RESUMO
Boehmeria is a taxonomically challenging group within the nettle family (Urticaceae). The polyphyly of the genus has been proposed by previous studies with respect to five genera (Debregeasia, Cypholophus, Sarcochlamys, Archiboehmeria, and Astrothalamus). Extensive homoplasy of morphological characters has made generic delimitation problematic. Previous studies in other plant groups suggest that plastome structural variations have the potential to provide characters useful in reconstructing evolutionary relationships. We aimed to test this across Boehmeria and its allied genera by mapping plastome structural variations onto a resolved strongly supported phylogeny. In doing so, we expanded the sampling of the plastome to include Cypholophus, Sarcochlamys, Archiboehmeria, and Astrothalamus for the first time. The results of our phylogenomic analyses provide strong support for Sarcochlamys as being more closely related to Leucosyke puya than to Boehmeria and for the clustering of Boehmeria s.l. into four subclades. The sizes of the plastomes in Boehmeria s.l. ranged from 142,627 bp to 170,958 bp. The plastomes recovered a typical quadripartite structure comprising 127~146 genes. We observe several obvious structural variations across the taxa such as gene loss and multiple gene duplication, inverted repeat (IR) contraction and wide expansions, and inversions. Moreover, we recover a trend for these variations that the early clades were relatively conserved in evolution, whereas the later diverging clades were variable. We propose that the structural variations documented may be linked to the adaptation of Boehmeria s.l. to a wide range of habitats, from moist broadleaf forests in Asia to xeric shrublands and deserts in Africa. This study confirms that variation in plastome gene loss/duplication, IR contraction/expansion, and inversions can provide evidence useful for the reconstruction of evolutionary relationships.
RESUMO
OBJECTIVES: This study aimed to assess the predictive value of radiomics derived from intratumoral and peritumoral regions and to develop a radiomics nomogram to predict preoperative nuclear grade and overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC). METHODS: The study included 395 patients with ccRCC from our institution. The patients in Center A (anonymous) institution were randomly divided into a training cohort (n = 284) and an internal validation cohort (n = 71). An external validation cohort comprising 40 patients from Center B also was included. Computed tomography (CT) radiomics features were extracted from the internal area of the tumor (IAT) and IAT combined peritumoral areas of the tumor at 3 mm (PAT 3 mm) and 5 mm (PAT 5 mm). Independent predictors from both clinical and radiomics scores (Radscore) were used to construct a radiomics nomogram. Kaplan-Meier analysis with a log-rank test was performed to evaluate the correlation between factors and OS. RESULTS: The PAT 5-mm radiomics model (RM) exhibited exceptional predictive capability for grading, achieving an area under the curves of 0.80, 0.80, and 0.90 in the training, internal validation, and external validation cohorts. The nomogram and RM gained from the PAT 5-mm region were more clinically useful than the clinical model. The association between OS and predicted nuclear grade derived from the PAT 5-mm Radscore and the nomogram-predicted score was statistically significant (p < 0.05). CONCLUSION: The CT-based radiomics and nomograms showed valuable predictive capabilities for the World Health Organization/International Society of Urological Pathology grade and OS in patients with ccRCC. CRITICAL RELEVANCE STATEMENT: The intratumoral and peritumoral radiomics are feasible and promising to predict nuclear grade and overall survival in patients with clear cell renal cell carcinoma, which can contribute to the development of personalized preoperative treatment strategies. KEY POINTS: The multi-regional radiomics features are associated with clear cell renal cell carcinoma (ccRCC) grading and prognosis. The combination of intratumoral and peritumoral 5 mm regional features demonstrated superior predictive performance for grading. The nomogram and radiomics models have a broad range of clinical applications.
RESUMO
Introduction: Molecular subgroups influence the vascular architecture within medulloblastomas, particularly the wingless (WNT) subgroup, which contributes to its propensity for primary tumor hemorrhage. Whether this mechanism affects intraoperative blood loss remains unknown. This study aimed to assess the association between WNT medulloblastoma and the predisposition for blood loss. Methods: This was a retrospective observational study using data from a neuro-oncology center comprising molecular data on patients treated between December 31, 2014, and April 30, 2023. Differences between WNT and other subgroups in the risk of primary outcome-intraoperative blood loss were assessed using multivariable-adjusted linear regression. Results: Of the 148 patients included in the analysis, 18 patients (12.2%) had WNT, 42 (28.4%) had sonic hedgehog (SHH) TP53-wildtype, 7 (4.7%) had SHH TP53-mutant, and 81 (54.7%) were non-WNT/ non-SHH. The WNT subgroup more frequently underwent primary intratumoral hemorrhage (22% vs. 3.8%; p = 0.011). The median intraoperative blood loss was 400.00 (interquartile range [IQR] 250, 500) mL for WNT and 300.00 [200, 400] mL for the other subgroups (p = 0.136), with an adjusted ß of 135.264 (95% confidence intervals [CI], 11.701-258.827; p = 0.032). Similar results were observed in both midline and noninfiltrative margin medulloblastoma. Discussion: WNT medulloblastoma is typically associated with primary intratumoral hemorrhage and intraoperative blood loss. The validity of determining the surgical approach based on predicted molecular subtypes from imaging data is questionable. However, attempting to engage in risk communication with patients in a molecular-specific way is worthwhile to validate.
RESUMO
Polygalaqii, a new species, is described and illustrated from limestone landform in southern Hunan, China. The new species resembles P.fallax and P.arillata in flower structure of the plants, but readily differs from the latter two in having erect and shorter inflorescences (0.2-1cm VS 10-15cm VS 7-10cm), and fewer flowers (1-5 flowers VS 10-30 flowers VS 10-20 flowers), and the latter two have a later flowering period (late March to mid-April VS May to August VS May to October). And it is an extremely unique new species that will hibernate in the hot summer of July and August. Following the IUCN Red List Criteria, P.qii is assessed as 'Data Deficient (DD)'.
RESUMO
Introduction: One common and very upsetting side effect of burn injuries is scarring, which presents serious difficulties for patients and medical professionals alike. Aim: To assess a new therapeutic approach for treating scars following burn repair procedures in terms of its clinical efficacy. Material and methods: This method administers Hirudoid under ultrasound guidance in addition to fractional CO2 laser treatment. An extensive analysis of the effects of this combination treatment on functional results, patient satisfaction, and scar appearance is being conducted as part of this research. Fractional CO2 laser treatment is utilized for its capacity to stimulate collagen remodelling and decrease scar hypertrophy, while Hirudoid, a topical medicine containing heparinoid, is used to minimize inflammation and enhance tissue healing. Enrolling patients who have had burn repair surgery is the goal of a quasi-experimental study. Conventional scar care methods are performed on the control group, whereas the experimental group is treated with fractional CO2 laser therapy after applying Hirudoid under ultrasound guidance. Throughout the research period, clinical evaluations are carried out on a regular basis. These evaluations cover scar features, pain thresholds, and patient-reported results. Results: The first findings show that the experimental group significantly outperformed the control group in terms of overall look, pigmentation, and scar texture. Functional examinations point to possible improvements in terms of scar flexibility and the range of motion, while patient-reported outcomes show improved satisfaction with the combination therapy. In order to guarantee the combination therapy's viability and tolerance in a clinical context, its side effects and safety profiles are also extensively assessed. In order to improve scar management following burn healing, the study intends to provide important insights into the creation of more patient-friendly and successful therapies. Conclusions: A potential approach to enhancing the clinical results of burn scar treatment is the study of fractional CO2 laser therapy in conjunction with ultrasound-guided Hirudoid. Enhancing scar management tactics via the combination of sophisticated technology and therapy modalities may eventually improve the quality of life for burn injury victims.
RESUMO
Although silicon (Si) has a high theoretical capacity, the large volume expansion during lithiation has greatly hindered its application in high-energy-density lithium-ion batteries (LIBs). Among the strategies for improving the performance of Si anode, the role of binders should not be underestimated. Here, a novel strategy for designing a cross-linkable binder for Si anode has been proposed. The binder with hydroxyl and nitrile groups can be in situ covalently cross-linked through the amide group in the batteries. The cross-linked binder (c-POAH) shows high elasticity and strong adhesion to Si particles and the current collector. Si||Li half coin cells using the c-POAH binder have excellent cycle performance and the capacity retention ratio is 67.1% after 100 cycles at 0.2 C. Scanning electronic microscopy images show that the c-POAH binder can contribute to suppressing the pulverization of the Si anode. Moreover, the investigation with X-ray photoelectronic spectrum demonstrates that the decomposition of the liquid electrolyte on Si anode has been mitigated and the c-POAH binder can promote the formation of a more stable SEI film. Our strategy of endowing the binder with good elasticity through in situ cross-linking has opened up a new route for developing binders, which will definitely promote the application of Si anodes in high-energy-density LIBs.
RESUMO
Aims: Cellular dormancy is a state of quiescence subpopulation of tumor cells, characterized by low differentiation and lack of mitotic activity. They could evade chemotherapy and targeted therapy, leading to drug resistance and disease recurrence. Recent studies have shown a correlation between dormant cancer cells and unique extracellular matrix (ECM) composition, which is critical in regulating cell behavior. However, their interacting roles in TNBC patients remains to be characterized. Main methods: Dormant cancer cells in MDA-MB-231 cell line with highest PKH26 dye-retaining were FACS-sorted and gene expression was then analyzed. Dormant associated ECM (DA-ECM) signature was characterized by pathway analysis. Unsupervised hierarchical clustering was used to define distinct ECM features for TNBC patients. ECM-specific tumor biology was defined by integration of bulk RNA-seq with single-cell RNA-seq data, analysis of ligand-receptor interactions and enriched biological pathways, and in silico drug screening. We validated the sensitivity of dormant cancer cells to MAPK inhibitors by flow cytometry in vitro. Key findings: We observed that dormant TNBC cells preferentially expressed â¼10 % DA-ECM genes. The DA-ECM High subtype defined by unsupervised hierarchical clustering analysis was associated with immunosuppressive tumor microenvironment. Moreover, ligand-receptor interaction and pathway analysis revealed that the DA-ECM High subtype may likely help maintain tumor cell dormancy through MAPK, Hedgehog and Notch signaling pathways. Finally, in silico drug screening against the DA-ECM signature and in vitro assay showed dormant cancer cells were relatively sensitive to the MAPK pathway inhibitors, which may represent a potential therapeutic strategy for treating TNBC. Significance: Collectively, our research revealed that dormancy-associated ECM characterized tumor cells possess significant ECM remodeling capacity, and treatment strategies towards these cells could improve TNBC patient outcome.
RESUMO
PURPOSE: This study aimed to develop and validate a computed tomography-based nomogram assessing visceral and subcutaneous adiposity for predicting outcomes in localized clear cell renal cell carcinoma (ccRCC). METHODS: A cohort of 364 patients with pathologically confirmed ccRCC participated in this retrospective study, with 254 patients assigned to the training set and 110 to the validation set (a 7:3 distribution ratio). The adipose score (AS) was generated using the least absolute shrinkage and selection operator Cox regression. Subsequently, a nomogram was constructed by integrating the clinical independent predictor with the AS to predict disease-free survival (DFS) in localized ccRCC after surgery. The performance of the nomogram was compared with the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade, and Necrosis (SSIGN) score. RESULTS: In both the training and validation cohorts, the nomogram exhibited superior discrimination compared to SSIGN and UISS (C-index: 0.897 vs. 0.781 vs. 0.776 in the training cohort, and 0.752 vs. 0.596 vs. 0.686 in the validation cohort; 5 year AUC: 0.907 vs. 0.805 vs. 0.820 in the training cohort, and 0.832 vs. 0.577 vs. 0.726 in the validation cohort). Decision curve analysis (DCA) revealed a superior net benefit across a wider range of threshold probabilities for predicting 5 year DFS compared to UISS and SSIGN scores. CONCLUSIONS: The developed prognostic nomogram demonstrated high accuracy and overall superior performance compared to existing prognostic models.
RESUMO
This study examined the risk factors for short-term outcomes, focusing particularly on the associations among molecular subgroups. The analysis focused on the data of pediatric patients with medulloblastoma between 2013 and 2023, as well as operative complications, length of stay from surgery to adjuvant treatment, 30-day unplanned reoperation, unplanned readmission, and mortality. 148 patients were included. Patients with the SHH TP53-wildtype exhibited a lower incidence of complications (45.2% vs. 66.0%, odds ratio [OR] 0.358, 95% confidence interval [CI] 0.160 - 0.802). Female sex (0.437, 0.207 - 0.919) was identified as an independent protective factor for complications, and brainstem involvement (1.900, 1.297 - 2.784) was identified as a risk factor. Surgical time was associated with an increased risk of complications (1.004, 1.001 - 1.008), duration of hospitalization (1.006, 1.003 - 1.010), and reoperation (1.003, 1.001 - 1.006). Age was found to be a predictor of improved outcomes, as each additional year was associated with a 14.1% decrease in the likelihood of experiencing a prolonged length of stay (0.859, 0.772 - 0.956). Patients without metastasis exhibited a reduced risk of reoperation (0.322, 0.133 - 0.784) and readmission (0.208, 0.074 - 0.581). There is a significant degree of variability in the occurrence of operative complications in pediatric patients with medulloblastoma. SHH TP53-wildtype medulloblastoma is commonly correlated with a decreased incidence of complications. The short-term outcomes of patients are influenced by various unmodifiable endogenous factors. These findings could enhance the knowledge of onconeurosurgeons and alleviate the challenges associated with patient/parent education through personalized risk communication. However, the importance of a dedicated center with expertise surgical team and experienced neurosurgeon in improving neurosurgical outcomes appears self-evident.
Assuntos
Neoplasias Cerebelares , Meduloblastoma , Procedimentos Neurocirúrgicos , Complicações Pós-Operatórias , Humanos , Meduloblastoma/cirurgia , Feminino , Masculino , Criança , Neoplasias Cerebelares/cirurgia , Procedimentos Neurocirúrgicos/métodos , Pré-Escolar , Complicações Pós-Operatórias/epidemiologia , Resultado do Tratamento , Adolescente , Estudos de Coortes , Tempo de Internação , Reoperação , Proteínas Hedgehog/genética , Fatores de Risco , Proteína Supressora de Tumor p53/genéticaRESUMO
Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.
Assuntos
Meios de Contraste , Aprendizado Profundo , Neoplasias Renais , Tomografia Computadorizada por Raios X , Humanos , Feminino , Masculino , Pessoa de Meia-Idade , Neoplasias Renais/diagnóstico por imagem , Neoplasias Renais/patologia , Estudos Retrospectivos , Tomografia Computadorizada por Raios X/métodos , Estudos Prospectivos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Idoso , Algoritmos , Rim/diagnóstico por imagem , AdultoRESUMO
BACKGROUND: Evidence of the association between obesity and renal cell carcinoma progression is contradictory. The effects of renal cell carcinoma on fat distribution are still unknown. OBJECTIVE: The goal of this study was to determine the ability of various forms of fat deposition to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma [ccRCC]. METHODS: This retrospective study included 320 patients with pathologically proven ccRCC [215 men and 105 women; 263 low-grade ccRCC and 57 highgrade ccRCC]. Based on computed tomography scans, adipose tissue in various body regions was classified into the perirenal fat area [PFA], visceral fat area [VFA], total fat area [TFA], subcutaneous fat area [SFA], and hepatic steatosis [HS]. Subsequently, the relative VFA [rVFA] was computed. Age, sex, body mass index, and maximal tumor diameter were also regarded as clinical factors. Univariate and multivariate logistic regression studies were conducted to evaluate whether there was an association between body fat composition and the Fuhrman classification and whether it was related to gender. RESULTS: After correcting for age, males with low-grade ccRCC exhibited higher TFA [257.6 vs. 203.0, p = 0.002], VFA [151.6 vs.115.5, p = 0.007], SFA [106.0 vs. 87.5, p = 0.015], PFA [55.1 vs. 30.4, p < 0.001], and HS [18% vs. 0%, p = 0.031] than those with high-grade ccRCC. There was no significant difference among rVFA in males. In females, there was no significant difference in any of the parameters. VFA and PFA remained independent predictors for high-grade ccRCC in males in both the monovariate [VFA: odds ratio [OR] 0.992, 95% confidence interval [CI] 0.987-0.997, p = 0.004; PFA: OR 0.949, 95% CI 0.930-0.970, p < 0.001] and multivariate [VFA: OR 1.028, 95% CI 1.001-1.074, p < 0.001; PFA: OR 0.878, 95% CI 0.833-0.926, p < 0.001] models. CONCLUSION: Gender-specific adipose tissue in different locations demonstrated varied values for predicting high-grade ccRCC and may be utilized as an independent predictor of high-grade ccRCC in male patients.
RESUMO
Lithium (Li) metal is regarded as the most desirable anode candidates for high-energy-density batteries by virtue of its lowest redox potential and ultrahigh theoretical specific capacity. However, uncontrollable Li dendritic growth, infinite volume variation and unstable solid electrolyte interface (SEI) ineluctably plague its commercialization process. Herein, the three-dimensional (3D) nanofiber functional layers with synergistic soft-rigid feature, consisting of tin oxide (SnO2)-anchored polyvinylidene fluoride (PVDF) nanofibers, are directly electrospun on copper current collector. This strategy can effectively regulate uniform Li deposition and strengthen SEI stability through the dual effect of physical accommodation and chemical ionic intervention. On the one hand, the nanofiber interlayers with excellent electrolyte affinity and well-distributed Li+ transport pathways can promote uniform Li+ flux distribution and large-size Li deposition. On the other hand, the rigid SnO2 contributes to reducing Li nucleation overpotential and stabilizing SEI layer assisted by its spontaneous reaction with Li. As a result, the smooth and dense Li deposition is achieved by such soft-rigid nanofiber interlayers, thereby extending the cycling life and improving the safety application of Li metal batteries. This work offers a new route for efficient protection of Li metal anodes and brings a new inspiration for developing high-energy-density Li metal batteries.
RESUMO
In this study, the performance of a zero-gap flow-through reactor with three-dimensional (3D) porous Ti/RuO2-TiO2@Pt anodes was systematically investigated for the electrocatalytic oxidation of phenolic wastewater, considering phenol and 4-nitrophenol (4-NP) as the target pollutants. The optimum parameters for the electrochemical oxidation of phenol and 4-NP were examined. For phenol degradation, at an initial concentration of 50 mg/L, initial pH of 7, NaCl concentration of 10.0 g/L, current density of 10 mA/cm2, and retention time of 30 min, the degradation efficiency achieved was 95.05%, with an energy consumption of 15.39 kWh/kg; meanwhile, for 4-NP, the degradation efficiency was 98.42% and energy consumption was 19.21 kWh/kg (at an initial concentration of 40 mg/L, initial pH of 3, NaCl concentration of 10.0 g/L, current density of 10 mA/cm2, and retention time of 30 min). The electrocatalytic oxidation of phenol and 4-NP conformed to the pseudo-first-order kinetics model, and the k values were 0.2562 min-1 and 0.1736 min-1, respectively, which are 1.7 and 3.6-times higher than those of a conventional electrolyzer. Liquid chromatography-mass spectrometry (LC-MS) was used to verify the intermediates formed during the degradation of phenol or 4-NP and a possible degradation pathway was provided. The extremely narrow electrode distance and the flow-through configuration of the zero-gap flow-through reactor were thought to be essential for its lower energy consumption and higher mass transfer efficiency. The zero-gap flow-through reactor with a novel 3D porous Ti/RuO2-TiO2@Pt electrode is a superior alternative for the treatment of industrial wastewater.
RESUMO
OBJECTIVE: To investigate the clinical and magnetic resonance imaging (MRI) features for preoperatively discriminating primary ovarian mucinous malignant tumors (POMTs) and metastatic mucinous carcinomas involving the ovary (MOMCs). METHODS: This retrospective multicenter study enrolled 61 patients with 22 POMTs and 49 MOMCs, which were pathologically proved between November 2014 to Jane 2023. The clinical and MRI features were evaluated and compared between POMTs and MOMCs. Univariate and multivariate analyses were performed to identify the significant variables between the two groups, which were then incorporated into a predictive nomogram, and ROC curve analysis was subsequently carried out to evaluate diagnostic performance. RESULTS: 35.9% patients with MOMCs were discovered synchronously with the primary carcinomas; 25.6% patients with MOMCs were bilateral, and all of the patients with POMTs were unilateral. The biomarker CEA was significantly different between the two groups (p = 0.002). There were significant differences in the following MRI features: tumor size, configuration, enhanced pattern, the number of cysts, honeycomb sign, stained-glass appearance, ascites, size diversity ratio, signal diversity ratio. The locular size diversity ratio (p = 0.005, OR = 1.31), and signal intensity diversity ratio (p = 0.10, OR = 4.01) were independent predictors for MOMCs. The combination of above independent criteria yielded the largest area under curve of 0.922 with a sensitivity of 82.3% and specificity of 88.9%. CONCLUSIONS: Patients with MOMCs were more commonly bilaterally and having higher levels of CEA, but did not always had a malignant tumor history. For ovarian mucin-producing tumors, the uniform locular sizes and signal intensities were more predict MOMCs.
Assuntos
Adenocarcinoma Mucinoso , Neoplasias Ovarianas , Feminino , Humanos , Neoplasias Ovarianas/diagnóstico por imagem , Neoplasias Ovarianas/cirurgia , Carcinoma Epitelial do Ovário/diagnóstico , Adenocarcinoma Mucinoso/diagnóstico por imagem , Adenocarcinoma Mucinoso/cirurgia , Mucinas , Diagnóstico DiferencialRESUMO
Background: Esophageal cancer is the seventh most frequently diagnosed cancer with a high mortality rate and the sixth leading cause of cancer deaths in the world. Early detection of esophageal cancer is very vital for the patients. Traditionally, contrast computed tomography (CT) was used to detect esophageal carcinomas, but with the development of deep learning (DL) technology, it may now be possible for non-contrast CT to detect esophageal carcinomas. In this study, we aimed to establish a DL-based diagnostic system to stage esophageal cancer from non-contrast chest CT images. Methods: In this retrospective dual-center study, we included 397 primary esophageal cancer patients with pathologically confirmed non-contrast chest CT images, as well as 250 healthy individuals without esophageal tumors, confirmed through endoscopic examination. The images of these participants were treated as the training data. Additionally, images from 100 esophageal cancer patients and 100 healthy individuals were enrolled for model validation. The esophagus segmentation was performed using the no-new-Net (nnU-Net) model; based on the segmentation result and feature extraction, a decision tree was employed to classify whether cancer is present or not. We compared the diagnostic efficacy of the DL-based method with the performance of radiologists with various levels of experience. Meanwhile, a diagnostic performance comparison of radiologists with and without the aid of the DL-based method was also conducted. Results: In this study, the DL-based method demonstrated a high level of diagnostic efficacy in the detection of esophageal cancer, with a performance of AUC of 0.890, sensitivity of 0.900, specificity of 0.880, accuracy of 0.882, and F-score of 0.891. Furthermore, the incorporation of the DL-based method resulted in a significant improvement of the AUC values w.r.t. of three radiologists from 0.855/0.820/0.930 to 0.910/0.955/0.965 (p = 0.0004/<0.0001/0.0068, with DeLong's test). Conclusion: The DL-based method shows a satisfactory performance of sensitivity and specificity for detecting esophageal cancers from non-contrast chest CT images. With the aid of the DL-based method, radiologists can attain better diagnostic workup for esophageal cancer and minimize the chance of missing esophageal cancers in reading the CT scans acquired for health check-up purposes.
RESUMO
OBJECTIVE: This study aimed to describe the characteristics of computed tomography (CT) and magnetic resonance imaging (MRI) of clear cell papillary renal cell carcinoma (CCPRCC). METHODS: This retrospective study comprised 27 patients diagnosed with 29 tumors of CCPRCC. The study was approved by the Medical Ethics Committee and the requirement for the informed consent was waived. The inclusion criteria stipulated pathology-confirmed CCPRCCs with at least one preoperative imaging examination, including CT or MRI. Two experienced radiologists independently analyzed the imaging characteristics, including size, location, growth mode, morphology, texture, density, and enhancement pattern. Paired t-test was used to compare differences in CT Hounsfield unit values and apparent diffusion coefficient (ADC) imaging between the tumor and the renal cortex. RESULTS: The mean age of the 27 patients was 57.0 ± 14.2 years. Nineteen patients underwent CT, while 12 underwent MRI (There are 4 patients underwent not only CT but also MRI). Among the cases, 26 (96%) were single, and 1 (4%) was multiple, consisting of three lesions. Out of the 29 tumors, 15 (52%) were located in the left kidney and 14 (48%) in the right kidney. The mean tumor diameter was 3.3 ± 1.7 cm. Furthermore, 19 (66%), 3 (10%), and 7 (24%) tumors were solid, cystic, mixed solid, and cystic type, respectively. The growth mode was endogenous and exogenous in 8 (28%) and 21 (72%) tumors, respectively. The tumor shape was irregular and round in 5 (17%) and 24 (83%) tumors, respectively. The CT value of the tumor was approximately 33.2 ± 9.8 HU, which was not significantly different from that of the renal cortex(31.1 ± 6.3HU)(p = 0.343). Furthermore, 7 (24%), 12 (41%), and 3 (10%) had calcification, cystic degeneration, and hemorrhage, respectively. In 12 tumors, hypointense and hyperintense were predominant on T1 and T2-weighted images, respectively. The tumor capsule was found at the edge of 12 tumors. The average ADC value of the tumor (1.54 ± 0.74 × 10-3 mm2/s) and that of the renal cortex(1.68 ± 0.63×10-3mm2 /s) was not statistically significantly different (p = 0.260). The enhancement scanning revealed "wash-in and wash-out" enhancement in 19 (68%) tumors, continuous or progressive enhancement in 6 (21%) tumors, and enhanced cystic wall and central separation in 3 (11%) tumors. CONCLUSION: CCPRCC occurs more likely in middle-aged and elderly individuals, and the tumor is prone to cystic degeneration, with rare bleeding and calcification, and no obvious limitation on MRI diffusion-weighted imaging, which enhancement form performs as mainly "wash-in and washout," but the final diagnosis depends on histopathology.
Assuntos
Carcinoma de Células Renais , Neoplasias Renais , Pessoa de Meia-Idade , Idoso , Humanos , Adulto , Carcinoma de Células Renais/diagnóstico por imagem , Carcinoma de Células Renais/patologia , Neoplasias Renais/diagnóstico por imagem , Neoplasias Renais/patologia , Estudos Retrospectivos , Imageamento por Ressonância Magnética/métodos , Imagem de Difusão por Ressonância Magnética/métodosRESUMO
Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts extensive research interests. Recent deep learning has shown its great potential in improving image quality and reconstruction speed. Faithful coil sensitivity estimation is vital for MRI reconstruction. However, most deep learning methods still rely on pre-estimated sensitivity maps and ignore their inaccuracy, resulting in the significant quality degradation of reconstructed images. In this work, we propose a Joint Deep Sensitivity estimation and Image reconstruction network, called JDSI. During the image artifacts removal, it gradually provides more faithful sensitivity maps with high-frequency information, leading to improved image reconstructions. To understand the behavior of the network, the mutual promotion of sensitivity estimation and image reconstruction is revealed through the visualization of network intermediate results. Results on in vivo datasets and radiologist reader study demonstrate that, for both calibration-based and calibrationless reconstruction, the proposed JDSI achieves the state-of-the-art performance visually and quantitatively, especially when the acceleration factor is high. Additionally, JDSI owns nice robustness to patients and autocalibration signals.
RESUMO
Delaying the deterioration of bakery goods is necessary in the food industry. The objective of this study was to determine the effects of wheat oligopeptide (WOP) on the qualities of bread rolls. The effects of WOP on the baking properties, moisture content, and starch crystallization of rolls during the storage process were investigated in this study. The results showed that WOP effectively improved the degree of gluten cross-linking, thereby improving the specific volume and the internal structure of rolls. The FTIR and XRD results showed that the addition of WOP hindered the formation of the starch double helix structure and decreased its relative crystallinity. The DSC results revealed a decrease in the enthalpy change (ΔH) from 0.812 to 0.608 J/g after 7 days of storage with 1.0% WOP addition, further indicating that WOP reduced the availability of water for crystal lattice formation and hindered the rearrangement of starch molecules. The addition of WOP also improved the microstructure of the rolls that were observed using SEM analysis. In summary, WOP is expected to be an effective natural additive to inhibit starch staling and provide new insights into starchy food products.
RESUMO
This study proposes a recognition model for different drying methods of grain using hyperspectral imaging technology (HSI) and multivariate analysis. Fresh harvested grain samples were dried using three different methods: rotating ventilation drying, mechanical drying, and natural drying. Hyperspectral images of the samples were collected within the 388-1065 nm band range. The spectral features of the samples were extracted using principal component analysis (PCA), while the texture features were extracted using second-order probability statistical filtering. Partial least squares regression (PLSR) drying models with different characteristics were established. At the same time, a BPNN (Back-propagation neural network, BPNN) based on spectral texture fusion features was established to compare the recognition effects of different models. Texture analysis indicated that the mean-image had the clearest contour, and the texture characteristics of mechanical drying were smaller than those of rotating ventilation drying and natural drying. The BPNN model established using spectral-texture feature variables showed the best performance in distinguishing grain in different drying modes, with a prediction model obtained based on the correlation coefficients of special variables. The spectral and texture feature values were fused for pseudo-color visualization expression, and the three drying methods of grain showed different colors. This study provides a reference for non-destructive and rapid detection of grain with different drying methods.
RESUMO
OBJECTIVE: This study was aimed at exploring the osteoporotic vertebral fracture rate and the related causal factors in prostate cancer patients before and after treatment. METHODS: One hundred prostate cancer patients were recruited in this study. One hundred men without prostate cancer history were selected as the control group. The study was approved by the Medical Ethics Committee under Ethics number B2021-373R and the requirement for the informed consent was waived. The T4-L1 vertebral body of the case group and the control group before and after treatment was evaluated according to Genant's semi-quantitative method. The difference in vertebral body fracture rate between the case group and the control group and the changes in vertebral body fracture rate before and after treatment among the case group were compared. They were grouped according to age, body mass index (BMI), prostate-specific antigen (PSA) levels, Gleason grade, and androgen deprivation therapy (ADT). Univariate and multivariate logistic regression models were used to determine the factors significantly associated with vertebral fracture rate in prostate cancer patients. RESULTS: The prevalence of vertebral fracture was 16% and 31% in prostate cancer patients before and after treatment, respectively, and 29% in the control group. The vertebral fracture rate of the patients before treatment significantly differed that of the control group and the patients after treatment. Univariate analysis showed that age, PSA levels, and treatment parameters were the significant influencing factors of vertebral fracture rates. Multivariate logistic regression analysis showed that age was the main influencing factor of vertebral fracture rates. CONCLUSION: Osteoporotic vertebral fractures in patients with prostate cancer was associated with many factors. And the incidence of vertebral fracture in prostate cancer patients after ADT was significantly higher than that before treatment.