Search

Purpose: Development and validation of a radiomics model for predicting occult locally advanced esophageal squamous cell carcinoma (LA-ESCC) on computed tomography (CT) radiomic features before implementation of treatment. Methods: The study retrospectively collected 574 patients with esophageal squamous cell carcinoma (ESCC) from two medical centers, which were divided into three cohorts for training, internal and external validation. After delineating volume of interest (VOI), radiomics features were extracted and subjected to feature selection using three robust methods. Subsequently, 10 machine learning models were constructed, among which the optimal model was utilized to establish a radiomics signature. Furthermore, a predictive nomogram incorporating both clinical and radiomics signatures was developed. The performance of these models was evaluated through receiver operating characteristic curves, calibration curves, decision curve analysis as well as measures including accuracy, sensitivity, and specificity. Results: A total of 19 radiomics features were selected. The multilayer perceptron (MLP), which was found to be optimal, achieved an AUC of 0.919, 0.864 and 0.882 in the training, internal and external validation cohorts, respectively. Similarly, MLP showed good accuracy in distinguish occult LA-ESCC in subgroup of cT1–2N0M0 diagnosed by clinicians with 0.803 and 0.789 in two validation cohorts respectively. By incorporating the radiomics signature with clinical signature, a predictive nomogram demonstrated superior prediction performance with an AUC of 0.877 and accuracy of 0.85 in external validation cohort. Conclusion: The radiomics and machine learning model can offers improved accuracy in prediction of occult LA-ESCC, providing valuable assistance to clinicians when choosing treatment plans.

Jasmonic acid is a crucial phytohormone that plays a pivotal role, serving as a regulator to balancing plant development and resistance. However, there are analogous and distinctive characteristics exhibited in JA biosynthesis, perception, and signal transduction pathways in both herbaceous and woody plants. Moreover, the majority of research subjects have predominantly focused on the function of JA in model or herbaceous plants. Consequently, there is a significant paucity of studies investigating JA regulation networks in woody plants, particularly concerning post-transcriptional regulatory events such as alternative splicing (AS). This review article aims to conduct a comprehensive summary of advancements that JA signals regulate plant development across various woody species, comparing the analogous features and regulatory differences to herbaceous counterparts. In addition, we summarized the involvement of AS events including splicing factor (SF) and transcripts in the JA regulatory network, highlighting the effectiveness of high-throughput proteogenomic methods. A better understanding of the JA signaling pathway in woody plants has pivotal implications for forestry production, including optimizing plant management and enhancing secondary metabolite production.

BackgroundEvidence indicates that the addition of ezetimibe to statin therapy reduces cardiovascular events. However, the impact of ezetimibe–statin combination therapy on coronary plaque regression, plaque stabilization, and diameter stenosis remains a matter of controversy.MethodsWe performed electronic searches in PubMed, Web of Knowledge, and the Cochrane Central Register of Controlled Trials to identify eligible trials assessing the effects of ezetimibe–statin combination therapy versus statin monotherapy reporting at least one outcome among total atheroma volume (TAV), minimum fibrous cap thickness (FCT), lumen volume (LV), and lumen area (LA) derived from intravascular imaging modalities of intravascular ultrasound (IVUS) and optical coherence tomography (OCT). We used the random-effects model and performed trial sequential analysis (TSA) during this meta-analysis.ResultsEleven articles with a total of 926 individuals (460 in the dual-lipid-lowering therapy group and 466 in the statin monotherapy group) were included in the final meta-analysis. Compared to statin monotherapy, ezetimibe–statin combination therapy was associated with significantly decreased TAV [WMD = −3.17, 95% CI (−5.42 to −0.92), and p = 0.006], with no effect on the LV of the coronary artery [WMD = −0.52, 95% CI (−2.24 to 1.21), and p = 0.56], the LA of the coronary artery [WMD = 0.16, 95% CI (−0.10–0.42), and p = 0.22], or minimum FCT thickness [WMD = 19.11, 95%CI (−12.76–50.97)].ConclusionIn patients with coronary artery disease, ezetimibe–statin combination therapy resulted in a significant regression in TAV compared to statin monotherapy, whereas no overall improvements of minimum FCT or lumenal stenosis were observed.

The impact of mitochondrial dysfunction on the pathogenesis of cardiovascular disease is increasing. However, the precise underlying mechanism remains unclear. Mitochondria produce cellular energy through oxidative phosphorylation while regulating calcium homeostasis, cellular respiration, and the production of biosynthetic chemicals. Nevertheless, problems related to cardiac energy metabolism, defective mitochondrial proteins, mitophagy, and structural changes in mitochondrial membranes can cause cardiovascular diseases via mitochondrial dysfunction. Mitofilin is a critical inner mitochondrial membrane protein that maintains cristae structure and facilitates protein transport while linking the inner mitochondrial membrane, outer mitochondrial membrane, and mitochondrial DNA transcription. Researchers believe that mitofilin may be a therapeutic target for treating cardiovascular diseases, particularly cardiac mitochondrial dysfunctions. In this review, we highlight current findings regarding the role of mitofilin in the pathogenesis of cardiovascular diseases and potential therapeutic compounds targeting mitofilin.

Objective: Acute aortic dissection (AAD) with a high mortality and postoperative complications remains presently no effective indicators to conjunctly predict the short-term mortality and the prognosis. This study aimed to investigate the predictive role of α-HBDH on in-hospital mortality and postoperative Major adverse cardiovascular events (MACE) in patients with AAD. Methods: In this retrospective study, a total of 369 enrolled patients from 2015 to 2021 were divided into three groups (T1: low, T2: medium and T3: high) based on the tertiles of α-HBDH levels on admission. In terms of the preoperative, intraoperative and postoperative indicators among 3 groups, the relationship between α-HBDH and studying endpoints was determined by logistic regression models, along with the consolidation using Kaplan–Meier and restricted cubic spline (RCS) analysis for predicting the in-hospital death and MACE complications. Last, subgroup analysis further verified the predictive value of α-HBDH. Results: Logistic regression analysis showed that α-HBDH was independently associated with in-hospital mortality of patients with AAD [OR(95CI): 4.771(1.043–21.832), P = 0.044] and MACE [OR(95CI): 9.869(2.148–45.349), P = 0.003]. Moreover, Kaplan-Meier analysis also showed an increased α-HBDH levels associated with poor survival within 30 days (log rank test, P 0.05). Conclusions: α-HBDH is a predictor of the in-hospital mortality and postoperative MACE, guiding admission stratification of patients with AAD.

Abstract Communication with hand gestures plays a significant role in human‐computer interaction by providing an intuitive and natural way for humans to communicate with machines. Ultrasound‐based devices have shown promising results in contactless hand gesture recognition without requiring physical contact. However, it is challenging to fabricate a densely packed wearable ultrasound array. Here, a stretchable ultrasound array is demonstrated with closely packed transducer elements fabricated using surface charge engineering between pre‐charged 1–3 Lead Zirconate Titanate (PZT) composite and thin polyimide film without using a microscope. The array exhibits excellent ultrasound properties with a wide bandwidth (≈57.1%) and high electromechanical coefficient (≈0.75). The ultrasound array can decipher gestures up to 10 cm in distance by using a contactless triboelectric module and identify materials from the time constant of the exponentially decaying impedance based on their triboelectric properties by utilizing the electrostatic induction phase. The newly proposed metric of the areal‐time constant is material‐specific and decreases monotonically from a highly positive human body (1.13 m2 s) to negatively charged polydimethylsiloxane (PDMS) (0.02 m2 s) in the triboelectric series. The capability of the closely packed ultrasound array to detect material along with hand gesture interpretation provides an additional dimension in the next‐generation human‐robot interaction.

Objective: The study established a nomogram based on quantitative parameters of spectral computed tomography (CT) and clinical characteristics, aiming to evaluate its predictive value for preoperative lymphovascular invasion (LVI) in gastric cancer (GC). Methods: From December 2019 to December 2021, 171 patients with pathologically confirmed GC were retrospectively collected with corresponding clinical data and spectral CT quantitative data. Patients were divided into LVI-positive and LVI-negative groups based on their pathological results. The univariate and multivariate logistic regression analyses were used to identify the risk factors and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were adopted to evaluate the predictive accuracy of nomogram. Results: Four clinical characteristics or spectral CT quantitative parameters, including Borrmann classification (P = 0.039), CA724 (P = 0.007), tumor thickness (P = 0.031), and iodine concentration in the venous phase (VIC) (P = 0.004) were identified as independent factors for LVI in GC patients. The nomogram was established based on the four factors, which had a potent predictive accuracy in the training, internal validation and external validation cohorts, with the area under the ROC curve (AUC) of 0.864 (95% CI, 0.798–0.930), 0.964 (95% CI, 0.903–1.000) and 0.877 (95% CI, 0.759–0.996), respectively. Conclusion: This study constructed a comprehensive nomogram consisting spectral CT quantitative parameters and clinical characteristics of GC, which exhibited a robust efficiency in predicting LVI in GC patients.

Abstract Studies considering the relationship between non-obesity-related body composition and lung function are few; therefore, this study aimed to explore these correlations and effects. This cross-sectional study conducted in rural Qingtongxia City and Pingluo County, Ningxia, China, included 776 participants aged 30–75 years. Body composition and lung function were measured using direct segmental multifrequency bioelectrical impedance analysis and a digital spirometer, respectively. Their correlation was assessed using partial correlation analysis, controlling for age and smoking status, and the body composition effect on lung function was analyzed using binomial logistic regression analysis. The body components total body water content, protein content, mineral content, muscle mass, fat-free mass (FFM), skeletal muscle mass, basal metabolic volume, and chest circumference (CC) positively correlated with pulmonary function (forced vital capacity and forced expiratory volume in one second) in both sexes. Neck circumference and hip circumference positively correlated with pulmonary function in women. Additionally, lung function declines more slowly in women (odds ratio [OR] = 0.66, 95% confidence interval [CI] = 0.44–0.98, p = 0.04); CC (OR = 0.92, 95% CI = 0.86–0.98, p = 0.01) increased as a protective factor for decreased lung function. Increased waist circumference (OR = 1.04, 95% CI = 1.00–1.09, p = 0.04) was a risk factor for reduced lung function. FFM contains body composition indicators positively correlating with lung function, excluding fat-related body composition. Abdominal obesity increases the risk of decreased lung function.

Delayed sowing mitigates lodging in wheat. However, the mechanism underlying the enhanced lodging resistance in wheat has yet to be fully elucidated. Field experiments were conducted to investigate the effects of sowing date on lignin and cellulose metabolism, stem morphological characteristics, lodging resistance, and grain yield. Seeds of Tainong 18, a winter wheat variety, were sown on October 8 (normal sowing) and October 22 (late sowing) during both of the 2015–2016 and 2016–2017 growing seasons. The results showed that late sowing enhanced the lodging resistance of wheat by improving the biosynthesis and accumulation of lignin and cellulose. Under late sowing, the expression levels of key genes (TaPAL, TaCCR, TaCOMT, TaCAD, and TaCesA1, 3, 4, 7, and 8) and enzyme activities (TaPAL and TaCAD) related to lignin and cellulose biosynthesis peaked 4–12 days earlier, and except for the TaPAL, TaCCR, and TaCesA1 genes and TaPAL, in most cases they were significantly higher than under normal sowing. As a result, lignin and cellulose accumulated quickly during the stem elongation stage. The mean and maximum accumulation rates of lignin and cellulose increased, the maximum accumulation contents of lignin and cellulose were higher, and the cellulose accumulation duration was prolonged. Consequently, the lignin/cellulose ratio and lignin content were increased from 0 day and the cellulose content was increased from 11 days after jointing onward. Our main finding is that the improved biosynthesis and accumulation of lignin and cellulose were responsible for increasing the stem-filling degree, breaking strength, and lodging resistance. The major functional genes enhancing lodging resistance in wheat that are induced by delayed sowing need to be determined.

Phase aberration caused by the skull is a major barrier to achieving high quality photoacoustic images of human and non-human primates’ brains. To address this issue, time-reversal methods have been used but they are computationally demanding and slow due to relying on solving the full-wave equation. The proposed approach is based on model-based image reconstruction in the frequency-domain to achieve near real-time image reconstruction. The relationship between an imaging region and transducer array elements can be mathematically described as a model matrix and the image reconstruction can be performed by pseudo-inverse of the model matrix. The model matrix is numerically calculated due to the lack of analytical solutions for transcranial ultrasound. However, this calculation only needs to be performed once for a given experimental setup and the same acoustic medium, and is an offline process not affecting the actual image reconstruction time. This non-iterative mode-based method demonstrates a substantial improvement in image reconstruction time, being approximately 18 times faster than the time-reversal method, all while maintaining comparable image quality.