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Abstract Baicalein is a natural flavonoid abundant in various foods and dietary plants, including Tuber aestivum and Oroxylum indicum. In this study, we investigated the role of baicalein in enhancing the insulin‐sensitizing effect of metformin in mice with prediabetes. Baicalein, when combined with 25% of normal‐dose metformin, achieved a diabetes‐reversion rate of 80%, which was 1.86‐fold that of normal‐dose metformin. Mechanistically, baicalein enhanced the insulin‐sensitizing effect of metformin on lipid metabolism by inhibiting de novo lipogenesis through the AMP‐activated protein kinase/SREBP‐1c/FASN pathway and by inducing fatty‐acid β‐oxidation through the upregulation of ACSL1, CPT1A, EHHADH, and acyl‐CoA dehydrogenases (ACADL/ACADM/ACADS). Meanwhile, baicalein enhanced the insulin‐sensitizing effect of metformin via the modulation of the gut microenvironment by enriching probiotics, especially Akkermansia by 53.4‐fold, depleting opportunistic pathogens, and strengthening the intestinal barrier. The improved gut microenvironment led to the alleviation of chronic endotoxemia, as evidenced by decreased levels of lipopolysaccharide and proinflammatory cytokines. Furthermore, baicalein enhanced the effect of metformin on decreasing the circulating level of branched‐chain amino acids (BCAAs), which further improved insulin sensitivity by normalizing the mTORC1/p70S6K/IRS1 signaling pathway and de novo lipogenesis. Moreover, the role of baicalein in enhancing the insulin‐sensitizing effect of metformin was verified by an oleic acid‐induced steatosis model and a BCAA‐induced insulin resistance model in hepatocytes. Our study laid a theoretical foundation for developing baicalein into a dietary supplement for diabetes prevention. The diverse mechanisms of food‐derived flavonoids can be applied in the development of dietary supplements to enhance the efficacy of oral hyperglycemic agents currently used in clinics.

Abstract Background Circulating tumor DNA (ctDNA) is a promising biomarker for predicting relapse in multiple solid cancers. However, the predictive value of ctDNA for disease recurrence remains indefinite in locoregional gastric cancer (GC). Here, we aimed to evaluate the predictive value of ctDNA in this context. Methods From 2016 to 2019, 100 patients with stage II/III resectable GC were recruited in this prospective cohort study (NCT02887612). Primary tumors were collected during surgical resection, and plasma samples were collected perioperatively and within 3 months after adjuvant chemotherapy (ACT). Somatic variants were captured via a targeted sequencing panel of 425 cancer‐related genes. The plasma was defined as ctDNA‐positive only if one or more variants detected in the plasma were presented in at least 2% of the primary tumors. Results Compared with ctDNA‐negative patients, patients with positive postoperative ctDNA had moderately higher risk of recurrence [hazard ratio (HR) = 2.74, 95% confidence interval (CI) = 1.37–5.48; P = 0.003], while patients with positive post‐ACT ctDNA showed remarkably higher risk (HR = 14.99, 95% CI = 3.08‐72.96; P < 0.001). Multivariate analyses indicated that both postoperative and post‐ACT ctDNA positivity were independent predictors of recurrence‐free survival (RFS). Moreover, post‐ACT ctDNA achieved better predictive performance (sensitivity, 77.8%; specificity, 90.6%) than both postoperative ctDNA and serial cancer antigen. A comprehensive model incorporating ctDNA for recurrence risk prediction showed a higher C‐index (0.78; 95% CI = 0.71–0.84) than the model without ctDNA (0.71; 95% CI = 0.64–0.79; P = 0.009). Conclusions Residual ctDNA after ACT effectively predicts high recurrence risk in stage II/III GC, and the combination of tissue‐based and circulating tumor features could achieve better risk prediction.

The 3D morphology of the joint surface significantly influences the shear behavior of the jointrock. Constant normal load (CNL) direct shear tests with different shear displacement were conducted to understand the shear stress changing with joint roughness and damage degree during shear. The rough joint specimens were prepared using 3D scanning and printing techniques, and shear tests with different normal stresses and shear displacements were performed. Four different parameters and the damaged area quantitatively described by the image binarization and box dimension were calculated and compared to study the roughness evolution of joint surfaces. The experimental results demonstrated that the roughness parameter and shear stress decrease and approach constant values with increasing shear displacement. A JRC degradation model was presented based on regression analyses to evaluate the JRC values of rock joints under various displacements to replace it in the JRC–JCS model. Additionally, a new postshear behavior modeling was proposed for rock joints based on surface degradation characteristics under various initial joint roughness coefficients (JRC0) and normal stress. The stress–displacement curves resulting from the proposed modified model work well in predicting the postpeak stress–displacement curve, which can prove the effectiveness of the postpeak shear behavior modeling.

Abstract Change detection (CD) is a fundamental problem that aims at detecting changed objects from two observations. Previous CNN‐based CD methods detect changes through multi‐scale deep convolutional features extracted from two images. However, we find that change always occurs in the ‘Query’ image for fixed cameras. This condition means that changes can be detected in advance from a single image with a coarse change. In this paper, we propose an efficient CD method to detect precise changes from the change image. First, a change image selector is designed to identify the image containing changes. Second, a coarse change prior map generator is proposed to generate coarse change prior to indicate the position of changes. Then, we introduce a simple multi‐scale CD module to refine the coarse change detection. As only one image is used in the multi‐scale CD module, our method is more efficient in training and testing than other compared methods. Numerous experiments have been conducted to analyse the effectiveness of the proposed method. Experimental results show that the proposed method achieves superior detection performance and higher speed than other compared CD methods.

Abstract Bruton’s tyrosine kinase (BTK), expressed in B cells and cells of innate immunity, including microglia, is an essential signaling element downstream of the B‐cell receptor and Fc‐receptors. Tolebrutinib (PRN2246, SAR442168) is a potent BTK inhibitor that covalently binds the kinase, resulting in durable inhibition with the potential to target inflammation in the periphery and central nervous system (CNS). Tolebrutinib crosses the blood‐brain barrier and potently inhibits BTK in microglial cells isolated from the CNS. A first‐in‐human randomized, double‐blind, placebo‐controlled study of tolebrutinib was conducted. The trial design consisted of five single ascending dose arms with oral administration of a single dose of 5, 15, 30, 60, and 120 mg (n = 6 per arm, n = 2 placebo), five multiple ascending dose arms with oral administration of 7.5, 15, 30, 60, and 90 mg (n = 8 per arm, n = 2 placebo) over 10 days, and one arm (n = 4) in which cerebral spinal fluid (CSF) exposure was measured 2 h after a single 120 mg dose. Tolebrutinib was well‐tolerated in the study and all treatment‐related treatment emergent adverse events were mild. Tolebrutinib was rapidly absorbed following oral administration with a rapid half‐life of ~ 2 h. Peripheral BTK occupancy was assessed at various timepoints by an enzyme‐linked immunosorbent assay‐based readout using an irreversible probe. Assessments demonstrated extensive and prolonged peripheral BTK occupancy at steady‐state with once daily doses as low as 7.5 mg. Further, CSF exposure was demonstrated 2 h after administration at 120 mg.

Abstract Change detection (CD) is a fundamental yet challenging problem, which aims at detecting changed object in two observations. Recent CD methods are designed based on the off‐the‐shelf semantic segmentation network architectures, which is not optimal for extracting and using change‐related features. In this paper, a novel CD network architecture is proposed, including change‐related feature extraction, cross feature enhancement, and multi‐level supervision. Absolute difference of the features of different convolutional layers is first computed from a Unet‐like network for two observations. The features are partitioned into high‐ and low‐level features according to their functionalities. Then the high‐ and low‐level features are recurrently refined by cross feature enhancement to increase the representational ability of the features. The network learns change‐related features with multi‐level supervisions. The final CD result can be obtained by fusing multiple predictions. Experimental results on three CD benchmark datasets indicate the superiority of the authors' method when compared with six state‐of‐the‐art deep learning‐based CD methods.

Background: Asthma is a heterogeneous disease with distinct prevalence and manifestation between sexes. This study was to identify sex-specific features of asthma via metabolomic analysis of sphingolipids. Methods: Forty-two asthma patients (27 women and 15 men) admitted to the Peking University Third Hospital from January 2015 to December 2015 were enrolled. Peripheral venous blood was collected for metabolomic analysis by targeted liquid chromatography-mass spectrometry. Sex hormones(estradiol, progesterone, testosterone, and androstenedione) and multiple inflammatory factors (periostin, leptin, IgE, IL-4, IL-5, IL-10, IL-13, IL-17A, and IFN-γ) were also assessed. The eosinophil percentage in induced sputum was also detected. All these data were applied to comparative analysis between sexes. Results: Testosterone was negatively related to periostin (ρ = −0.420, P = 0.009) and IL-5 (ρ = −0.540, P = 0.012), while estradiol was positively related to the blood eosinophil percentage (ρ = 0.384, P = 0.025). Among the eighteen species of sphingolipids detected in the 42 patients, five ceramide (Cer) species (Cer16:0, Cer:20:0, Cer22:0, Cer24:0, and Cer26:0) and one sphingomyelin (SM) species (SM38:0) were significantly higher in male than in female patients. Further investigation found that the correlation between Cer20:0 and IL-5 was positive in males (ρ = 0.943, P = 0.005) but negative in females (ρ = −0.561, P = 0.030). Conclusions: Testosterone was negatively correlated with eosinophil inflammatory factors, but estradiol was positively correlated. Male asthma patients had higher ceramide and sphingomyelin levels than female patients. Different sexes had opposite correlations with ceramide and IL-5, respectively, suggesting that therapeutic strategies targeting ceramide should be different between sexes.

Abstract Background Invasive micropapillary carcinoma (IMPC) is an uncommon subtype of breast cancer. Previous studies of this subtype demonstrated a higher propensity for lymph node metastases as compared with invasive ductal carcinoma (IDC). The purpose of the present study was to determine the clinical characteristics, outcomes, and propensity for lymph node metastasis of patients with IMPC of the breast recorded in the National Cancer Database (NCDB). Methods Records of patients with IMPC diagnosed between 2004 and 2014 were retrieved from the NCDB. Log-rank test was performed to evaluate associations of clinical characteristics with overall survival (OS). Cox proportional hazards model was used to determine variables associated with OS. Results Overall, 2660 patients with IMPC met the selection criteria; the 5-year OS rate was 87.5% and 24.9% of patients had nodal involvement at presentation. Patients with ≥ 4 positive lymph nodes had shorter OS than node-negative patients, whereas patients with 1–3 positive nodes had similar OS to node-negative patients. Age

Abstract Objectives Although the genomic landscape of small‐cell carcinoma of the oesophagus (SCCE) has been dissected, its transcriptome‐level aberration and immune microenvironment status are unknown. Methods Using ultra‐deep whole transcriptome sequencing, we analysed the expression profile of nine paired SCCE samples and compared the transcriptome with public transcriptomic data set of normal oesophageal mucosa and other cancer types. Based on the transcriptome data, the immune signatures were investigated. The genomic data of 55 SCCE samples were also applied for immune checkpoint blockade therapy (ICBT) biomarker evaluation including microsatellite instability (MSI) status, tumor mutation burden (TMB) and neoantigen burden (TNB). Also, we evaluated the CD8, CD68 and programmed death‐ligand 1 (PD‐L1) in 62 retrospective SCCE samples with IHC assay. Results Differential expression analysis revealed that the cell cycle, p53, and Wnt pathways are significantly deregulated in SCCE. Immune microenvironment analysis showed that high leucocyte infiltration and adaptive immune resistance did occur in certain individuals, while the majority showed a relatively suppressive immune status. Immune checkpoints such as CD276 and LAG‐3 were upregulated, and higher M2 macrophage infiltration in tumor tissues. Furthermore, normal tissues adjacent to the tumors of SCCE presented a more activated inflammatory status than tumor‐free healthy controls. These observations showed that ICBT might benefit SCCE patients. As the critical biomarker of ICBT, TMB of SCCE was 3.64 with the predictive objective response rate 13.2%, while the PD‐L1‐positive rate was 43%. Conclusions Our study systematically characterized the immune microenvironment in small‐cell carcinoma of the esophagus and provided evidence that several patients with SCCE may benefit from immune checkpoint blockade therapy.

Abstract The number of elderly patients with cancer is increasing. Medical comorbidities are more common in this population. Little is known regarding the prognostic relevance of comorbidities in elderly patients with nasopharyngeal carcinoma (NPC). Using the National Cancer Data Base (NCDB), we queried patients age >65 years diagnosed with NPC and treated with definitive radiation between 2004 and 2012 to examine the association between comorbidity and survival outcomes. Comorbidity was assessed with the Charlson Comorbidity Index (CCI). The influence of comorbidity on overall survival (OS) was evaluated. Cox proportional hazards model was used to study the impact of comorbidity on OS. A total of 1137 patients met the specified criteria. Median follow‐up was 61.2 months. Five‐year OS was 50.4%. Comorbidities were present in 22.4% of patients, with 17.6% of patients having a CCI score of 1% and 4.8% having a CCI score of ≥2. Patients with a CCI score of 0 had significantly higher 5‐year OS than patients with a CCI score of 1 or ≥2 (53.1% vs. 42.2% vs. 32.9%, P

In view of the drawback of most image inpainting algorithms by which texture was not prominent, an adaptive inpainting algorithm based on continued fractions was proposed in this paper. In order to restore every damaged point, the information of known pixel points around the damaged point was used to interpolate the intensity of the damaged point. The proposed method included two steps; firstly, Thiele’s rational interpolation combined with the mask image was used to interpolate adaptively the intensities of damaged points to get an initial repaired image, and then Newton-Thiele’s rational interpolation was used to refine the initial repaired image to get a final result. In order to show the superiority of the proposed algorithm, plenty of experiments were tested on damaged images. Subjective evaluation and objective evaluation were used to evaluate the quality of repaired images, and the objective evaluation was comparison of Peak Signal to Noise Ratios (PSNRs). The experimental results showed that the proposed algorithm had better visual effect and higher Peak Signal to Noise Ratio compared with the state-of-the-art methods.

We investigate the differential diagnostic value of tremor analysis of EMG on Parkinson’s disease (PD), essential tremor (ET), and enhanced physiological tremor (EPT). Clinical data from 25 patients with PD, 20 patients with ET, and 20 patients with EPT were collected. The tremor frequency and muscle contraction pattern of the resting, posture, and 500 g and 1000 g overload were recorded. The frequency of PD tremor was 4–6 Hz, and the frequency of ET was also in this range; the frequency of EPT is 6–12 hz having some overlap with PD. The muscle contraction patterns of the ET and EPT group were mainly synchronous contraction, and the muscle contraction mode of the PD group was mainly alternating contraction. Having tremor latency from rest to postural position and having changes in tremor amplitude after mental concentration in PD might distinguish ET. Tremor analysis of EMG was able to distinguish PD from ET and EPT by varying the tremor frequency and muscle contraction pattern. It can also differentiate between PD and ET by the latency and concentration effect and ET and EPT by weight load effect.

In order to discover the structure of local community more effectively, this paper puts forward a new local community detection algorithm based on minimal cluster. Most of the local community detection algorithms begin from one node. The agglomeration ability of a single node must be less than multiple nodes, so the beginning of the community extension of the algorithm in this paper is no longer from the initial node only but from a node cluster containing this initial node and nodes in the cluster are relatively densely connected with each other. The algorithm mainly includes two phases. First it detects the minimal cluster and then finds the local community extended from the minimal cluster. Experimental results show that the quality of the local community detected by our algorithm is much better than other algorithms no matter in real networks or in simulated networks.

For expanding the application scope of car-following, based on the basic idea of the noncontact interaction of the objects in physics, establish an attention field model to describe the driving behavior. Firstly, propose the time distance concept to describe the degree of driver perception to the front one-dimensional space and extend its application range to the two-dimensional space. Secondly, connect the point which has the same time distance to constitute the equipotential line of drivers’ attention field equipotent, and establish a model to describe it. Thirdly, define the effective range of the driver’s psychological field with the feature of the driver’s visual distance range increasing and the angle decreasing. Finally, design the calculation method to collect projection of the object in the psychological field scope and calculate the curve points to determine the object’s intensity of psychological field. Preliminarily build the driving behavior model and use the numerical simulation method to simulate the simple transport scenarios; initially verify the validity of the model.