameters from lateral lumbar radiographs and compare its performance to that of attending-level radiologists. METHODS: A total of 1791 lateral lumbar radiographs were collected through the PACS system and used to develop the deep learning-based model. Landmarks for the four used parameters, including the lumbosacral lordosis angle (LSLA), lumbosacral angle (LSA), sacral horizontal angle (SHA), and sacral inclination angle (SIA), were identified and automatically labeled by the model. At the same time, the measurement results were obtained through landmarks on the test set compared to manual measurements as the reference standard. Statistical analyses of the Percentage of Correct Key Points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient, mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman plots were performed to evaluate the performance of the model. RESULTS: The mean differences between the reference standard and the model for LSLA, LSA, SHA, and SIA, were 0.39°, 0.09°, 0.13°, and 0.12°, respectively. A strong correlation and consistency between the four parameters were found between the model and reference standard (ICC = 0.92-0.98, r = 0.92-0.97, MAE = 1.35-1.84, RMSE = 1.82-2.51), while with statistically significant difference for LSLA (p = 0.02). CONCLUSIONS: The presented model revealed clinically equivalent measurements in terms of accuracy, while superior measurements were obtained in terms of cost-effectiveness, reliability, and reproducibility. The model may help clinicians improve their understanding and evaluation of lumbar diseases and LBP from a quantitative perspective in practical work. (ChiCTR2100048250).

In vivo real-time assessment of the anastomotic blood supply in colorectal surgery using confocal laser endomicroscopy in an anastomotic model.

BACKGROUND AND STUDY AIMS: Anastomotic ischemia can affect healing and eventually lead to anastomotic leakage, and confocal laser endomicroscopy (CLE) can offer detailed observations at the subcellular level. We aimed to evaluate the anastomotic microcirculation in different anastomotic perfusion models using CLE. METHODS: Anastomotic perfusion models were established using twelve rabbits distributed into two groups: group A (good perfusion, n = 6) and group B (poor perfusion, n = 6). Afterward, intraoperative detection of anastomotic perfusion was carried out using CLE, and quantitative analysis of blood cells was performed. Rabbits that satisfied the criteria underwent a second exploratory operation and specimens were stained by hematoxylin and eosin. RESULTS: Enhanced with fluorescein sodium, capillaries were obviously highlighted in group A, while few capillaries were viewed in group B. Delayed development of fluorescence occurred in group B. The average flow of blood cells was 37.0 ± 5.93 per minute in group A and 6.33 ± 2.16 per minute in group B (p < 0.001). In addition, during the second exploratory surgery, rabbits with inadequate anastomotic perfusion exhibited more serious intestinal adhesion and ischemia. Anastomotic leakage and abdominal infection occurred in all rabbits in group B. CONCLUSION: CLE can realize real-time imaging of the anastomotic microcirculation and is a feasible technique for performing intraoperative evaluation in different anastomotic perfusion situations. This animal experiment provides the groundwork for future in vivo research in humans.