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Background: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is important for personalized clinical decision‐making. Radiologists' assessment based on clinical characteristics showed poor performance for detecting AP presence. Purpose: To develop deep learning models for detecting AP presence, and to compare the performance of these models with those of a clinical model (CM) and radiologists' interpretation (RI). Study Type: Retrospective. Population: Totally, 616 men from six institutions who underwent radical prostatectomy, were divided into a training cohort (508 patients from five institutions) and an external validation cohort (108 patients from one institution). Field Strength/Sequences: T2‐weighted imaging with a turbo spin echo sequence and diffusion‐weighted imaging with a single‐shot echo plane‐imaging sequence at 3.0 T. Assessment: The reference standard for AP was histopathological extracapsular extension, seminal vesicle invasion, or positive surgical margins. A deep learning model based on the Swin‐Transformer network (TransNet) was developed for detecting AP. An integrated model was also developed, which combined TransNet signature with clinical characteristics (TransCL). The clinical characteristics included biopsy Gleason grade group, Prostate Imaging Reporting and Data System scores, prostate‐specific antigen, ADC value, and the lesion maximum cross‐sectional diameter. Statistical Tests: Model and radiologists' performance were assessed using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The Delong test was used to evaluate difference in AUC. P < 0.05 was considered significant. Results: The AUC of TransCL for detecting AP presence was 0.813 (95% CI, 0.726–0.882), which was higher than that of TransNet (0.791 [95% CI, 0.702–0.863], P = 0.429), and significantly higher than those of CM (0.749 [95% CI, 0.656–0.827]) and RI (0.664 [95% CI, 0.566–0.752]). Data Conclusion: TransNet and TransCL have potential to aid in detecting the presence of AP and some single adverse pathologic features. Level of Evidence: 4 Technical Efficacy: Stage 4 [ABSTRACT FROM AUTHOR]

Yin chai hu (Radix Stellariae) is a root medicine that is frequently used in Chinese traditional medicine to treat fever and malnutrition. In modern medicine, it has been discovered to have anti‐inflammatory, anti‐allergic, and anticancer properties. In a previous study, we were able to extract lipids from Stellariae Radix using supercritical CO2 extraction (SRE), and these sterol lipids accounted for up to 88.29% of the extract. However, the impact of SRE on the development of atopic dermatitis (AD) has not yet been investigated. This study investigates the inhibitory effects of SRE on AD development using a 2,4‐dinitrochlorobenzene (DNCB)‐induced AD mouse model. Treatment with SRE significantly reduced the dermatitis score and histopathological changes compared with the DNCB group. The study found that treatment with SRE resulted in a decrease of pro‐inflammatory cytokines TNF‐α, CXC‐10, IL‐12, and IL‐1β in skin lesions. Additionally, immunohistochemical analysis revealed that SRE effectively suppressed M1 macrophage infiltration into the AD lesion. Furthermore, the anti‐inflammatory effect of SRE was evaluated in LPS + INF‐γ induced bone marrow‐derived macrophages (BMDMs) M1 polarization, SRE inhibited the production of TNF‐α, CXC‐10, IL‐12, and IL‐1β and decreased the expression of NLRP3. Additionally, SRE was found to increase p‐AMPKT172, but had no effect on total AMPK expression, after administration of the AMPK inhibitor Compound C, the inhibitory effect of SRE on M1 macrophages was partially reversed. The results indicate that SRE has an inhibitory effect on AD, making it a potential therapeutic agent for this atopic disorder. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) transition metal nitrides and carbides (MXenes), represented by Ti3C2Tx, have broad applications in flexible electronics, electromechanical devices, and structural membranes due to their unique physical and chemical properties. Despite the Young's modulus of 2D Ti3C2Tx has been theoretically predicted to be 0.502 TPa, which has not been experimentally confirmed so far due to the measurement is extremely restricted. Here, by optimizing the sample preparation, cutting, and transfer protocols, we perform the direct in-situ tensile tests on monolayer Ti3C2Tx nanosheets using nanomechanical push-to-pull equipment under a scanning electron microscope. The effective Young's modulus is 0.484 ± 0.013 TPa, which is much closer to the theoretical value of 0.502 TPa than the previously reported 0.33 TPa by the disputed nanoindentation method, and the measured elastic stiffness is ~948 N/m. Moreover, during the process of tensile loading, the monolayer Ti3C2Tx shows an average elastic strain of ~3.2% and a tensile strength as large as ~15.4 GPa. This work corrects the previous reports by nanoindentation method and demonstrates that the Ti3C2Tx indeed keeps immense potential for broad range of applications. The Young's modulus of the MXene Ti3C2Tx, theoretically predicted to be 0.502 TPa, has not yet been experimentally confirmed. This work supplants previous reports using nanoindentation with the correctly measured Young's modulus of 0.484 ± 0.013 TPa. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the prebiotic potential of polysaccharides derived from Stellariae Radix (SRPs) and explore their influence on the gut microbiota composition in mice. Lactobacillus acidophilus and Bifidobacterium longum were cultivated in an MRS medium, while their growth kinetics, clumping behavior, sugar utilization, pH variation, growth density, and probiotic index were meticulously monitored. Additionally, the impact of crude Stellariae Radix polysaccharides (CSRP) on the richness and diversity of gut microbiota in mice was assessed via 16S rDNA sequencing. The results demonstrated the remarkable ability of CSRPs to stimulate the proliferation of Lactobacillus acidophilus and Bifidobacterium longum. Moreover, the oral administration of CSRPs to mice led to a noticeable increase in beneficial bacterial populations and a concurrent decrease in detrimental bacterial populations within the intestinal flora. These findings provided an initial validation of CSRPs as a promising agent in maintaining the equilibrium of gut microbiota in mice, thereby offering a substantial theoretical foundation for developing Stellariae Radix as a prebiotic ingredient in various applications, including food, healthcare products, and animal feed. Furthermore, this study presented novel insights for the exploration and utilization of Stellariae Radix resources. [ABSTRACT FROM AUTHOR]

The original plant of Chinese medicine Stellariae Radix (Yin Chai Hu) is Stellaria dichotoma L. var. lanceolata Bge (abbreviated as SDL). SDL is a perennial herbaceous plant and a characteristic crop in Ningxia. Growth years are vital factors that affect the quality of perennial medicinal materials. This study aims to investigate the impact of growth years on SDL and screen for the optimal harvest age by comparing the medicinal material characteristics of SDL with different growth years. Additionally, metabolomics analysis using UHPLC-Q-TOF MS was employed to investigate the impact of growth years on the accumulation of metabolites in SDL. The results show that the characteristics of medicinal materials and the drying rate of SDL gradually increase with the increase in growth years. The fastest development period of SDL occurred during the first 3 years, after which the development slowed down. Medicinal materials characteristics of 3-year-old SDL exhibited mature qualities with a high drying rate, methanol extract content, and the highest content of total sterols and total flavonoids. A total of 1586 metabolites were identified, which were classified into 13 major classes with more than 50 sub-classes. Multivariate statistical analysis indicated significant differences in the diversity of metabolites of SDL in different growth years, with greater differences observed in metabolites as the growth years increased. Moreover, different highly expressed metabolites in SDL at different growth years were observed: 1–2 years old was beneficial to the accumulation of more lipids, while 3–5 years old was conducive to accumulating more alkaloids, benzenoids, etc. Furthermore, 12 metabolites accumulating with growth years and 20 metabolites decreasing with growth years were screened, and 17 significantly different metabolites were noted in 3-year-old SDL. In conclusion, growth years not only influenced medicinal material characteristics, drying rate, content of methanol extract, and total sterol and flavonoid contents, but also had a considerable effect on SDL metabolites and metabolic pathways. SDL planted for 3 years presented the optimum harvest time. The screened significantly different metabolites with biological activity, such as rutin, cucurbitacin e, isorhamnetin-3-o-glucoside, etc., can be utilized as potential quality markers of SDL. This research provides references for studying the growth and development of SDL medicinal materials, the accumulation of metabolites, and the selection of optimal harvest time. [ABSTRACT FROM AUTHOR]

Non-Hermitian metasurfaces provide an excellent platform for the study of parity-time (PT) symmetry transition. The exceptional point (EP) in the transition process exhibits peculiar physical phenomena and enriches the development of metasurfaces. In this study, a terahertz metal–graphene hybrid metasurface that can study PT symmetry transition and EP in transmission and reflection polarization channels is designed by using the phase transition characteristics of VO2. The tunable asymmetric loss and PT symmetry transition can be actively controlled by changing the Fermi energy of the graphene strip. Interestingly, owing to the special chirality of the structure, the original metasurface, and the mirrored metasurface degenerate into a circularly polarized state with opposite rotations at the same Fermi energy. The π-phase mutation at EP is observed following the interaction of circularly polarized waves and the metasurface and is expected to have good application prospects in environmental monitoring and gas sensing. [ABSTRACT FROM AUTHOR]

Stellaria Radix, called Yinchaihu in Chinese, is a traditional Chinese medicine, which is obtained from the dried roots of Stellaria dichotoma L. var. lanceolata Bge. Cultivated yinchaihu (YCH) has become a main source of production to alleviate the shortage of wild plant resources, but it is not clear whether the metabolites of YCH change with the mode of production. In this study, the contents of methanol extracts, total sterols and total flavonoids in wild and cultivated YCH are compared. The metabolites were analyzed by ultra-high performance liquid chromatography–tandem time-of-flight mass spectrometry. The content of methanol extracts of the wild and cultivated YCH all exceeded the standard content of the Chinese Pharmacopoeia. However, the contents of total sterols and total flavonoids in the wild YCH were significantly higher than those in the cultivated YCH. In total, 1586 metabolites were identified by mass spectrometry, and 97 were significantly different between the wild and cultivated sources, including β-sitosterol, quercetin derivatives as well as many newly discovered potential active components, such as trigonelline, arctiin and loganic acid. The results confirm that there is a rich diversity of metabolites in the wild and cultivated YCH, and provide a useful theoretical guidance for the evaluation of quality in the production of YCH. [ABSTRACT FROM AUTHOR]

The mid-infrared absorber is an important device for effective capture of high by atmospheric infrared transparent window, and has been a research hotspot in military, medical, biological and other fields. In this paper, a kind of ultra-thin mid-infrared ultra-broadband absorber with background insensitive is realized by stacking four metal/dielectric films (Si/Ag/Si3N4/SiO2) on silver substrate and periodically arranged cross-anchor metal pattern in a method of finite-difference time domain. The results show that the absorption rate is more than 90% and the relative absorption bandwidth is 95.5% in the wavelength ranging from 9.1 μm to 24.1 μm. The average absorptivity is 92% in the range of background refractive index (n = 1∼1.8), A proof of the device's insensibility to background refractive index. At a large incidence angle (θ ≤ 50°), the lowest absorption rate is up to 80%. The thickness of the optimized device is only 1.7 μm. The research results have important application value in infrared remote sensing, pollution monitoring, disease diagnosis and other fields. [ABSTRACT FROM AUTHOR]

Immune system dysregulation is associated with tumor incidence and growth. Here, we established an RNA-based individualized immune signature associated with prognosis for nonsmall cell lung cancer (NSCLC) to guide adjuvant therapy. We downloaded publicly accessible data on RNA expression and clinical characteristics of NSCLC from the Cancer Genome Atlas (TCGA). From immune-related genes (IRGs) retrieved from the immunology database and analysis portal (ImmPort) database, we then screened differentially expressed immune-related genes (DEIRGs). Using overall survival (OS) as a clinical endpoint, we identified 26 prognostic DEIRGs via univariate and multivariate Cox regression analysis, and then developed a risk model based on these 26 IRGs with an area under the curve (AUC) of 0.701, and its predictive ability independent from other clinical factors. We also downloaded tumor immune infiltrate data and analyzed the correlations between lymphocytic infiltration with our risk scores, but found no significant association. Furthermore, we retrieved 86 differentially expressed transcription factors (TFs) to assess their regulatory relationships with the 26 prognostic DEIRGs. In summary, we developed a robust risk model to predict survival in patients with NSCLC, based on the expression of 26 IRGs. It provides novel predictive and therapeutic molecular targets. [ABSTRACT FROM AUTHOR]

Background: Predicting the recurrence risk of bladder cancer is crucial for the individualized clinical treatment of patients with bladder cancer. Objective: To explore the radiomics based on multiphase CT images combined with clinical risk factors, and to further construct a radiomics-clinical model to predict the recurrence risk of bladder cancer within 2 years after surgery. Methods: Patients with bladder cancer who underwent surgical treatment at the First Affiliated Hospital of Soochow University from January 2016 to December 2019 were retrospectively included and followed up to record the disease recurrence. A total of 183 patients were included in the study, and they were randomly divided into training group and validation group in a ratio of 7: 3. The three basic models which are plain scan, corticomedullary phase, and nephrographic phase as well as two combination models, namely, corticomedullary phase + nephrographic phase and plain scan + corticomedullary phase + nephrographic phase, were built with the logistic regression algorithm, and we selected the model with higher performance and calculated the Rad-score (radiomics score) of each patient. The clinical risk factors and Rad-score were screened by Cox univariate and multivariate proportional hazard models in turn to obtain the independent risk factors, then the radiomics-clinical model was constructed, and their performance was evaluated. Results: Of the 183 patients included, 128 patients constituted the training group and 55 patients constituted the validation group. In terms of the radiomics-clinical model constructed by three independent risk factors—number of tumors, tumor grade, and Rad-score—the AUCs of the training group and validation group were 0.813 (95% CI 0.740–0.886) and 0.838 (95% CI 0.733–0.943), respectively. In the validation group, the diagnostic accuracy, sensitivity, and specificity were 0.727, 0.739, and 0.719, respectively. Conclusion: Combining with radiomics based on multiphase CT images and clinical risk factors, the radiomics-clinical model constructed to predict the recurrence risk of bladder cancer within 2 years after surgery had a good performance. [ABSTRACT FROM AUTHOR]

Optical tweezers are key tools to trap and manipulate nanoparticles in a non-invasive way, and have been widely used in the biological and medical fields. We present an integrated multifunctional 2D plasmonic optical tweezer consisting of an array of graphene discs and the substrate circuit. The substrate circuit allows us to apply a bias voltage to configure the Fermi energy of graphene discs independently. Our work is based on numerical simulation of the finite element method. Numerical results show that the optical force is generated due to the localized surface plasmonic resonance (LSPR) mode of the graphene discs with Fermi Energy Ef = 0.6 eV under incident intensity I = 1 mW/μm2, which has a very low incident intensity compared to other plasmonic tweezers systems. The optical forces on the nanoparticles can be controlled by modulating the position of LSPR excitation. Controlling the position of LSPR excitation by bias voltage gates to configure the Fermi energy of graphene disks, the nanoparticles can be dynamically transported to arbitrary positions in the 2D plane. Our work is integrated and has multiple functions, which can be applied to trap, transport, sort, and fuse nanoparticles independently. It has potential applications in many fields, such as lab-on-a-chip, nano assembly, enhanced Raman sensing, etc. [ABSTRACT FROM AUTHOR]

Background: To evaluate the preoperative predictive value of radiomics in the diagnosis of breast cancer (BC). Methods: By searching PubMed and Embase libraries, our study identified 19 eligible studies. We conducted a meta-analysis to assess the differential value in the preoperative assessment of BC using radiomics methods. Results: Nineteen radiomics studies focusing on the diagnostic efficacy of BC and involving 5865 patients were enrolled. The integrated sensitivity and specificity were 0.84 (95% CI: 0.80–0.87, I 2 = 76.44%) and 0.83 (95% CI: 0.78–0.87, I 2 = 81.79%), respectively. The AUC based on the SROC curve was 0.91, indicating a high diagnostic value. Conclusion: Radiomics has shown excellent diagnostic performance in the preoperative prediction of BC and is expected to be a promising method in clinical practice. [ABSTRACT FROM AUTHOR]

As a byproduct of coal tar distillation, coal tar pitch (CTP) has been proven to be carcinogenic to human. However, the mechanisms of lung cancer induced by CTP are still unclear. It has been shown that long non-coding RNAs (LncRNAs) play an important role in the development of human cancers. This study aims to investigate the effect of LncRNA-ENST00000556926 on malignant-transformed human bronchial epithelial (BAES-2B) cells induced by coal tar pitch extracts (CTPE). In this study, BEAS-2B cells were treated with 2.4 μg/ml of CTPE for 72 h and then passaged; and the cells were treated 4 times in the same procedure, then passaged until passage 30 (CTPE30). Cell counting kit-8 (CCK-8) assay was used to detect cell viability, then cell cycle and apoptosis were analyzed by flow cytometry, and transcriptome sequencing analysis was used to detect differentially expressed mRNAs after interference of ENST00000556926. The results indicated that the expression of ENST00000556926 in CTPE30 group was significantly higher compared with control group. Furthermore, after interfering the expression of ENST00000556926, cell viability was inhibited, and cell cycle was arrested while apoptosis of malignant-transformed BEAS-2B cells was promoted. Moreover, a total of 159 differentially expressed mRNAs were screened out after interference of ENST00000556926, including 62 up-regulated mRNAs and 97 down-regulated mRNAs. In addition, knockdown of ENST00000556926 decreased the expression of thioredoxin domain containing 5 (TXNDC5) and FOXD1. In conclusion, LncRNA-ENST00000556926 could regulate the proliferation, apoptosis and mRNA transcriptome of malignant-transformed BEAS-2B cells induced by CTP, which may provide a novel treatment strategy for lung cancer. Graphical Abstract [ABSTRACT FROM AUTHOR]

Recycling waste into new materials and energy is becoming a major challenge in the context of the future circular economy, calling for advanced methods of waste treatment. For instance, microbially-mediated anaerobic digestion is widely used for conversion of sewage sludge into biomethane, fertilizers and other products, yet the efficiency of microbial digestion is limited by the occurrence of antibiotics in sludges, originating from drug consumption for human and animal health. Here we present antibiotic levels in Chinese wastewater, then we review the effects of antibiotics on hydrolysis, acidogenesis and methanogenesis, with focus on macrolides, tetracyclines, β-lactams and antibiotic mixtures. We detail effects of antibiotics on fermentative bacteria and methanogenic archaea. Most results display adverse effects of antibiotics on anaerobic digestion, yet some antibiotics promote hydrolysis, acidogenesis and methanogenesis. [ABSTRACT FROM AUTHOR]

This paper presents a new surveillance video synopsis method which performs much better than previous approaches in terms of both compression ratio and artifact. Previously, a surveillance video was usually compressed by shifting the moving objects of that video forward along the time axis, which inevitably yielded serious collision and chronological disorder artifacts between the shifted objects. The main observation of this paper is that these artifacts can be alleviated by changing the speed or size of the objects, since with varied speed and size the objects can move more flexibly to avoid collision points or to keep chronological relationships. Based on this observation, we propose a video synopsis method that performs object shifting, speed changing, and size scaling simultaneously. We show how to integrate the three heterogeneous operations into a single optimization framework and achieve high-quality synopsis results. Unlike previous approaches that usually use alternative optimization strategies to solve synopsis optimizations, we develop a Metropolis sampling algorithm to find the solution for our three-variable optimization problem. A variety of experiments demonstrate the effectiveness of our method. [ABSTRACT FROM AUTHOR]

In China, carbon dioxide (CO 2) emissions have been in a state of constant growth, and CO 2 emission reduction is a considerable challenge for China. The paper uses the IPAT-E (I = Human Impact, P = Population, A = Affluence, T = Technology, E = Energy) model to determine and classify the influencing factors of CO 2 emissions. Based on the provincial panel data, the paper used the partial least squares (PLS) method to establish a structural equation model (SEM), and analyzes the path coefficient between CO 2 emissions and its influencing factors. The paper contains 16 indicators from 2001 to 2016. Empirical results show that affluence, technology and energy have a significant positive impact on CO 2 emissions at the national level. And the affluence factor under the influence of population factor has the greatest impact. From a regional perspective, affluence factor has a significant positive impact on CO 2 emissions in the Northeast, East, Northwest, Southwest, and Central South China, with the largest impact on the Southwest. Technology factor has a small positive impact on East, Northwest and Southwest China. Energy factor has a significant positive impact on the Northeast, North, East China, Northwest and Central South China, with the greatest impact on North China. Affluence and technology factors have a negative impact on CO 2 emissions in North China. In addition, the population has a greater impact on affluence, with minimal impact on the Southwest. This study provides a comprehensive and accurate indicator estimation framework for CO 2 emissions. And the paper provides theoretical support for the government to formulate policies. This picture shows that the influencing path of various factors on CO 2 emissions and indicates the path coefficients of each factor, which constructs an indicator system that affects CO 2 emissions. Unlabelled Image • Utilize the IPAT-E model to identify factors that affect China's CO 2 emissions • Quantitatively study the contributions of each factor to CO 2 emissions • Combine IPAT-E and PLS-SEM models to construct a CO 2 emission research framework • Provide theoretical support for China to formulate CO 2 emission reduction policies [ABSTRACT FROM AUTHOR]

This figure describes the increments of CO 2 during 2002–2016 on the basis of 2001 and the contribution of various influencing factors to CO 2 emissions. • This paper analyzes the contribution of driving forces to industrial CO 2 emissions. • This paper optimizes the spectral clustering though the geodesic distance. • Industrialization has shifted from the eastern coast to the north and middle-west. • This paper utilizes 19 energy types to calculate CO 2 emissions. • China's 30 provinces are clustered into 6 clusters by spectral clustering. Understanding the CO 2 (carbon dioxide) emissions mechanisms in each province is important to reduce China's CO 2 emissions and achieve carbon reduction targets. This paper combines two-layer LMDI (logarithmic mean divisia index) method and spectral clustering to analyze industrial CO 2 emission drivers in 30 provinces of China and proposes carbon reduction policies. First, each province's industrial CO 2 emission factors are decomposed into energy structure, energy intensity, industrialization level, per capita GDP and total population; energy intensity and per capita GDP play a dominant role in suppressing and promoting industrial CO 2 emissions, respectively. The industrialization level has gradually developed from the eastern coastal areas to the north and the central and western regions, especially Inner Mongolia, Jilin, Henan and Sichuan. The impact mechanisms of the provinces on China's CO 2 emissions are very different from temporal and spatial angle. Second, this paper optimizes spectral clustering though geodesic distance and utilizes it to cluster 30 provinces in China. Finally, based on the characteristics of CO 2 emissions and clustering results, more targeted carbon emission reduction strategies are proposed. Therefore, the formulation of carbon emission reduction policies should not only consider the surface characteristics of CO 2 emissions, but also explore the root causes of CO 2 emissions. [ABSTRACT FROM AUTHOR]

The amount of solar ultraviolet-B (UV–B) radiation reaching the Earth's surface is increasing due to stratospheric ozone dynamics and global climate change. Increased UV-B radiation poses a major threat to ecosystems. Although many studies have focused on the potential effects of enhanced UV-B radiation on plants, the dynamic changes of defense response in plants under continuous UV-B radiation remains enigmatic. In this study, we investigated the effect of UV-B radiation at 0.024 W/m2 on the UVR8-and reactive oxygen species (ROS-) signaling pathways, antioxidant system, and wax synthesis of G. uralensis. These parameters were investigated at different UV-B radiation stages (2 h, 6 h, 12 h, 24 h, 48 h, and 96 h). The results revealed that the uvr8 expression level was significantly repressed after 2 h of UV-B radiation, partly because G. uralensis rapidly acclimated to UV-B. Significant H 2 O 2 accumulation occurred after 12 h UV-B radiation, resulting in activation of the ROS signaling pathway and the antioxidant system. After 24 h of UV-B radiation, wax synthesis was enhanced alongside a decrease in the capacity of the main antioxidant system. The dynamic and ordered changes in these pathways reveal how different strategies function in G. uralensis at different times during adaption to enhanced UV-B radiation. This study will help us better understand dynamic changes of defense response in plant under enhanced UV-B radiation, further providing fundamental knowledge to develop plant resistance gene resources. • A variety of different strategies were operated at different times in G. uralensis to adapt to enhanced UV-B radiation. • UVR8 signaling pathway was significantly repressed after 2 h of UV-B radiation. • ROS level was elevated after 6 h of UV-B radiation. • Main antioxidase activities were increased after 6 h of UV-B radiation, but decreased after 24 h of UV-B radiation. • Core genes for wax synthesis were up-regulated after 24 h of UV-B radiation. [ABSTRACT FROM AUTHOR]