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Abstract Rationale and Objectives The management of complex renal cysts is guided by the Bosniak classification system, which may be inadequate for risk stratification of patients to determine the appropriate intervention. Radiomics models based on CT imaging may provide additional useful information. Materials and Methods A total of 322 patients with Bosniak II-IV cysts were included in the study from January 2010 to December 2019. Contrast-enhanced CT scans were performed on all patients. ITK-snap was used for segmentation, and the PyRadiomics 3.0.1 package was used for feature extraction. The radiomics features were screened via the least absolute shrinkage and selection operator (LASSO) regression method. After feature selection, a logistic regression (LR) model, support vector machine (SVM) model and random forest (RF) model were constructed. Results In the present study, 217 benign renal cysts (67.4%) and 105 cystic renal cell carcinomas (32.6%) were identified. According to the Bosniak classification, the sample included 179 (55.6%) Bosniak II cysts, 38 (11.8%) Bosniak IIF cysts, 44 (13.7%) Bosniak III cysts and 61 (18.9%) Bosniak IV cysts. A total of 1334 radiomics features were extracted from both unenhanced and cortical CT scans. After LASSO regression, all the models (LR, SVM and RF) showed satisfactory discrimination and reliability in both unenhanced and cortical CT scans (AUC > 0.950). In the Bosniak IIF-III subgroup analysis, the diagnostic accuracy of the LR model was very low for both the unenhanced and cortical scans. In contrast, the SVM model and RF model showed excellent and stable performance in classifying Bosniak IIF-III cysts. The AUCs of the models were all > 0.85, with a maximum of 0.941. The sensitivity, specificity, accuracy, and AUC of the RF model were 0.889, 0.913, 0.902, and 0.941, respectively. Conclusion Our data indicate that radiomics models can effectively distinguish between cystic renal cell carcinoma (cRCC) and complex renal cysts (Bosniak II-IV). Radiomics models may still have high diagnostic accuracy even for Bosniak IIF-III cysts that are clinically difficult to distinguish. However, external validation of these findings is still needed.

Abstract Background This study aims to develop a hierarchical classification method to automatically assess the severity of knee osteoarthritis (KOA). Methods This retrospective study recruited 4074 patients. Clinical diagnostic indicators and clinical diagnostic processes were applied to develop a hierarchical classification method that involved four sub-task classifications. These four sub-task classifications were the classification of Kellgren-Lawrence (KL) grade 0–2 and KL grade 3–4, KL grade 3 and KL grade 4, KL grade 0 and KL grade 1–2, and KL grade 1 and KL grade 2, respectively. To extract the features of clinical diagnostic indicators, four U-Net models were first used to segment the total joint space (TJS), the lateral joint space (LJS), the medial joint space (MJS), and osteophytes, respectively. Based on the segmentation result of TJS, the region of knee subchondral bone was generated. Then, geometric features were extracted based on segmentation results of the LJS, MJS, TJS, and osteophytes, while radiomic features were extracted from the knee subchondral bone. Finally, the geometric features, radiomic features, and combination of geometric features and radiomic features were used to construct the geometric model, radiomic model, and combined model in KL grading, respectively. A strict decision strategy was used to evaluate the performance of the hierarchical classification method in all X-ray images of testing cohort. Results The U-Net models achieved relatively satisfying performances in the segmentation of the TJS, the LJS, the MJS, and the osteophytes with the dice similarity coefficient of 0.88, 0.86, 0.88, and 0.64 respectively. The combined models achieved the best performance in KL grading. The accuracy of combined models was 98.50%, 81.65%, 82.07%, and 74.10% in the classification of KL grade 0–2 and KL grade 3–4, KL grade 3 and KL grade 4, KL grade 0 and KL grade 1–2, and KL grade 1 and KL grade 2, respectively. For all X-ray images of the testing cohort, the accuracy of the hierarchical classification method was 65.98%. Conclusion The hierarchical classification method developed in the current study is a feasible approach to assess the severity of KOA.

Abstract There is a lack of in-depth research on the impacts and changes in chronic psychological stress (CPS) on the cardiovascular system after acute myocardial infarction (AMI). This study aims to explore the comorbid mechanism and dynamic evolution of AMI exposed to CPS. 120 Wistar rats were randomly divided into Sham Operation group, Sham Operation + Chronic Unpredictable Mild Stress (CUMS) group, AMI group and AMI + CUMS group, with each group further divided into subgroups at days 7, 14, and 28. The AMI model was created by ligating the left anterior descending coronary artery, and CUMS model was used to induce CPS in rats. Behavioral changes were assessed through open field tests and sucrose preference tests. Cardiac function and structure were evaluated via echocardiography. The serum levels of TNFα, IL-6, NO, ET, CK-MB, cTNT, and ANP were measured using assay kits. Pathological changes in cardiac and brain tissues were observed under an optical microscope. Comparative analysis across different models revealed that CUMS significantly reduced behavioral activities in rats, with an interaction between CUMS and AMI affecting total distance (P

This paper addresses the problem of high-resolution imaging of shadowed multiple-targets with limited labeled data, by proposing a transfer-learning-based method for through-the-wall radar imaging. First, a generative adversarial sub-network is developed to facilitate the migration of labeled simulation data to measured data, overcoming the difficulty of generating labeled data. This method incorporates an attention mechanism, adaptive residual blocks, and a multi-scale discriminator to improve the quality of image migration. It also incorporates a structural consistency loss function to minimize perceptual differences between images. Finally, the labeled data are used to train the through-the-wall radar target-imaging sub-network, achieving high-resolution imaging of multiple targets through walls. Experimental results show that the proposed method effectively reduces discrepancies between simulated and obtained images, and generates pseudo-measured images with labels. It systematically addresses issues such as side/grating ghost interference, target image defocusing, and multi-target mutual interference, significantly improving the multi-target imaging quality of the through-the-wall radar. The imaging accuracy achieved is 98.24%, 90.97% and 55.17% for single, double, and triple-target scenarios, respectively. Compared with CycleGAN, the imaging accuracy for the corresponding scenarios is improved by 2.29%, 40.28% and 15.51%, respectively.

Abstract Active surveillance (AS) is the primary strategy for managing patients with low or favorable-intermediate risk prostate cancer (PCa). Identifying patients who may benefit from AS relies on unpleasant prostate biopsies, which entail the risk of bleeding and infection. In the current study, we aimed to develop a radiomics model based on prostate magnetic resonance images to identify AS candidates non-invasively. A total of 956 PCa patients with complete biopsy reports from six hospitals were included in the current multicenter retrospective study. The National Comprehensive Cancer Network (NCCN) guidelines were used as reference standards to determine the AS candidacy. To discriminate between AS and non-AS candidates, five radiomics models (i.e., eXtreme Gradient Boosting (XGBoost) AS classifier (XGB-AS), logistic regression (LR) AS classifier, random forest (RF) AS classifier, adaptive boosting (AdaBoost) AS classifier, and decision tree (DT) AS classifier) were developed and externally validated using a three-fold cross-center validation based on five classifiers: XGBoost, LR, RF, AdaBoost, and DT. Area under the receiver operating characteristic curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE) were calculated to evaluate the performance of these models. XGB-AS exhibited an average of AUC of 0.803, ACC of 0.693, SEN of 0.668, and SPE of 0.841, showing a better comprehensive performance than those of the other included radiomic models. Additionally, the XGB-AS model also presented a promising performance for identifying AS candidates from the intermediate-risk cases and the ambiguous cases with diagnostic discordance between the NCCN guidelines and the Prostate Imaging-Reporting and Data System assessment. These results suggest that the XGB-AS model has the potential to help identify patients who are suitable for AS and allow non-invasive monitoring of patients on AS, thereby reducing the number of annual biopsies and the associated risks of bleeding and infection.

Abstract The research investigated the tooth backlash influences the error in seedling picking trajectories of the gear train SPM. First, a sine function and the sum of random errors are taken into account is utilized to fit the tooth backlash of the firstly and secondary transmissions. Additionally, the analysis established the relationship between the fitting parameters and the tooth backlash of the firstly and secondary transmissions, in order to determine the appropriate fitting parameters. Next, the relationship between the tooth backlash of the firstly and secondary transmission in the seedling picking mechanism (SPM) and the x, y coordinates, as well as the velocity and acceleration of the seedling needle tip (SNT), is examined. This analysis is based on the error and movement variance of the coordinate and kinematic parameters of SNT. The results indicate that the tooth backlash of the firstly transmission has a more significant influence on the error of the seedling picking trajectory compared to the tooth backlash of the secondary transmission. When the tooth backlash of the noncircular gear in the firstly transmission reaches its maximum value of 0.24 mm, the x and y coordinates of the SNT can reach maximum values of 1 and 3.5 mm. The test of the jumping of the needle tip and idling trajectory description indicated that noncircular gears with larger tooth backlash exhibit higher positional jumping at the tip of the seedling needle.

Background Oxylipin metabolism plays an essential role in glioma progression and immune modulation in the tumor microenvironment. Lipid metabolic reprogramming has been linked to macrophage remodeling, while the understanding of oxylipins and their catalyzed enzymes lipoxygenases in the regulation of glioma-associated microglia/macrophages (GAMs) remains largely unexplored.Methods To explore the pathophysiological relevance of oxylipin in human glioma, we performed Ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) analysis in human glioma and non-tumor brain tissues. To comprehensively investigate the role of arachidonate lipoxygenase 5 (ALOX5) in glioma, we performed in vivo bioluminescent imaging, immunofluorescence staining and flow cytometry analysis on tumors from orthotopic glioma-bearing mice. We developed an ALOX5-targeted nanobody, and tested its anti-glioma efficacy of combination therapy with α-programmed cell death protein-1 (PD-1).Results In this study, we found that ALOX5 and its oxylipin 5-hydroxyeicosatetraenoic acid (5-HETE) are upregulated in glioma, accumulating programmed death-ligand 1 (PD-L1)+ M2-GAMs and orchestrating an immunosuppressive tumor microenvironment. Mechanistically, 5-HETE derived from ALOX5-overexpressing glioma cells, promotes GAMs migration, PD-L1 expression, and M2 polarization by facilitating nuclear translocation of nuclear factor erythroid 2-related factor 2. Additionally, a nanobody targeting ALOX5 is developed that markedly suppresses 5-HETE efflux from glioma cells, attenuates M2 polarization of GAMs, and consequently ameliorates glioma progression. Furthermore, the combination therapy of the ALOX5-targeted nanobody plus α-PD-1 exhibits superior anti-glioma efficacy.Conclusions Our findings reveal a pivotal role of the ALOX5/5-HETE axis in regulating GAMs and highlight the ALOX5-targeted nanobody as a potential therapeutic agent, which could potentiate immune checkpoint therapy for glioma.

Timely and accurate monitoring of above-ground biomass (AGB) is of great significance for indicating crop growth status, predicting yield, and assessing carbon dynamics. Compared with the traditional time-consuming and laborious method through destructive sampling, UAV remote sensing provides a timely and efficient strategy for estimating biomass. However, the universality of remote sensing retrieval models with multi-feature fusion under different management practices and cultivars are unknown. The spectral, textural, and structural features extracted by UAV multispectral and RGB imaging, coupled with agricultural meteorological parameters, were integrated to estimate the AGB in potato during the whole growth period. Six advanced modeling algorithms, including random forest (RF), partial least squares regression (PLSR), multiple linear regression (MLR), simple linear regression (SLR), ridge regression (RR), and lasso regression (LR) models, were adopted to evaluate the ability of estimating AGB by single feature and multi-feature information fusion. The results indicate the following: (1) The newly proposed variety-dependent indicator growth process ratio (GPR) can improve the model accuracy by over 20%. (2) The fusion of vegetation indices, canopy cover, growing degree days, and GPR achieved higher accuracy to estimate AGB at all growth stages compared with single feature model. (3) RF model performed best for the estimation of AGB during the whole growth period with R2 0.79 and rRMSE 0.24 ton/ha. The study demonstrated that the fusion of multi-feature coupled with the machine learning algorithm achieved the best performance for estimating potato AGB under different management practices and cultivars, which can be a potential and useful phenotyping strategy for estimating AGB at refined plot scale during the whole growth period.

Sintering is a common phenomenon, which often takes place during the oxidation roasting process of molybdenite concentrate in multiple-hearth furnaces. The occurrence of sintering phenomena has detrimental effects on the product quality and the service life of the furnace. In this work, the influence of two key factors (roasting temperature and K content) on the sintering behavior is investigated using molybdenite concentrate as the raw material. Different technologies such as XRD, FESEM-EDS, and phase diagrams are adopted to analyze the experimental data. The results show that the higher the roasting temperature is, the greater the mass loss and the more serious the sintering degree will be. The results also show that with the increase in K content, the mass loss of the raw material is first increased and then decreased, while its sintering degree is still gradually increased. The sintering products obtained during the oxidation roasting process are often tightly combined with the bottom of the used crucible with a smooth and dense surface structure, while their internal microstructures are very complicated, which not only includes numerous MoO3 species, but also unoxidized MoS2, Mo sub-oxide, SiO2, and a variety of molybdates. Among them, both MoO3 and molybdates can be easily dissolved into the ammonia solution, leading to a residue mainly composed of SiO2 and CaMoO4. This study also finds that the sintering phenomenon is caused by the increase in local temperature and the formation of various low-melting-point eutectics. It is suggested that decreasing the roasting temperature and K content, especially the K content, are effective methods for reducing the sintering degree of molybdenite concentrate during the oxidation roasting process.

Abstract We successfully removed a rare ectopic pituitary adenoma from a 64-year-old female patient initially misdiagnosed with a chordoma. The tumor was located in the slope region and posed a challenge due to its rarity and location. Using neuro-navigation and neuro-endoscopic techniques, we performed a transnasal transsphenoidal resection and confirmed postoperatively that the tumor was a non-functional pituitary adenoma. Although the patient experienced temporary cortisol deficiency after surgery, she recovered well. To accurately diagnose ectopic pituitary adenomas of clivus, doctors must carefully evaluate the patient's imaging results and hormone levels. If necessary, nuclear medicine scans can also aid in diagnosis. Endoscopic transnasal-transsphenoidal surgery is the preferred treatment method, and preoperative multimodal imaging evaluation and intraoperative neuro-navigation technology are essential for a successful surgery.

The temporal dynamics of canopy growth are closely related to the accumulation and distribution of plant dry matter. Recently, unmanned aerial vehicles (UAVs) equipped with various sensors have been increasingly adopted in crop growth monitoring. In this study, two potato varieties were used as materials, and treated with different combinations of nitrogen forms (nitrate and ammonium) and application rates (0, 150, and 300 kg ha−1). A canopy development model was then constructed using low-cost time-series RGB imagery acquired by UAV. The objectives of this study were to quantify the variation in canopy development parameters under different nitrogen treatments and to explore the model parameters that represent the dynamics of plant dry matter accumulation, as well as those that contribute significantly to yield. The results showed that, except for the thermal time to canopy senescence (t2), other parameters of the potato canopy development model exhibited varying degrees of variation under different nitrogen treatments. The model parameters were more sensitive to nitrogen forms, such as ammonium and nitrate, than to application rates. The integral area (At) under the canopy development curve had a direct effect on plant dry matter accumulation (path coefficient of 0.78), and the two were significantly positively correlated (Pearson correlation coefficient of 0.93). Integral area at peak flowering (AtII) was significantly correlated with yield for both single and mixed potato varieties, having the greatest effect on yield (total effect of 1.717). In conclusion, UAV-acquired time-series RGB imagery could effectively quantify the variation of potato canopy development parameters under different nitrogen treatments and monitor the dynamic changes in plant dry matter accumulation. The regulation of canopy development parameters is of great importance and practical value for optimizing nitrogen management strategies and improving yield.

Abstract This study aims to discriminate between leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis and gamma-aminobutyric acid B (GABAB) receptor antibody encephalitis using a convolutional neural network (CNN) model. A total of 81 patients were recruited for this study. ResNet18, VGG16, and ResNet50 were trained and tested separately using 3828 positron emission tomography image slices that contained the medial temporal lobe (MTL) or basal ganglia (BG). Leave-one-out cross-validation at the patient level was used to evaluate the CNN models. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were generated to evaluate the CNN models. Based on the prediction results at slice level, a decision strategy was employed to evaluate the CNN models’ performance at patient level. The ResNet18 model achieved the best performance at the slice (AUC = 0.86, accuracy = 80.28%) and patient levels (AUC = 0.98, accuracy = 96.30%). Specifically, at the slice level, 73.28% (1445/1972) of image slices with GABAB receptor antibody encephalitis and 87.72% (1628/1856) of image slices with LGI1 antibody encephalitis were accurately detected. At the patient level, 94.12% (16/17) of patients with GABAB receptor antibody encephalitis and 96.88% (62/64) of patients with LGI1 antibody encephalitis were accurately detected. Heatmaps of the image slices extracted using gradient-weighted class activation mapping indicated that the model focused on the MTL and BG for classification. In general, the ResNet18 model is a potential approach for discriminating between LGI1 and GABAB receptor antibody encephalitis. Metabolism in the MTL and BG is important for discriminating between these two encephalitis subtypes.

Abstract Background In this phase Ib/II open-label study, tumor immune suppression was targeted in patients with advanced refractory solid tumors and patients with recurrent/refractory non-small cell lung cancer (NSCLC) using galunisertib with nivolumab. Methods Eligible patients were ≥ 18 years old, had an Eastern Cooperative Oncology Group performance status ≤ 1, and were treatment-naive for anti-programmed cell death-1, its ligand, or transforming growth factor β receptor 1 kinase inhibitors. Phase Ib was an open-label, dose-escalation assessment of the safety and tolerability of galunisertib with nivolumab in patients with advanced refractory solid tumors. Phase II evaluated the safety of galunisertib with nivolumab in NSCLC patients who had received prior platinum-based treatment but were immuno-oncology agent-naive. Results This trial was conducted between October 2015 and August 2020. No dose-limiting toxicities were observed in phase I. In the phase II NSCLC cohort (n = 25), patients received 150 mg twice daily galunisertib (14 days on/14 days off dosing schedule for all phases) plus nivolumab at 3 mg/kg (intravenously every 2 weeks). In this phase, the most frequent treatment-related adverse events (AEs) were pruritus (n = 9, 36%), fatigue (n = 8, 32%), and decreased appetite (n = 7, 28%). No grade 4 or 5 treatment-related AEs were observed. Six (24%) patients had confirmed partial response (PR) and 4 (16%) had stable disease; 1 additional patient had confirmed PR after initial pseudo-progression. The median duration of response was 7.43 months (95% confidence interval [CI]: 3.75, NR). Among the 7 responders, including the delayed responder, 1 had high PD-L1 expression (≥ 50%). The median progression-free survival was 5.26 months (95% CI: 1.77, 9.20) and the median overall survival was 11.99 months (95% CI: 8.15, NR). Interferon gamma response genes were induced post-treatment and cell adhesion genes were repressed, although the association of these observations with tumor response and clinical outcomes was not statistically powered due to limited samples available. Conclusions The study met its primary endpoint as galunisertib combined with nivolumab was well tolerated. Preliminary efficacy was observed in a subset of patients in the Phase 2 NSCLC cohort. Trial registration Trial registered with ClinicalTrials.gov (NCT02423343; 22.04.2015).

Dementia has become one of the most important diseases threatening human health. Alzheimer's disease (AD) and vascular dementia (VaD) have the highest incidence rates among the types of dementia, but until now, therapeutic methods have been limited. Panax ginseng has been used in China for thousands of years to treat dementia, and modern medical studies have found that it contains multiple active components, such as ginsenosides, polysaccharides, amino acids, volatile oils and polyacetylenes, many of which have therapeutic effects in treating AD and VaD. Studies have found that ginsenosides have multitarget therapeutic effects in treating dementia, such as regulation of synaptic plasticity and the cholinergic system, inhibition of Aβ aggravation and tau hyperphosphorylation, anti-neuroinflammation, anti-oxidation effects and anti-apoptosis effects. Other active components of Panax ginseng, such as gintonin, oligosaccharides, polysaccharides and ginseng proteins, also have therapeutic effects on AD and VaD. The effectiveness of ginseng-containing Chinese medicine compounds has also been confirmed by clinical and basic investigations in treating AD and VaD. In this review, we summarized the potential therapeutic effects and related mechanisms of Panax ginseng in treating AD and VaD to provide some examples for further studies.

User-generated content (UGC) is developing rapidly as an emerging platform form, however, the problem of indirect copyright infringement by algorithms is becoming more and more prominent, and infringement governance has become a key act in the development of UGC platforms. When infringement occurs, recommendation algorithms expand the scope and results of infringement, while platforms choose to conspire with direct infringers for their own interests, making it difficult for infringed persons to defend their rights. In order to analyse the influence of different factors in the platform ecosystem on the subject's behavioural strategies, a "platform-infringer" evolutionary game model is constructed, and numerical simulation is used to verify the correctness of the stable results. Based on the simulation results, it is concluded that the factors of uncertain revenue, punishment and reputation loss have important influence on the decision-making behaviour of the subject of infringement governance, and accordingly, the proposed measures on the publishers, platforms and the legal level of the government are conducive to the evolution of the system to the point of positive regulation and stability of rights protection, with a view to promoting the healthier and more stable development of the UGC platforms.

Abstract Objective The management of paravebous sinus meningiomas that invade major venous sinuses is a subject of debate, particularly concerning the necessity of complete resection of the tumor and reconstruction of the venous sinus. This article aims to demonstrate the outcomes of total removal of the lesion (including the invading venous sinus portion) and the effects of restoring or not restoring venous circulation in terms of recurrence of the tumor, mortality, and post-operative complications. Methods The authors conducted a study involving 68 patients with paravebous sinus meningiomas. Of the 60 parasagittal meningiomas, 23 were located in the anterior third, 30 in the middle third, and 7 in the posterior third. Additionally, 3 lesions were located in the sinus confluence area, and 5 in the transverse sinus. All patients underwent surgery, and the degree of venous sinus involvement was classified into six types. For type I meningiomas, the outer layer of the sinus wall was stripped off. For types II to VI, two strategies were employed: non-constitutional, wherein the tumor and affected venous sinuses were removed without repair, and reconstructive, wherein the tumor was completely removed and the venous sinuses were sutured or repaired. Karnofsky Performance Status (KPS) scale and Magnetic Resonance Venography (MRV) were utilized to assess the outcomes of the surgical procedures. Results The study group of 68 patients underwent complete tumor resection in 97.1%, with sinus reconstruction attempted in 84.4% of cases with sinus wall and sinus cavity invasion. The recurrence rate of this group was 5.9%, with follow-up ranging from 33 to 57 months. It was found that the recurrence rate was significantly higher in cases with incomplete resection than in those with complete resection. The overall mortality rate was 4.4%, with all cases resulting from malignant brain swelling due to the failure to perform venous reconstruction after resectioning of the meningioma type VI. Furthermore, 10.3% of patients experienced worsening symptoms of neurological deficits or complete loss of neurological function, with a significantly higher incidence in those without venous reconstruction than in the venous reconstruction group (P

Organic photovoltaics (OPVs) have attracted widespread attention and became an important member of clean energy. Recently, their power conversion efficiency (PCE) has surpassed 19%. As is well known, the morphology of the active layer in OPVs crucially influences the PCE. In consideration of the intricate interactions between the donor molecules and acceptor molecules, the precise control of the morphology of the active layer is extremely challenging. Hence, it is urgent to develop effective methods to fabricate the hierarchical structure of the active layer. One significant driving force for the morphological evolution of the active layer is crystallization. Therefore, regulating the crystallization kinetics is an effective strategy for morphology control. In this review, we present the kinetic strategies recently developed to highlight their significance and effectiveness in morphology control. By applying these kinetic strategies, the hierarchical structure, including phase separation, domain size, crystallinity, and molecular orientation of the active layer can be optimized in different blend systems, leading to an improved PCE of OPVs. The outcomes set the stage for future advancements in device performance.

Atrial fibrillation (AF) is a common clinical arrhythmia whose pathogenesis has not been fully elucidated, and the inflammatory response plays an important role in the development of AF. The inflammasome is an important component of innate immunity and is involved in a variety of pathophysiologic processes. The NLRP3 inflammasome is by far the best studied and validated inflammasome that recognizes multiple pathogens through pattern recognition receptors of innate immunity and mediates inflammatory responses through activation of Caspase-1. Several studies have shown that NLRP3 inflammasome activation contributes to the onset and development of AF. Ecological dysregulation of the gut microbiota has been associated with the development of AF, and some evidence suggests that gut microbiota components, functional byproducts, or metabolites may induce or exacerbate the development of AF by directly or indirectly modulating the NLRP3 inflammasome. In this review, we report on the interconnection of NLRP3 inflammasomes and gut microbiota and whether this association is related to the onset and persistence of AF. We discuss the potential value of pharmacological and dietary induction in the management of AF in the context of the association between the NLRP3 inflammasome and gut microbiota. It is hoped that this review will lead to new therapeutic targets for the future management of AF.

BackgroundEndovascular thrombectomy (EVT) is an important treatment for patients with acute ischemic stroke (AIS). A number of studies have suggested that anesthesia type (conscious sedation vs. general anesthesia) during intra-arterial treatment for acute ischemic stroke has implications for patient outcomes.MethodsPubMed, EMBASE, Cochrane Library and clinicaltrials.gov were searched for randomized controlled trials (RCTs) that were performed to evaluate general anesthesia (GA) and conscious sedation (CS) up to May 30, 2023. Review Manager 5.3 software was used to assess the data. The risk ratio (RR) and mean difference (MD) were analyzed and calculated with a fixed effect model.ResultsWe pooled 930 patients from seven RCTs. We conducted a meta-analysis comparing the outcomes of GA and CS in the included trials. The rate of functional independence in the GA group was higher than that in the CS group (RR: 1.17, 95% CI: 1.00–1.35; P = 0.04; I2 = 16%). The GA group had a higher successful recanalization rate than the CS group (RR: 1.15, 95% CI: 1.08–1.22; P < 0.0001; I2 = 26%). The GA group had a higher pneumonia rate than the CS group (RR: 1.69, 95% CI: 1.22–2.34; P = 0.002; I2 = 26%). In addition, there was no significant difference between GA and CS with respect to the National Institutes of Health Stroke Scale (NIHSS) score at 24 h (P = 0.62), Modified Rankin Scale (mRS) score at 90 days (P = 0.25), intracerebral hemorrhage (P = 0.54), and mortality at 3 months (P = 0.61).ConclusionGA demonstrated superiority over CS in achieving successful recanalization and functional independence at 3 months when performing EVT in AIS patients. However, it was also associated with a higher risk of pneumonia. Further studies, particularly those with long-term follow-ups, are necessary to identify precise strategies for selecting the appropriate anesthetic modality in EVT patients.Systematic review registrationINPLASY202370116.

Timely and accurate prediction of crop yield is essential for increasing crop production, estimating planting insurance, and improving trade benefits. Potato (Solanum tuberosum L.) is a staple food in many parts of the world and improving its yield is necessary to ensure food security and promote related industries. We conducted a comprehensive literature survey to demonstrate methodological evolution of predicting potato yield. Publications on predicting potato yield based on methods of remote sensing (RS), crop growth model (CGM), and yield limiting factor (LF) were reviewed. RS, especially satellite-based RS, is crucial in potato yield prediction and decision support over large farm areas. In contrast, CGM are often utilized to optimize management measures and address climate change. Currently, combined with the advantages of low cost and easy operation, unmanned aerial vehicle (UAV) RS combined with artificial intelligence (AI) show superior potential for predicting potato yield in precision management of large-scale farms. However, studies on potato yield prediction are still limited in the number of varieties and field sample size. In the future, it is critical to employ time-series data from multiple sources for a wider range of varieties and large field sample sizes. This study aims to provide a comprehensive review of the progress in potato yield prediction studies and to provide a theoretical reference for related research on potato.

High temperatures delay tuberization and decrease potato (Solanum tuberosum L.) yields. However, the molecular mechanisms and regulatory networks underlying tuberization under high temperatures remain largely unknown. Here, we performed the mRNA and miRNA sequencing of leaves and stems to identify genes and regulatory networks involved in tuberization under high temperatures. A total of 2804 and 5001 differentially expressed genes (DEGs) under high-temperature stress were identified in leaves and stems, respectively. These genes were significantly enriched in gene ontology terms regarding meristem development, the sucrose biosynthetic process, and response to heat. Meanwhile, 101 and 75 differentially expressed miRNAs (DEmiRNAs) were identified in leaves and stems, respectively. We constructed an interaction network between DEmiRNAs and DEGs, identifying 118 and 150 DEmiRNA–DEG pairs in leaves and stems, respectively. We found three miRNA–mRNA candidate modules involved in tuberization under high temperatures, including stu-miR8030-5p/StCPY714, stu-miR7981f-p5/StAGL8a, and stu-miR10532A/StAGL8b. Our study constructed an interaction network between miRNAs and target genes and proposes candidate miRNA–gene modules that regulate tuber formation under high temperatures. Our study provides new insights for revealing the regulatory mechanism of the high-temperature inhibition of tuberization and also provides gene resources for improving the heat tolerance in potatoes.

Paleo-lacustrine sediments indicate that a mega-lake developed in the Hetao Basin (HTB), suggesting dramatic changes in the geomorphology and surface process of the Yellow River and surrounding regions. However, the formation time of the mega Hetao paleo-lake (HTPL) in the HTB remains unclear. In this study, a set of 7.6-m-thick lacustrine sediments in the middle of the HTB is dated by both quartz optically stimulated luminescence (OSL) and K-feldspar (KF) post-infrared infrared stimulated luminescence (p-IR IRSL, pIRIR). The results are as follows. 1) The quartz OSL ages do not increase with depth as the KF pIRIR ages displayed but are saturated at ca. 80–100 ka with the consequence of age underestimation. The influence of signal saturation may occur below 96 Gy (ca. 32 ka) in this region. Thus, the KF pIRIR ages are chosen for geomorphological evolution reconstruction. 2) These ages suggest the level of the HTPL exceeded 1033 m asl twice—at the early stages of MIS 7 (∼255–245 ka) and MIS 5 (∼130–120 ka). However, the exact scale of the HTPL and its relationship with the Jilantai paleo-lake is unclear. 3) This chronology suggests strong linkage between periodic formation of the HTPL and glacial-scale climatic change. We therefore propose an alternative hypothesis to interpret these processes: the Hobq dunefield expanded eastward to dam the narrow Jin-Shaan Gorge during the glacial periods when the flow of the Yellow River was weak. Then, in the beginning of the interglacial periods, the basin was filled by abruptly resumed runoff in response to increased glacial meltwater and precipitation on the northeastern Tibetan Plateau. Once the lake spilt out, the loose dune dam was quickly breached.

The application of the cast WC, the Co powder coated cast WC and the Ni powder coated cast WC particles in diamond saw blades were studied, and their effects on the mechanical properties, the micro morphologies and the cutting properties of the diamond saw blade matrix were explored. The results show that when the mass ratio of the three kinds of WC material to the metal powder is 3∶1, the hardness of the three kinds of matrix is equivalent. The bending strength of the matrix containing Co powder coated cast WC is the highest, the interface between the WC particles and the matrix is the closest, and the microstructure of the matrix is the densest. The bending strength of the matrix containing Ni powder coated cast WC is the second. The matrix with only cast WC has the worst bending strength. Compared with the saw blade with only cast WC added, the cutting life of the saw blade with Co powder coated cast WC is the longest and increases by 40%.

Abstract Nonfullerene acceptors (NFAs) lead the continuous development of organic solar cells (OSCs) with competitive efficiency over 19%. Design and synthesis of novel photovoltaic materials are effective methods to improve the OSCs performance, which can regulate the optoelectric properties, such as energy level, absorption spectra, charge transport, and so on. So far, hundreds of NFAs have been reported. Meanwhile, it has been demonstrated that intrinsic morphology of active layer is partially determined by the chemical structures of NFAs. Hence, only in‐depth understanding of the relationship between different structures of NFAs and morphology can guide the molecular design of NFAs for highly efficient OSCs. Herein, we review some state‐of‐the‐art NFAs according to their functional moieties, that is, arene core, end group and side chain, and discuss the relationship between molecular structure, morphology and device parameter. Additionally, the challenges and prospects for further development of OSCs based on NFAs are briefly considered. This review brings a unique insight into structure–function correlation in this field, which may help to rapidly develop efficient OSCs.

Four representative TS-RCR (three-soft rock-coal-rock) structural bodies were selected according to the lithofacies analysis of coal measures in the Xiangshui Coal Mine, Guizhou, China, to analyze the mechanical properties, internal structure damage characteristics, and crack evolution law of the TS-RCR structural body composed of a soft roof, a soft floor, and soft coal seams. The mechanical model of the TS-RCR structural body was proposed. (1) The stress-strain curves of TS-RCR structures with different lithologies under cyclic loading and unloading show a change rule of sparsity, density, and sparsity with the increased cycles. The deformation of TS-RCR structures under cyclic loading and unloading can be divided into four stages. When the height ratio of the TS-RCR structural body was the same, the higher the strength of the upper and lower rocks, the more cycles the TS-RCR structural body had, and the denser the cyclic loading and unloading curve. On the contrary, the fewer cycles the TS-RCR structural body had, the sparser the cyclic loading and unloading curve. (2) The T2 (transverse relaxation time) spectrum curves of the structural bodies were monitored at about 1 and 10 ms, and two obvious peaks were detected, indicating micropores and mesopores with a large volume in the structural body. Signal intensity increased at the relaxation time of 1 ms, decreased at 10–100 ms, and increased slightly at 100–1000 ms. The pore structure of the structural body with different lithologies changed significantly with the increased cycle number. (3) The damage and failure process of the structural body was roughly divided into three periods according to the time-history analysis of acoustic-emission AF (the ratio of acoustic-emission ringing count to duration) of the structural body: the active period with a relatively low AF value (AF

In this paper, the “sonar percolation detection or logging” technology, which has emerged recently, is questioned from the aspects of test principle and calculation method, and the serious problems of this technology are pointed out. It is considered that sonar technology can not be used for seepage testing.

Abstract We determined the antitumor mechanism of apatinib in glioma using a patient-derived orthotopic xenograft (PDOX) glioma mouse model and glioblastoma (GBM) cell lines. The PDOX mouse model was established using tumor tissues from two glioma patients via single-cell injections. Sixteen mice were successfully modeled and randomly divided into two equal groups (n = 8/group): apatinib and normal control. Survival analysis and in vivo imaging was performed to determine the effect of apatinib on glioma proliferation in vivo. Candidate genes in GBM cells that may be affected by apatinib treatment were screened using RNA-sequencing coupled with quantitative mass spectrometry, data mining of The Cancer Genome Atlas, and Chinese Glioma Genome Atlas databases, and immunohistochemistry analysis of clinical high-grade glioma pathology samples. Quantitative reverse transcription-polymerase chain reaction (qPCR), western blotting, and co-immunoprecipitation (co-IP) were performed to assess gene expression and the apatinib-mediated effect on glioma cell malignancy. Apatinib inhibited the proliferation and malignancy of glioma cells in vivo and in vitro. Thrombospondin 1 (THBS1) was identified as a potential target of apatinib that lead to inhibited glioma cell proliferation. Apatinib-mediated THBS1 downregulation in glioma cells was confirmed by qPCR and western blotting. Co-IP and mass spectrometry analysis revealed that THBS1 could interact with myosin heavy chain 9 (MYH9) in glioma cells. Simultaneous THBS1 overexpression and MYH9 knockdown suppressed glioma cell invasion and migration. These data suggest that apatinib targets THBS1 in glioma cells, potentially via MYH9, to inhibit glioma cell malignancy and may provide novel targets for glioma therapy.

Abstract Background This study evaluated the predictive value of gene signatures for biochemical recurrence (BCR) in primary prostate cancer (PCa) patients. Methods Clinical features and gene expression profiles of PCa patients were attained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets, which were further classified into a training set (n = 419), a validation set (n = 403). The least absolute shrinkage and selection operator Cox (LASSO‐Cox) method was used to select discriminative gene signatures in training set for biochemical recurrence‐free survival (BCRFS). Selected gene signatures established a risk score system. Univariate and multivariate analyses of prognostic factors about BCRFS were performed using the Cox proportional hazards regression models. A nomogram based on multivariate analysis was plotted to facilitate clinical application. Kyoto Encyclopedia of Gene and Genomes (KEGG) and Gene Ontology (GO) analyses were then executed for differentially expressed genes (DEGs). Results Notably, the risk score could significantly identify BCRFS by time‐dependent receiver operating characteristic (t‐ROC) curves in the training set (3‐year area under the curve (AUC) = 0.820, 5‐year AUC = 0.809) and the validation set (3‐year AUC = 0.723, 5‐year AUC = 0.733). Conclusions Clinically, the nomogram model, which incorporates Gleason score and the risk score, could effectively predict BCRFS and potentially be utilized as a useful tool for the screening of BCRFS in PCa.

BackgroundHeart failure (HF) with preserved ejection fraction (HFpEF) is a growing public health burden, with mortality and rehospitalization rates comparable to HF with reduced ejection fraction (HFrEF). The evidence for the clinical usefulness of soluble suppression of tumorigenicity 2 (sST2) in HFpEF is contradictory. Therefore, we conducted the following systematic review and meta-analysis to assess the diagnostic and prognostic value of serum sST2 in HFpEF.MethodsPubMed and Scopus were searched exhaustively from their inception until March 15, 2022. In diagnostic analysis, we compared the diagnostic value of serum sST2 in HFpEF to NT pro-BNP. We separately pooled the unadjusted and multivariate-adjusted hazard ratios (HRs) and the corresponding 95% confidence intervals (CIs) in prognostic analysis.ResultsA total of 16 publications from 2008 to 2021 were examined. The results of this analysis were as follow: Firstly, compared with NT pro-BNP, sST2 obtains poor diagnostic performance in independently identifying HFpEF from healthy controls, hypertensive patients, and HFrEF patient. Nevertheless, it may provide incremental value to other biomarkers for diagnosing HFpEF and deserves further investigation. Secondly, log sST2 was independently associated with adverse endpoints on multivariable analysis after adjusting for variables such as age, sex, race, and NYHA class. Per log unit rise in sST2, there was a 2.76-fold increased risk of all-cause death [HR:2.76; 95% CI (1.24, 6.16); p = 0.516, I2 = 0%; P = 0.013] and a 6.52-fold increased risk in the composite endpoint of all-cause death and HF hospitalization [HR:6.52; 95% CI (2.34, 18.19); p = 0.985, I2 = 0%; P = 0.000]. Finally, the optimal threshold levels of serum sST2 need further determined.ConclusionsHigher sST2 was strongly linked to an increased risk of adverse outcomes in HFpEE. Especially, log sST2 independently predicted all-cause death and the composite endpoint of all-cause death and HF hospitalization. However, prospective and multicenter studies with large-sample and extended follow-up periods are required to validate our results due to limitations in our research.

Abstract The molecular orientation has a profound influence on the performance of organic solar cells. Both donor and acceptor adopt face‐on orientation guarantees efficient exciton dissociation and charge transport, which is a key to achieving high device performance. However, the molecules usually adopt edge‐on orientation in some blend systems, take small molecules based on an oligothiophene (DRCN5T): fused‐ring electron acceptor based on indacenodithieno[3,2‐b]‐thiophene core and thienyl side‐chains (ITIC‐Th) blend, for instance, the orientation of DRCN5T is edge‐on, which is detrimental to the photophysical process of the device. Herein, a solid additive strategy, that is, adding N2200 as a nucleus for DRCN5T, was proposed, which combined the nucleation process with molecular diffusivity, thus realizing the orientation transformation of DRCN5T from edge‐on to face‐on. Consequently, the device performance was significantly improved, and a clear relationship between molecular orientation and energy loss/biomolecular recombination was established. More importantly, this study revealed not only the thermodynamic factors, including the crystallinity of solid additive, the lattice matching degree, and miscibility between DRCN5T and solid additive but also the kinetic parameter, such as the diffusivity of DRCN5T are very important to efficiently regulate the molecular orientation. Overall, this study presents the in‐depth mechanism of orientation transformation via adding solid additives, which may provide a guideline for solid additive choices.

Water and nitrogen are essential for potato growth and development. We aim to understand how potato adapts to changes in soil water and nitrogen content. Potato plant adaptations to changes in soil moisture and nitrogen levels were analyzed at the physiological and transcriptomic levels in four treatment groups: adequate nitrogen under drought, adequate nitrogen under sufficient irrigation, limited nitrogen under drought, and limited nitrogen under sufficient irrigation. Many light-capture pigment complex genes and oxygen release complex genes were differentially expressed in leaves when nitrogen levels were increased under drought conditions, and several genes encoding rate-limiting enzymes in the Calvin–Benson–Bassham cycle were up-regulated; furthermore, leaf stomatal conductance decreased, whereas the saturated vapor pressure difference and relative chlorophyll content in the chloroplasts increased. StSP6A, a key gene in potato tuber formation, was down-regulated in response to increased nitrogen application, and the stolon growth time was prolonged. Genes related to root nitrogen metabolism were highly expressed, and protein content in the tuber increased. Weighted gene co-expression network analysis (WGCNA) revealed 32 gene expression modules that responded to changes in water and nitrogen levels. A total of 34 key candidate genes were identified, and a preliminary molecular model of potato responses to alterations in soil water and nitrogen content was constructed.

Abstract The development of glioblastoma (GBM) is typically accompanied by marked changes in lipid metabolism. Oxylipins and their catalyzed enzymes lipoxygenases (LOXs) have been shown to participate in the development of cancers via multiple pathways, while the understanding of LOXs in GBM remains enigmatic. Thus, we aimed to explore the expression and functional roles of LOXs in the development of GBM. Here we showed that ALOXE3 was markedly down-regulated in human GBM. Knockdown of ALOXE3 in GBM cells fostered the orthotopic tumor growth and shortened lifespan in mice. ALOXE3 deficiency rendered GBM cells resistant to p53-SLC7A11 dependent ferroptosis, promoting GBM cell survival. Mechanistically, miR-18a directly targeted ALOXE3 and suppressed its expression and functions in GBM cells. Furthermore, ALOXE3 silencing promoted 12-hydroxyeicosatetraenoic acids (12-HETE) secretion from GBM cells, in turn, 12-HETE enhanced migration of GBM cells by activating Gs-protein-coupled receptor (GsPCR)-PI3K-Akt pathway in an autocrine manner. Altogether, miR-18a/ALOXE3 axis exerts tumor promoting functions by regulating ferroptosis and migration of GBM cells. Targeting miR-18a/ALOXE3 axis may provide novel therapeutic approaches for GBM treatment.

PurposeSalvia miltiorrhiza Bge. (Danshen, DS) and Ligusticum chuanxiong Hort. (Chuanxiong, CX) have been widely used in traditional Chinese medicine to prevent and treat myocardial ischemia and renal insufficiency, and their extracts (Guanxinning injection, GXN) have been reported to exhibit antioxidant, anti-inflammatory, and anti-ischemia-reperfusion injury properties. It is well-established that ischemic postconditioning (IPOC) can protect against myocardial ischemia-reperfusion (I/R) injury in rats with chronic renal failure (CRF). However, little is known on whether GXN combined with IPOC may affect myocardial I/R injury in CRF rats. We sought to observe the effect of GXN combined with IPOC on myocardial I/R injury in CRF rats by quantifying changes in the expression of proteins related to mitochondrial dynamics.Materials and MethodsIn a survey, 90 Wistar rats were randomly divided into 6 groups (15 rats per group): CRF group, I/R group, comorbid group (CRF + I/R), IPOC group, IPOC + GXN group and the sham group. Changes in blood myocardial injury markers, urea, and creatinine were analyzed. Heart tissues were harvested for histomorphometry and western blotting when rats were sacrificed. Myocardial infarction area was measured by Evans blue and Triphenyltetrazolium chloride solution staining. The expressions of mitochondrial fission relative proteins (DRP1 and FIS1) and mitochondrial fusion relative proteins (OPA1 and MFN1) were detected by western blotting.ResultsIPOC could significantly decrease myocardial injury markers and myocardial area of necrosis (AN)/area at risk (AAR) of the comorbid model rats. Further results showed that GXN combined with IPOC could significantly reduce CK-MB levels and myocardial AN/AAR in comorbid model rats compared with the IPOC group. Meanwhile, both IPOC and IPOC + GXN significantly reduced DRP1 levels and increased the MFN1 and OPA1 protein levels in the comorbid model rats. However, compared with the IPOC group, MFN1 and OPA1 protein levels increased significantly in the IPOC + GXN group.ConclusionExtracts of DS and CX combined with IPOC exert a protective effect against myocardial I/R injury in rats with CRF, mediated by increased expression of mitochondrial fusion proteins (MFN1 and OPA1).

ObjectiveThis study aims to detect the invisible metabolic abnormality in PET images of patients with anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis using a multivariate cross-classification method.MethodsParticipants were divided into two groups, namely, the training cohort and the testing cohort. The training cohort included 17 healthy participants and 17 patients with anti-LGI1 encephalitis whose metabolic abnormality was able to be visibly detected in both the medial temporal lobe and the basal ganglia in their PET images [completely detectable (CD) patients]. The testing cohort included another 16 healthy participants and 16 patients with anti-LGI1 encephalitis whose metabolic abnormality was not able to be visibly detected in the medial temporal lobe and the basal ganglia in their PET images [non-completely detectable (non-CD) patients]. Independent component analysis (ICA) was used to extract features and reduce dimensions. A logistic regression model was constructed to identify the non-CD patients.ResultsFor the testing cohort, the accuracy of classification was 90.63% with 13 out of 16 non-CD patients identified and all healthy participants distinguished from non-CD patients. The patterns of PET signal changes resulting from metabolic abnormalities related to anti-LGI1 encephalitis were similar for CD patients and non-CD patients.ConclusionThis study demonstrated that multivariate cross-classification combined with ICA could improve, to some degree, the detection of invisible abnormal metabolism in the PET images of patients with anti-LGI1 encephalitis. More importantly, the invisible metabolic abnormality in the PET images of non-CD patients showed patterns that were similar to those seen in CD patients.

BackgroundHeart failure with preserved ejection fraction (HFpEF) is an increasing public health concern. Currently, data regarding the clinical application value of plasma Galectin-3 (Gal-3) in HFpEF are contradictory. Therefore, we performed the following meta-analysis to appraise the clinical implications of serum Gal-3 in HFpEF, including its capacity to predict new-onset disease, long-term unfavorable endpoints, and the degree of cardiac structural abnormality and left ventricular diastolic dysfunction (LVDD).MethodsPubMed, Embase, Scopus, and Web of Science were retrieved exhaustively from their inception until November 30, 2021, to obtain studies assessing the correlation between plasma Gal-3 and the clinical features of HFpEF (new-onset HFpEF, adverse outcomes, and echocardiographic parameters related to abnormal cardiac structure and LVDD).ResultsA total of 24 papers containing 27 studies were ultimately included in the present research. The results of the meta-analysis revealed that high plasma Gal-3 levels are strongly associated with the following clinical characteristics of HFpEF: (i) the increased risk of new-onset HFpEF (HR: 1.11; 95% CI: 1.04-1.19; p = 0.910, I2 = 0%; P = 0.002); (ii) the high risk of adverse outcomes of HFpEF patients [all-cause death (HR: 1.55; 95% CI: 1.27-1.87; p = 0.138, I2 = 42%; P = 0.000) and the composite events [all-cause death and HF hospitalization (HR: 1.50; 95% CI: 1.30-1.74; p = 0.001, I2 = 61%; P = 0.000) or cardiovascular (CV) death and HF hospitalization (HR: 1.71; 95% CI: 1.51-1.94; p = 0.036, I2 = 58%; P = 0.000)]; (iii) echocardiographic indices [E/e ratio (r: 0.425, 95% CI: 0.184-0.617; p = 0.000, I2 = 93%; P = 0.001) and DT (r: 0.502, 95% CI: 0.061-0.779; p = 0.001 I2 = 91%; P = 0.027)].ConclusionsPlasma Gal-3 might be employed as an additional predictor for new-onset HFpEF, the adverse prognosis in HFpEF patients (all-cause death, the composite endpoints of all-cause death and HF hospitalization or CV death and HF hospitalization), and the severity of LVDD in HFpEF populations.

Summary: In all polymer solar cells (all-PSCs), the domain size is critical for device performance. In highly crystalline polymer blends, however, precisely adjusting the domain size remains a significant challenge because of the simultaneous crystallization of both components. Herein, a strategy that promotes acceptor and donor to crystallize separately was proposed. Take PBDB-T/N2200 blends for instance; the solution state and confined crystallization were combined, which induced the crystallization of N2200, and PBDB-T occurred during the film-forming process and at thermal annealing stage. This separated crystallization process lowers the driving force of phase separation without affecting the degree of crystallinity of the blends. Thus, an interpenetrating network with high crystallinity and proper domain size was obtained, which boosted the power conversion efficiency to 7.59%. Importantly, the relation between pre-aggregation and domain size was established, which may be a guide to precisely adjust the active layer’s domain size in all-PSCs.

Distant metastasis (DM) is the main cause of treatment failure in locally advanced rectal cancer. Here, the authors developed and validated a radiomic signature (RS) for prediction of DM within a multicenter dataset, and suggest that it may help with stratification of patients who might benefit from adjuvant chemotherapy for DM.

The electricity price is the sensitive signal of the supply–demand balance and some other market incidents. The analysis of the price data can provide plenty of the market information. It is helpful for the participants to understand the market and improve future strategies. However, most of the forecast models eliminate the details to reduce the structural risk for generality. In this paper, the data-driven analysis is proposed to explore the PJM electricity price in detail. The price time series is decomposed into different components. Each component is modeled and tested by the statistical method to illustrate the hidden pattern of the fluctuation, so that there can be reasonable interpretation about the market. The relationship between the price and the wind power is numerically detected through the heterogeneity of the price time series. The paper demonstrates the data-driven method to mine information and achieve the analysis of electricity market. Keywords: Electricity market, Real-time price, Time series, Heterogeneous volatility, Wind power

BackgroundConventional parameters show limited and unreliable correlations with medulloblastoma prognosis.AimTo evaluate the factors influencing overall survival (OS), event-free survival (EFS), and progression-free survival (PFS) in patients with medulloblastoma.MethodsPubMed, EMBASE, the Cochrane Library, and Web of Science were searched for studies published up to May 2021. The associations between various clinical and treatment factors and survival parameters were assessed.ResultsTwenty-nine studies (8455 patients) were included. Desmoplastic medulloblastoma (HR=0.41, 95%CI: 0.31-0.56), M0 disease (HR=2.07, 95%CI: 1.48-2.89), WNT, SSH, group 4 (all P

Support technology faces challenges in view of the large deformation of surrounding rock in three-soft coal roadways under high horizontal stress in Zijin Coal Mine, China. Geostress near the tested working face of the mine was measured and its distribution law was analyzed through theoretical analysis, numerical simulation analysis, and field measurement. The original supporting scheme of the three-soft coal roadway on the tested working face was analyzed to discover the deformation and failure mechanism of the surrounding rock of the original supporting roadway and the control measures. An optimized support scheme of H-G (hollow grouting) anchor cables, high strength bolts, W-shaped steel belts, metal meshes, and sprayed concretes was proposed for field applications. Based on the roadway in the tested 3201 working face at Zijin Coal Mine, the technical parameters for optimizing the combined support of the roadway were determined. The following results were be obtained through field measurement. The roadway was kept intact after excavation and the optimized support scheme was adopted in the three-soft coal roadway. No obvious deformation in appearance existed in the roof, floor, and roadway coal sides. Compared with the original support scheme, the stability of the roadways was improved visibly. The displacement of the roadway roof decreased from 100 to 30 mm, and that of the roadway coal walls decreased from more than 100 mm to less than 50 mm. This work verifies the effectiveness of a combined support scheme of H-G anchor cables, high strength bolts, W-shaped steel belts, metal meshes, and sprayed concretes to control deformations of surrounding rock in three-soft coal roadways. The new support scheme has good social and economic benefits and can be used as a reference for other roadway supports under similar conditions.

Objectives: Gait and balance disturbances are common symptoms of idiopathic normal pressure hydrocephalus (iNPH). This study aimed to quantitatively evaluate gait and balance parameters after external lumbar drainage (ELD) using APDM inertial sensors.Methods: Two-minute walkway tests were performed in 36 patients with suspected iNPH and 20 healthy controls. A total of 36 patients underwent ELD. According to clinical outcomes, 20 patients were defined as responders, and the other 16 as non-responders. The gait parameters were documented, and the corresponding differences between responders and non-responders were calculated.Results: When compared with healthy controls, patients with suspected iNPH exhibited decreased cadence, reduced gait speed, a higher percentage of double support, decreased elevation at mid-swing, reduced foot strike angle, shorter stride length, difficulty in turning, and impaired balance functions. After the ELD, all these manifestations, except elevation at mid-swing and balance functions, were significantly improved in responders. The change of Z-score absolute value in the six parameters, except for foot strike angle, was >1. No significant improvement was observed in non-responders.Conclusion: APDM inertial sensors are useful for the quantitative assessment of gait impairment in patients with iNPH, which may be a valuable tool for identifying candidates that are suitable for shunting operations.

Abstract Anti-EGFR antibodies are effective in therapies for late-stage colorectal cancer (CRC); however, many tumours are unresponsive or develop resistance. We performed genomic analysis of intrinsic and acquired resistance to anti-EGFR therapy in prospectively collected tumour samples from 25 CRC patients receiving cetuximab (an EGFR inhibitor). Of 25 CRC patients, 13 displayed intrinsic resistance to cetuximab; 12 were intrinsically sensitive. We obtained six re-biopsy samples at acquired resistance from the intrinsically sensitive patients. NCOA4–RET and LMNA–NTRK1 fusions and NRG1 and GNAS amplifications were found in intrinsic-resistant patients. In cetuximab-sensitive patients, we found KRAS K117N and A146T mutations in addition to BRAF V600E, AKT1 E17K, PIK3CA E542K, and FGFR1 or ERBB2 amplifications. The comparison between baseline and acquired-resistant tumours revealed an extreme shift in variant allele frequency of somatic variants, suggesting that cetuximab exposure dramatically selected for rare resistant subclones that were initially undetectable. There was also an increase in epithelial-to-mesenchymal transition at acquired resistance, with a reduction in the immune infiltrate. Furthermore, characterization of an acquired-resistant, patient-derived cell line showed that PI3K/mTOR inhibition could rescue cetuximab resistance. Thus, we uncovered novel genomic alterations that elucidate the mechanisms of sensitivity and resistance to anti-EGFR therapy in metastatic CRC patients.

Majority of type 2 diabetes mellitus (T2DM) patients are highly susceptible to several forms of cognitive impairments, particularly dementia. However, the underlying neural mechanism of these cognitive impairments remains unclear. We aimed to investigate the correlation between whole brain resting state functional connections (RSFCs) and the cognitive status in 95 patients with T2DM. We constructed an elastic net model to estimate the Montreal Cognitive Assessment (MoCA) scores, which served as an index of the cognitive status of the patients, and to select the RSFCs for further prediction. Subsequently, we utilized a machine learning technique to evaluate the discriminative ability of the connectivity pattern associated with the selected RSFCs. The estimated and chronological MoCA scores were significantly correlated with R = 0.81 and the mean absolute error (MAE) = 1.20. Additionally, cognitive impairments of patients with T2DM can be identified using the RSFC pattern with classification accuracy of 90.54% and the area under the receiver operating characteristic (ROC) curve (AUC) of 0.9737. This connectivity pattern not only included the connections between regions within the default mode network (DMN), but also the functional connectivity between the task-positive networks and the DMN, as well as those within the task-positive networks. The results suggest that an RSFC pattern could be regarded as a potential biomarker to identify the cognitive status of patients with T2DM. Keywords: Type 2 diabetes mellitus, Resting state functional connectivity, Elastic net, Support vector machines, MoCA

Abstract Background Crop emergence and canopy cover are important physiological traits for potato (Solanum tuberosum L.) cultivar evaluation and nutrients management. They play important roles in variety screening, field management and yield prediction. Traditional manual assessment of these traits is not only laborious but often subjective. Results In this study, semi-automated image analysis software was developed to estimate crop emergence from high-resolution RGB ortho-images captured from an unmanned aerial vehicle (UAV). Potato plant objects were extracted from bare soil using Excess Green Index and Otsu thresholding methods. Six morphological features were calculated from the images to be variables of a Random Forest classifier for estimating the number of potato plants at emergence stage. The outputs were then used to estimate crop emergence in three field experiments that were designed to investigate the effects of cultivars, levels of potassium (K) fertiliser input, and new compound fertilisers on potato growth. The results indicated that RGB UAV image analysis can accurately estimate potato crop emergence rate in comparison to manual assessment, with correlation coefficient ($$ r^{2} $$ r2 ) of 0.96 and provide an efficient tool to evaluate emergence uniformity. Conclusions The proposed UAV image analysis method is a promising tool for use as a high throughput phenotyping method for assessing potato crop development at emergence stage. It can also facilitate future studies on optimizing fertiliser management and improving emergence consistency.

Organic solar cells (OSCs) are a kind of device that can convert light energy into electrical energy, they possess the advantages of being lightweight, flexible, processable printing, and large-area production, and they are an effective way to alleviate energy deficiency and environmental pollution [...]

The surface of Bacillus megaterium was modified by coating sodium alginate. The modified B. megaterium before and after adsorption were characterized by SEM, FTIR and XPS. The effects of pH, reaction time, initial U(VI) concentration and adsorbent dosage on the adsorption of U(VI) by the modified B. megaterium were studied by batch adsorption experiments. The adsorption process was studied by pseudo-first-order kinetics and pseudo-second-order kinetic models, Langmuir and Freundlich isotherms. The results showed that the maximum adsorption capacity of U(VI) was 74.61 mg g−1 under the conditions of pH 5.0, adsorbent 0.2 g l−1, 30°C and initial U(VI) concentration of 15 mg l−1. The adsorption process accords with pseudo-first-order kinetics and Langmuir isotherm. The adsorption capacity of U(VI) by the modified B. megaterium was still higher than 80% after five times of desorption and reuse experiments. In conclusion, the sodium alginate modified B. megaterium was an ideal material for U(VI) biosorption.

Abstract Reliable monitoring of metabolites in biofluids is critical for diagnosis, treatment, and long‐term management of various diseases. Although widely used, existing enzymatic metabolite assays face challenges in clinical practice primarily due to the susceptibility of enzyme activity to external conditions and the low sensitivity of sensing strategies. Inspired by the micro/nanoscale confined catalytic environment in living cells, the coencapsulation of oxidoreductase and metal nanoparticles within the nanopores of macroporous silica foams to fabricate all‐in‐one bio‐nanoreactors is reported herein for use in surface‐enhanced Raman scattering (SERS)‐based metabolic assays. The enhancement of catalytical activity and stability of enzyme against high temperatures, long‐time storage or proteolytic agents are demonstrated. The nanoreactors recognize and catalyze oxidation of the metabolite, and provide ratiometric SERS response in the presence of the enzymatic by‐product H2O2, enabling sensitive metabolite quantification in a “sample in and answer out” manner. The nanoreactor makes any oxidoreductase‐responsible metabolite a candidate for quantitative SERS sensing, as shown for glucose and lactate. Glucose levels of patients with bacterial infection are accurately analyzed with only 20 µL of cerebrospinal fluids, indicating the potential application of the nanoreactor in vitro clinical testing.