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The advent of Network Function Virtualization (NFV) and Service Function Chains (SFCs) unleashes the power of dynamic creation of network services using Virtual Network Functions (VNFs). This is of great interest to network operators since poor service quality and resource wastage can potentially hurt their revenue in the long term. However, the study shows with a set of test-bed experiments that packet loss at certain positions (i.e., different VNFs) in an SFC can cause various degrees of resource wastage and performance degradation because of repeated upstream processing and transmission of retransmitted packets.To overcome this challenge, this study focuses on resource scheduling and deployment of SFCs while considering packet loss positions. This study developed a novel SFC packet dropping cost model and formulated an SFC scheduling problem that aims to minimize overall packet dropping cost as a Mixed-Integer Linear Programming (MILP) and proved that it is NP-hard. In this study, Palos is proposed as an efficient scheme in exploiting the functional characteristics of VNFs and their positions in SFCs for scheduling resources and deployment to optimize packet dropping cost. Extensive experiment results show that Palos can achieve up to 42.73% improvement on packet dropping cost and up to 33.03% reduction on average SFC latency when compared with two other state-of-the-art schemes.

Abstract Background The breeder rooster has played a pivotal role in poultry production by providing high-quality semen. Typically, fertility peaks between 30 and 40 weeks of age and then declines rapidly from 45 to 55 weeks of age. Research into improving fertility in aging roosters is essential to extend their productive life. While progress has been made, enhancing fertility in aging roosters remains a significant challenge. Methods To identify the genes related to promoting sperm remodeling in aged Houdan roosters, we combined changes in testis and semen quality with transcriptome sequencing (RNA-seq) to analyze the synchrony of semen quality and testis development. In this study, 350-day-old Houdan breeder roosters were selected for RNA-seq analysis in testis tissues from induced molting roosters (D group) and non-induced molting roosters (47DG group). All analyses of differentially expressed genes (DEGs) and functional enrichment were performed. Finally, we selected six DEGs to verify the accuracy of the sequencing by qPCR. Results Compared with the 47DG group, sperm motility (P

With the widespread integration of deep learning in intelligent transportation and various industrial sectors, target detection technology is gradually becoming one of the key research areas. Accurately detecting road vehicles and pedestrians is of great significance for the development of autonomous driving technology. Road object detection faces problems such as complex backgrounds, significant scale changes, and occlusion. To accurately identify traffic targets in complex environments, this paper proposes a road target detection algorithm based on the enhanced YOLOv5s. This algorithm introduces the weighted enhanced polarization self attention (WEPSA) self-attention mechanism, which uses spatial attention and channel attention to strengthen the important features extracted by the feature extraction network and suppress insignificant background information. In the neck network, we designed a weighted feature fusion network (CBiFPN) to enhance neck feature representation and enrich semantic information. This strategic feature fusion not only boosts the algorithm's adaptability to intricate scenes, but also contributes to its robust performance. Then, the bounding box regression loss function uses EIoU to accelerate model convergence and reduce losses. Finally, a large number of experiments have shown that the improved YOLOv5s algorithm achieves mAP@0.5 scores of 92.8% and 53.5% on the open-source datasets KITTI and Cityscapes. On the self-built dataset, the mAP@0.5 reaches 88.7%, which is 1.7%, 3.8%, and 3.3% higher than YOLOv5s, respectively, ensuring real-time performance while improving detection accuracy. In addition, compared to the latest YOLOv7 and YOLOv8, the improved YOLOv5 shows good overall performance on the open-source datasets.

Geographic traceability is crucial to global oil trade security. This study discusses the possibility of using multivariate statistical methods combined with multi-indicator analysis to identify samples of crude oil imports from five major countries to China. The physicochemical properties and trace elements of crude oil were detected by Petroleum product standards and inductively coupled plasma atomic emission spectrometry (ICP-AES). Eight indexes (moisture, density, sulfur content, acid value, organochlorine, carbon residual, V, and Ni) were analyzed. Principal component analysis (PCA), hierarchical clustering analysis (HCA), Orthogonal projections to lateen structures-discriminant analysis (OPLS-DA), and other multivariate data analysis methods were used to determine the geographical origin of crude oil samples. Satisfying results have been obtained using PCA to reduce the dimensions of the indicators of crude oil from different origins. It allows the reduction of 8 variables to 3 principal components and accounts for 80.06% of the total variance. The HCA shows five clusters corresponding to five sources of crude oil. This will help to improve the utilization rate of crude oil with different characteristics, improve the quality of crude oil trade, and ensure the high quality of crude oil trade. For the sample set used for modeling, the model's accuracy was 97.19% after OPLS-DA optimization. These results show that the combination of multi-index analysis and stoichiometry is an effective tool for identifying crude oil origin, which fills the technical gap in the rapid identification of crude oil origin.

Abstract Background Microvascular invasion (MVI) is an independent prognostic factor that is associated with early recurrence and poor survival after resection of hepatocellular carcinoma (HCC). However, the traditional pathology approach is relatively subjective, time‐consuming, and heterogeneous in the diagnosis of MVI. The aim of this study was to develop a deep‐learning model that could significantly improve the efficiency and accuracy of MVI diagnosis. Materials and Methods We collected H&E‐stained slides from 753 patients with HCC at the First Affiliated Hospital of Zhejiang University. An external validation set with 358 patients was selected from The Cancer Genome Atlas database. The deep‐learning model was trained by simulating the method used by pathologists to diagnose MVI. Model performance was evaluated with accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic curve. Results We successfully developed a MVI artificial intelligence diagnostic model (MVI‐AIDM) which achieved an accuracy of 94.25% in the independent external validation set. The MVI positive detection rate of MVI‐AIDM was significantly higher than the results of pathologists. Visualization results demonstrated the recognition of micro MVIs that were difficult to differentiate by the traditional pathology. Additionally, the model provided automatic quantification of the number of cancer cells and spatial information regarding MVI. Conclusions We developed a deep learning diagnostic model, which performed well and improved the efficiency and accuracy of MVI diagnosis. The model provided spatial information of MVI that was essential to accurately predict HCC recurrence after surgery.

Abstract Background Intramuscular fat (IMF) content is the major indicator for evaluating chicken meat quality due to its positive correlation with tenderness, juiciness, and flavor. An increasing number of studies are focusing on the functions of microRNAs (miRNAs) in intramuscular adipocyte differentiation. However, little is known about the association of miR-128-3p with intramuscular adipocyte differentiation. Our previous RNA-seq results indicated that miR-128-3p was differentially expressed at different periods in chicken intramuscular adipocytes, revealing a possible association with intramuscular adipogenesis. The purpose of this research was to investigate the biological functions and regulatory mechanism of miR-128-3p in chicken intramuscular adipogenesis. Results The results of a series of assays confirmed that miR-128-3p could promote the proliferation and inhibit the differentiation of intramuscular adipocytes. A total of 223 and 1,050 differentially expressed genes (DEGs) were identified in the mimic treatment group and inhibitor treatment group, respectively, compared with the control group. Functional enrichment analysis revealed that the DEGs were involved in lipid metabolism-related pathways, such as the MAPK and TGF-β signaling pathways. Furthermore, target gene prediction analysis showed that miR-128-3p can target many of the DEGs, such as FDPS, GGT5, TMEM37, and ASL2. The luciferase assay results showed that miR-128-3p targeted the 3’ UTR of FDPS. The results of subsequent functional assays demonstrated that miR-128-3p acted as an inhibitor of intramuscular adipocyte differentiation by targeting FDPS. Conclusion miR-128-3p inhibits chicken intramuscular adipocyte differentiation by downregulating FDPS. Our findings provide a theoretical basis for the study of lipid metabolism and reveal a potential target for molecular breeding to improve meat quality.

Abstract According to the 7th National Population Census, China is experiencing rapid growth of its ageing population, with large spatial disparities in the distribution of older folks in different regions. And yet, scant comparative research has been conducted on the two regions of Zhejiang and Jilin in particular, which differ considerably in economic development but witness nearly the same ageing trend. In response, this article compares Zhejiang, an advanced economic province, with Jilin, with its relatively low level of economic development, to explore the ageing issue and analyse the spatial correlation between older populations and socioeconomic factors. Using the spatiotemporal data analysis and geographical detector approaches, we obtain three significant findings: 1. both provinces have maintained steady rates of increase in ageing; 2. the older populations in Zhejiang and Jilin are mostly concentrated in the provincial capitals and nearby cities with reasonably established economies; and 3. the factors, including local fiscal expenditures, beds in hospitals and nursing homes, and coverage of social security, show a highly similar spatial pattern between older populations in Zhejiang and Jilin. The q-values of all the selected socioeconomic factors in Jilin showed a growth trend, indicating that the spatial correlation between these factors and ageing is strengthening year on year, that is, the resources gained from the socioeconomic development of Jilin have shifted steadily toward old-age services. As a consequence, a vicious circle of the slowing down of the economic growth drives away working forces and quickens the pace of population ageing, is present. From a policy perspective, Jilin province is strongly dependent on state-owned enterprises characterised by institutional rigidity, an inflexible market economy and an under-developed private sector, all of which are profoundly influenced by ageing. The consequence is large population outflows of young people. In contrast, the economy of Zhejiang province is partially decoupled from the ageing trend, so the gap in level of development between its counties has been narrowing. The policy implication here is that Zhejiang represents an active private economy that has coped successfully with ageing by attracting young migrants and developing new forms of development, such as the digital economy.

ABSTRACT: The “Yufen 1” H line chicken (YF) has excellent characteristics including early sexual maturity and high egg production, and the conservation of its genetic diversity is the core of the breeding activity. To overcome misrepresented breeds and protect the integrity of the germplasm genetic resources, it is important to develop accurate and convenient methods to identify YF. In this study, whole genome resequencing was performed on the YF population, and bioinformatics analysis was conducted by combining the data from different breeds. Linkage disequilibrium (LD) analysis revealed that YF had the slowest LD-decay rate, suggesting strong natural and artificial selection in its history. Through selective sweep analysis, 1,126 selected regions in YF were identified, which contained 163,661 single nucleotide polymorphisms (SNPs). In particular, 5 specific SNPs (SNP1: Chr2:45509616, SNP2: Chr2:45510792, SNP3: Chr9:13788193, SNP4: Chr9:13795646, SNP5: Chr9:13798154) were found exclusively in the YF population. Subsequently, PCR amplification and Sanger sequencing confirmed the presence of these 5 SNPs in YF. Finally, 4 SNPs (SNP1, SNP2, SNP4, SNP5) were screened and verified using the Kompetitive Allele Specific PCR (KASP) typing technique. These SNPs can be used as specific molecular identity cards (IDs) for YF authentication. The present study is of great significance to ensure sustainable conservation and promotion of YF germplasm resources.

ABSTRACT: The reproductive performance of breeder roosters has significant economic importance in the poultry industry. Breeder roosters have severely reduced semen quality with age and will be at risk of culling in the following years. In order to extend the use of breeder roosters, we drew on the induced molting model of hens and selected 35 Houdan roosters aged 50 wk for induced molting. By comparing the body weight, testicular weight, semen quality, and reproductive performance before and after induced molting, we found that induced molting could restore the body weight and testicular weight to the levels before molting (P > 0.05). At the same time, it significantly improved sperm motility (P < 0.05) and also improved reproductive performance such as fertilization rate and hatching rate. To further reveal the mechanism underlying the effects of induced molting on semen quality and reproductive performance in aged Houdan roosters, we collected testes from 3 periods: 1 d before fasting (F0), 15 d after fasting (F15), and 32 d after recovery feeding (R32) for transcriptome sequencing analysis. A total of 5,671 genes were detected in F0, F15, and R32, and trend analysis of the 5,671 differential genes showed 2 significant trends (profile 5 and profile 2). KEGG enrichment analysis of the genes in the 2 profiles, revealed significantly enriched pathway regulation of actin cytoskeleton. In the regulation of actin cytoskeleton pathway, we found a protein kinase gene (SRC) and a senescence gene (ROCK2). SRC was highly expressed at F15, leading to the phosphorylation of key substrates, which in turn disrupted the Sertoli cell spermatid connection and the spermiogenesis process, resulting in no mature spermatozoa produced from F15, SRC expression was inhibited at R32, the expression level was reduced, and mature spermatozoa reappeared. The senescence gene ROCK2 was highly expressed at F15 compared to F0 and R32, which may have been responsible for inducing senescence atrophy in the testes.

Abstract Background Preoperative prediction of pancreatic cystic neoplasm (PCN) differentiation has significant value for the implementation of personalized diagnosis and treatment plans. This study aimed to build radiomics deep learning (DL) models using computed tomography (CT) data for the preoperative differential diagnosis of common cystic tumors of the pancreas. Methods Clinical and CT data of 193 patients with PCN were collected for this study. Among these patients, 99 were pathologically diagnosed with pancreatic serous cystadenoma (SCA), 55 were diagnosed with mucinous cystadenoma (MCA) and 39 were diagnosed with intraductal papillary mucinous neoplasm (IPMN). The regions of interest (ROIs) were obtained based on manual image segmentation of CT slices. The radiomics and radiomics-DL models were constructed using support vector machines (SVMs). Moreover, based on the fusion of clinical and radiological features, the best combined feature set was obtained according to the Akaike information criterion (AIC) analysis. Then the fused model was constructed using logistic regression. Results For the SCA differential diagnosis, the fused model performed the best and obtained an average area under the curve (AUC) of 0.916. It had a best feature set including position, polycystic features (≥6), cystic wall calcification, pancreatic duct dilatation and radiomics-DL score. For the MCA and IPMN differential diagnosis, the fused model with AUC of 0.973 had a best feature set including age, communication with the pancreatic duct and radiomics score. Conclusions The radiomics, radiomics-DL and fused models based on CT images have a favorable differential diagnostic performance for SCA, MCA and IPMN. These findings may be beneficial for the exploration of individualized management strategies.

Summary: Background: In preclinical models of Type 1 Diabetes (T1D) the integrity of the gut barrier (GB) is instrumental to avoid dysregulated crosstalk between the commensal microbiota and immune cells and to prevent autoimmunity. The GB is composed of the intestinal epithelial barrier (IEB) and of the mucus layer containing mucins and antimicrobial peptides (AMPs) that are crucial to maintain immune tolerance. In preclinical models of T1D the alterations of the GB primarily affect the mucus layer. In human T1D increased gut permeability and IEB damage have been demonstrated but the integrity of the mucus layer was never assessed. Methods: We evaluated GB integrity by measuring serological markers of IEB damage (serological levels of zonulin) and bacterial translocation such as lipopolysaccharide binding protein (LBP) and myeloid differentiation protein 2 (MD2), and mRNA expression of tight junction proteins, mucins and AMPs in intestinal tissue of T1D patients and healthy controls (HC). Simultaneously, we performed immunological profiling on intestinal tissue and 16S rRNA analysis on the mucus-associated gut microbiota (MAGM). Findings: Our data show a GB damage with mucus layer alterations and reduced mRNA expression of several mucins (MUC2, MUC12, MUC13, MUC15, MUC20, MUC21) and AMPs (HD4 and HD5) in T1D patients. Mucus layer alterations correlated with reduced relative abundance of short chain fatty acids (SCFA)-producing bacteria such as Bifidobacterium dentium, Clostridium butyricum and Roseburia intestinalis that regulate mucin expression and intestinal immune homeostasis. In T1D patients we also found intestinal immune dysregulation with higher percentages of effector T cells such as T helper (Th) 1, Th17 and TNF-α+ T cells. Interpretation: Our data show that mucus layer alterations are present in T1D subjects and associated with dysbiosis and immune dysregulation. Funding: Research Grants from the Juvenile Diabetes Foundation (Grant 1-INO-2018-640-A-N to MF and 2-SRA-2019-680-S-B to JD) and from the Italian Ministry of Health (Grant RF19-12370721 to MF).

Purpose: Primary hepatic sarcomatoid carcinoma (PHSC) is a rare type of malignant tumor in the liver. Nevertheless, few studies have focused on the imaging diagnosis of PHSC. In this study, we collected clinical and computed tomography (CT) imaging data of PHSC from two institutions, aiming to investigate the clinical and radiological characteristics of PHSC. Methods: We retrospectively investigated the clinical characteristics and CT features of 22 PHSC patients (19 males and 3 females; mean age, 63.4 years; range, 49 to 76 years), 95 hepatocellular carcinoma (HCC) patients and 50 intrahepatic cholangiocarcinoma (ICC) patients. Two radiologists independently evaluated the CT features of the three groups. Subsequently, we analyzed the differences in the clinical characteristics and CT features between the PHSC and control groups. Results: Most PHSCs were larger than 5 cm (72.7%). PHSC mainly showed irregular (81.8%), heterogeneous (100%) masses with ill-defined (72.7%) borders with necrosis (86.4%) on CT, which are more common CT features versus HCC (p

Abstract Multidrug resistance is one of the major public health issues the world is facing today. However, the World Health Organization (WHO) revealed recently that there has been little progress in the development of new antibiotics to tackle drug‐resistant infections. By mining the bacterial genome database, Zhu et al, in the last issue of EMBO Molecular Medicine, report a defensin expressed by human oral actinomyces, actinomycesin, and characterize its anti‐infectious capacity (Zhu et al, 2021). They demonstrate the safety and efficacy of this bacterial antimicrobial peptide (AMP) against various bacterial strains, describe its mode of action, and validate its use as systemic drug therapy against bacterial infections in mice. This study highlights human oral bacteria as a source of antimicrobial agents that need to be considered in the future to fight multidrug‐resistant bacteria.

BackgroundMental health has become a major public health issue worldwide. Biological and epidemiological studies have suggested that diet and physical fitness play a role in the prevention or cure of mental disorders. However, further research is required to elucidate the relationship between diet, physical fitness, and mental health. The study aims to provide a theoretical basis for promoting an adolescent healthy lifestyle and preventing mental problems by exploring the relationship between physical fitness, calcium intake, calorie intake, and adolescent mental health.MethodsA cross-sectional study of a sample of adolescents (N = 253, 12–13 years) was conducted. The study involved adolescents from three middle schools in Central Jiangsu Province, including 136 boys and 117 girls. Weight, height, and body mass index were measured. Physical fitness was scored using the Chinese National Student Physical Fitness Standard. Diet data were collected using a weighed 7-day food diary to estimate energy intake and dietary calcium intake. The mental health status of the participants was assessed using the Chinese Middle School Student Mental Health Scale. A T-test and analysis of variance were used to analyze the differences of variables between different genders and body mass index, and Pearson correlation and stepwise multiple regression were used to explore the relationship between physical fitness, dietary intake, and mental health.ResultsThe height (165.13 ± 8.07), weight (55.24 ± 13.00), and strength quality (64.93 ± 21.66) of boys are higher than those of girls (161.67 ± 6.44,48.99 ± 8.97, 58.40 ± 23.75, P < 0.05), and the flexibility quality (74.59 ± 14.75) of girls is higher than that of boys (68.30 ± 20.84) (P < 0.05). There were significant differences in the total scores of speed and physical fitness (F values were 4.02187.73, 3.07, 5.95, 10.33, and 9.52, respectively, P < 0.05). There was a significant positive correlation between calcium intake, cardiopulmonary fitness, and mental health (r = 0.276, P < 0.01; r = 0.159, P < 0.05). Calcium intake and cardiopulmonary fitness could explain 8.4% of the changes in the mental health of adolescents aged 12–13(ΔR2 = 0.084, P < 0.05).ConclusionAdequate calcium intake and the improvement of cardiopulmonary fitness in adolescents aged 12–13 are essential for the good development of their mental health. Future research in this field should examine the prospective associations between multiple measures of physical fitness composition and other nutrients ingested and mental health outcomes, as well as intervention studies that seek to provide evidence of causality.

The Kondo effect can serve as a powerful paradigm to understand strongly correlated many-body processes in physics. Here, Guo et al. utilize single molecule transistor devices as a testbed to study multi-level Kondo correlation and show electrical gate evolution and the universality of the two-stage Kondo effect.

Herein, the novel sodium ion hybrid capacitors (SIHCs) are successfully and facilely fabricated by utilizing the same carbon resource of magnesium citrate. Namely, the carbons which are fabricated by immediate carbonizations of magnesium citrate are used as positive electrodes, and N, S-doped carbons prepared by co-carbonizations of magnesium citrate with ammonium persulfate are determined as negative electrodes. The detailed electrochemical evaluations demonstrate that fabricated SIHCs possess tremendous Na+ storage performance. For instance, the fabricated SIHC(1//1) shows an energy density of 100.8 Wh Kg−1 at a power density of 136.8 W Kg−1, when current density was 0.1 A g−1. Furthermore, when the current density was set at 5.0 A g−1, this SIHC(1//1) also exhibits a power density of 12957.6 W Kg−1 at an energy density of 46.9 Wh Kg−1. These results reveal that SIHC(1//1) has the powerful competitiveness in high energy and power-required electricity storage applications.

This work aims to address the P-bifurcation of a stochastic nonlinear system with fractional damping driven by Gaussian white noise. Based on a stochastic averaging method, a fractional damping stochastic nonlinear equation has been studied. Furthermore, the expressions of drift and diffusion coefficients of the Fokker–Planck equation (FPKE) have been obtained. The probability density function (PDF), the steady solution of FPKE, has also been derived. Then, PDFs of two fractional damping Morse oscillators have been obtained. One can note that the analytical results coincide with the results of numerical simulation. Importantly, stochastic P-bifurcation of a fractional damping stochastic nonlinear Morse oscillator has been further addressed and analyzed.

The effective protection and utilization of poultry resources depend on an accurate understanding of the genetic diversity and population structure. The breeding of the specialized poultry lineage “Yufen 1”, with its defined characteristics, was approved by the China Poultry Genetic Resource Committee in 2015. Thus, to investigate the relationship between the progenitor H line and other poultry breeds, the genetic diversity and population structure of “Yufen 1” H line (YF) were investigated and compared with those of 2 commercial chicken breeds, the ancestor breed Red Jungle Fowls, and 11 Chinese indigenous chicken breeds based on a whole-genome resequencing approach using 8,112,424 SNPs. The genetic diversity of YF was low, and the rate of linkage disequilibrium decay was significantly slower than that of the other Chinese indigenous breeds. In addition, it was shown that the YF population was strongly selected during intensive breeding and that genetic resources have been seriously threatened, which highlights the need to establish a systematic conservation strategy as well as utilization techniques to maintain genetic diversity within YF. Moreover, a principal component analysis, a neighbor-joining tree analysis, a structure analysis, and genetic differentiation indices indicated that YF harbors a distinctive genetic resource with a unique genetic structure separate from that of Chinese indigenous breeds at the genome level. The findings provide a valuable resource and the theoretical basis for the further conservation and utilization of YF.

Objective This study aimed to investigate the strength of a novel micro‐dynamic pedicle screw by comparing it to the traditional pedicle screw. Methods Forty‐five lumbar vertebrae received a traditional pedicle screw on one side and a micro‐dynamic pedicle screw on the other side as follows (traditional group vs micro‐dynamic group): 15 vertebrae underwent instant pull‐out testing; 15 vertebrae underwent 5000‐cyclic fatigue loading testing; and 15 vertebrae underwent 10,000‐cyclic fatigue loading testing and micro‐computed tomography (micro‐CT) scanning. The peek pull‐out force and normalized peek pull‐out force after instant pull‐out testing, 5000‐cyclic and 10,000‐cyclic fatigue loading testing were recorded to estimate the resistance of two types of screws. Bone mineral density was recorded to investigate the strength of the different screws in osteoporotic patients. And the semidiameter of the screw insertion area on micro‐CT images after fatigue were compared to describe the performance between screw and bone surface. Results The bone mineral density showed a weak correlation with peek pull‐out force (r = 0.252, P = 0.024). The peek pull‐out force of traditional pedicle screw after 10,000‐cyclic fatigue loading were smaller than that of instant pull‐out test in both osteoporotic (P = 0.017) and healthy group (P = 0.029), the peek pull‐out force of micro‐dynamic pedicle screw after 10,000‐cyclic fatigue loading was smaller than that in instant pull‐out test in osteoporotic group (P = 0.033), but no significant difference in healthy group (P = 0.853). The peek pull‐out force in traditional group and micro‐dynamic group underwent instant pull‐out testing (P = 0.485), and pull‐out testing after 5000‐cyclic fatigue loading testing (P = 0.184) did not show significant difference. However, the peek pull‐out force in micro‐dynamic group underwent pull‐test after 10,000‐cyclic fatigue loading testing was significantly greater than that measured in traditional group (P = 0.005). The normalized peek pull‐out force of traditional groups underwent instant pull‐out testing, pull‐out test after 5000‐cyclic and 10,000‐cyclic fatigue loading testing significantly decreased as the number of cycles increased (P

BackgroundAn accurate pathological diagnosis of hepatocellular carcinoma (HCC), one of the malignant tumors with the highest mortality rate, is time-consuming and heavily reliant on the experience of a pathologist. In this report, we proposed a deep learning model that required minimal noise reduction or manual annotation by an experienced pathologist for HCC diagnosis and classification.MethodsWe collected a whole-slide image of hematoxylin and eosin-stained pathological slides from 592 HCC patients at the First Affiliated Hospital, College of Medicine, Zhejiang University between 2015 and 2020. We propose a noise-specific deep learning model. The model was trained initially with 137 cases cropped into multiple-scaled datasets. Patch screening and dynamic label smoothing strategies are adopted to handle the histopathological liver image with noise annotation from the perspective of input and output. The model was then tested in an independent cohort of 455 cases with comparable tumor types and differentiations.ResultsExhaustive experiments demonstrated that our two-step method achieved 87.81% pixel-level accuracy and 98.77% slide-level accuracy in the test dataset. Furthermore, the generalization performance of our model was also verified using The Cancer Genome Atlas dataset, which contains 157 HCC pathological slides, and achieved an accuracy of 87.90%.ConclusionsThe noise-specific histopathological classification model of HCC based on deep learning is effective for the dataset with noisy annotation, and it significantly improved the pixel-level accuracy of the regular convolutional neural network (CNN) model. Moreover, the model also has an advantage in detecting well-differentiated HCC and microvascular invasion.

BackgroundOur aim was to establish a deep learning radiomics method to preoperatively evaluate regional lymph node (LN) staging for hilar cholangiocarcinoma (HC) patients. Methods and MaterialsOf the 179 enrolled HC patients, 90 were pathologically diagnosed with lymph node metastasis. Quantitative radiomic features and deep learning features were extracted. An LN metastasis status classifier was developed through integrating support vector machine, high-performance deep learning radiomics signature, and three clinical characteristics. An LN metastasis stratification classifier (N1 vs. N2) was also proposed with subgroup analysis.ResultsThe average areas under the receiver operating characteristic curve (AUCs) of the LN metastasis status classifier reached 0.866 in the training cohort and 0.870 in the external test cohorts. Meanwhile, the LN metastasis stratification classifier performed well in predicting the risk of LN metastasis, with an average AUC of 0.946.ConclusionsTwo classifiers derived from computed tomography images performed well in predicting LN staging in HC and will be reliable evaluation tools to improve decision-making.

IntroductionHepatic sarcomatoid carcinoma (HSC) is a rare type of liver cancer with a high malignant grade and poor prognosis. This study compared the clinical characteristics and magnetic resonance imaging (MRI) features of HSCs with those of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), aiming to identify valuable features for HSC diagnosis.MethodsIn total, 17 pathologically confirmed HSC cases, 50 HCC cases and 50 common ICC cases were enrolled from two hospitals. The clinical characteristics and MRI features of all cases were summarized and statistically analyzed.ResultsOn the one hand, the incidence rates of elevated carbohydrate antigen (CA) 19-9 and elevated carcinoembryonic antigen (CEA) were significantly higher in the HSC cases than in the HCC cases (29.4% vs. 0%; 17.6% vs. 0%). The HSC enhancement patterns, primarily including progressive enhancement, were also significantly different from HCC cases. The incidence rates of heterogeneous signals on T2-weighted imaging and during the arterial phase were significantly higher in the HSC cases than in the HCC cases (94.1% vs. 66.0%; 100.0% vs. 72.0%). The diameter of HSCs was significantly larger than that in the HCC cases (6.12 cm vs. 4.21 cm), and the incidence rates of adjacent cholangiectasis, intrahepatic metastasis and lymph node enlargement were considerably higher in the HSC cases than in the HCC cases (52.9% vs. 6.0%; 47.1% vs. 12.0%; 41.2% vs. 2.0%). On the other hand, the incidence rate of elevated CA199 was significantly lower in the HSC cases than in the ICC cases (29.4% vs. 60.0%). The incidence rates of intratumoral necrosis and pseudocapsules were significantly higher in the HSC cases than in the HCC cases (35.3% vs. 8.0%; 47.1% vs. 12.0%). However, the incidence rates of target signs were significantly lower in the HSC cases than in the HCC cases (11.8% vs. 42.0%). In addition, there was no significant difference in the enhancement patterns between HSC cases and ICC cases.ConclusionsHSCs were frequently seen in elderly men with clinical symptoms and elevated CA199 levels. The MRI features, including large size, obvious heterogeneity, hemorrhage, progressive enhancement, pseudocapsule and lymph node enlargement, contributed to the diagnosis of HSC.

The study of isolated atoms or molecules inside a fullerene cavity provides a unique environment. It is likely to control the outer carbon cage and study the isolated species when molecules or atoms are trapped inside a fullerene. We report the Diels–Alder addition reaction of 9,10-dimethyl anthracene (DMA) to H2@C60 while 1H NMR spectroscopy is utilized to characterize the Diels–Alder reaction of the DMA with the fullerene. Through 1H NMR spectroscopy, a series of isomeric adducts are identified. The obtained peaks are sharp, precise, and straightforward. Moreover, in this paper, H2@C60 and its isomers are described for the first time.

As an endophytic fungus, the growth-promoting effects of Piriformospora indica have been widely confirmed in many of its host plants. In this study, we investigated the influences of P. indica colonization on the growth of the daughter plants of two strawberry cultivars, ‘Benihoppe’ and ‘Sweet Charlie.’ The results showed that the fungus colonization significantly promoted the growth of the daughter plants of both of the two strawberry varieties. Its colonization greatly improved almost all of the growth parameters of the ‘Benihoppe’ daughter plants, including the above-ground fresh weight, above-ground dry weight, root fresh weight, root dry weight, plant height, petiole length, leaf area, number of roots and chlorophyll content. However, the fungus colonization showed significant improving effects on only the above-ground fresh weight, root fresh weight and root dry weight of ‘Sweet Charlie.’ Surprisingly, the average root length of ‘Benihoppe’ and ‘Sweet Charlie’ was suppressed by about 14.3% and 24.6%, respectively, by P. indica. Moreover, after P. indica colonization, the leaf nitrate reductase activity and root activity upregulated by 30.12% and 12.74%, and 21.85% and 21.16%, respectively, for the ‘Benihoppe’ and ‘Sweet Charlie’ daughter plants. Our study indicated that P. indica could promote the growth of strawberry daughter plants by improving rooting, strengthening photosynthetic pigments production and nutrient absorption and accelerating biomass accumulation. The fungus shows great potential to be used in the strawberry industry, especially in the breeding of daughter plants.

Background: We conduct a study in developing and validating two radiomics-based models to preoperatively distinguish hepatic epithelioid angiomyolipoma (HEAML) from hepatic carcinoma (HCC) as well as focal nodular hyperplasia (FNH).Methods: Totally, preoperative contrast-enhanced computed tomography (CT) data of 170 patients and preoperative contrast-enhanced magnetic resonance imaging (MRI) data of 137 patients were enrolled in this study. Quantitative texture features and wavelet features were extracted from the regions of interest (ROIs) of each patient imaging data. Then two radiomics signatures were constructed based on CT and MRI radiomics features, respectively, using the random forest (RF) algorithm. By integrating radiomics signatures with clinical characteristics, two radiomics-based fusion models were established through multivariate linear regression and 10-fold cross-validation. Finally, two diagnostic nomograms were built to facilitate the clinical application of the fusion models.Results: The radiomics signatures based on the RF algorithm achieved the optimal predictive performance in both CT and MRI data. The area under the receiver operating characteristic curves (AUCs) reached 0.996, 0.879, 0.999, and 0.925 for the training as well as test cohort from CT and MRI data, respectively. Then, two fusion models simultaneously integrated clinical characteristics achieved average AUCs of 0.966 (CT data) and 0.971 (MRI data) with 10-fold cross-validation. Through decision curve analysis, the fusion models were proved to be excellent models to distinguish HEAML from HCC and FNH in comparison between the clinical models and radiomics signatures.Conclusions: Two radiomics-based models derived from CT and MRI images, respectively, performed well in distinguishing HEAML from HCC and FNH and might be potential diagnostic tools to formulate individualized treatment strategies.

Autoimmune diseases (AiDs) are characterized by the destruction of host tissues by the host immune system. The etiology of AiDs is complex, with the implication of multiple genetic defects and various environmental factors (pathogens, antibiotic use, pollutants, stress, and diet). The interaction between these two compartments results in the rupture of tolerance against self-antigens and the unwanted activation of the immune system. Thanks to animal models, the immunopathology of many AiDs is well described, with the implication of both the innate and adaptive immune systems. This progress toward the understanding of AiDs led to several therapies tested in patients. However, the results from these clinical trials have not been satisfactory, from reversing the course of AiDs to preventing them. The need for a cure has prompted many investigators to explore alternative aspects in the immunopathology of these diseases. Among these new aspects, the role of antimicrobial host defense peptides (AMPs) is growing. Indeed, beyond their antimicrobial activity, AMPs are potent immunomodulatory molecules and consequently are implicated in the development of numerous AiDs. Importantly, according to the disease considered, AMPs appear to play a dual role in autoimmunity with either anti- or pro-inflammatory abilities. Here, we aimed to summarize the current knowledge about the role of AMPs in the development of AiDs and attempt to provide some hypotheses explaining their dual role. Definitely, a complete understanding of this aspect is mandatory before the design of AMP-based therapies against AiDs.

Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC).Methods: Comprehensive publications were screened in PubMed, Embase, and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis.Results: Thirty-three imaging studies with 5,462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 [95% confidence interval (CI): 0.75–0.80; I2 = 70.7%] and 0.78 (95% CI: 0.76–0.81; I2 = 0.0%) for radiomics, respectively, and were 0.73 (95% CI: 0.71–0.75; I2 = 83.7%) and 0.82 (95% CI: 0.80–0.83; I2 = 86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference.Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is a promising application in clinical practice and can provide quantifiable image features. With the help of these features, highly consistent prediction performance will be achieved in anticipation.

Abstract Background The present study constructed and validated the use of contrast‐enhanced computed tomography (CT)‐based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients with hepatocellular carcinoma (HCC). Methods We enrolled 637 patients from two independent institutions. Patients from Institution I were randomly divided into a training cohort of 451 patients and a test cohort of 111 patients. Patients from Institution II served as an independent validation set. The LASSO algorithm was used for the selection of 798 radiomics features. Two classifiers for predicting MVI status and MVI risk were developed using multivariable logistic regression. We also performed a survival analysis to investigate the potentially prognostic value of the proposed MVI classifiers. Results The developed radiomics signature predicted MVI status with an area under the receiver operating characteristic curve (AUC) of .780, .776, and .743 in the training, test, and independent validation cohorts, respectively. The final MVI status classifier that integrated two clinical factors (age and α‐fetoprotein level) achieved AUC of .806, .803, and .796 in the training, test, and independent validation cohorts, respectively. For MVI risk stratification, the AUCs of the radiomics signature were .746, .664, and .700 in the training, test, and independent validation cohorts, respectively, and the AUCs of the final MVI risk classifier‐integrated clinical stage were .783, .778, and .740, respectively. Survival analysis showed that our MVI status classifier significantly stratified patients for short overall survival or early tumor recurrence. Conclusions Our CT radiomics‐based models were able to predict MVI status and MVI risk of HCC and might serve as a reliable preoperative evaluation tool.

Myrosinase enzymes and their substrate glucosinolates provide a specific defensive mechanism against biotic invaders in the Brassicaceae family. In these plants, myrosinase hydrolyzes glucosinolates into diverse products, which can have direct antibiotic activity or function as signaling molecules that initiate a variety of defense reactions. A myrosinase, β-thioglucoside glucohydrolase 1 (TGG1) was previously found to be strikingly abundant in guard cells, and it is required for the abscisic acid (ABA) response of stomata. However, it remains unknown which particular physiological processes actually involve stomatal activity as modulated by TGG1. In this experimental study, a homologous TGG1 gene from broccoli (Brassica oleracea var. italica), BoTGG1, was overexpressed in Arabidopsis. The transgenic plants showed enhanced resistance against the bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 via improved stomatal defense. Upon Pst DC3000 infection, overexpressing BoTGG1 accelerated stomatal closure and inhibited the reopening of stomata. Compared with the wild type, 35S::BoTGG1 was more sensitive to ABA- and salicylic acid (SA)-induced stomatal closure but was less sensitive to indole-3-acetic acid (IAA)-inhibited stomatal closure, thus indicating these hormone signaling pathways were possibly involved in stomatal defense regulated by TGG1. Furthermore, overexpression of BoTGG1 delayed flowering by promoting the expression of FLOWERING LOCUS C (FLC), which encodes a MADS-box transcription factor known as floral repressor. Taken together, our study’s results suggest glucosinolate metabolism mediated by TGG1 plays a role in plant stomatal defense against P. syringae and also modulates flowering time by affecting the FLC pathway.

Intestinal homeostasis underpins the development of type 1 diabetes (T1D), and dietary manipulations to enhance intestinal homeostasis have been proposed to prevent T1D. The current study aimed to investigate the efficacy of supplementing a novel specific low-methoxyl pectin (LMP) dietary fiber in preventing T1D development. Female NOD mice were weaned onto control or 5% (wt/wt) LMP supplemented diets for up to 40 weeks of age, overt diabetes incidence and blood glucose were monitored. Then broad-spectrum antibiotics (ABX) treatment per os for 7 days followed by gut microbiota transfer was performed to demonstrate gut microbiota-dependent effects. Next-generation sequencing was used for analyzing the composition of microbiota in caecum. Concentration of short chain fatty acids were determined by GC-MS. The barrier reinforcing tight junction proteins zonula occludens-2 (ZO-2), claudin-1 and NOD like receptor protein 3 (NLRP3) inflammasome activation were determined by Western blot. The proportion of CD25+Foxp3+CD4+ regulatory T cell (Foxp3+ Treg) in the pancreas, pancreatic and mesenteric lymph nodes was analyzed by flow cytometry. We found that LMP supplementation ameliorated T1D development in non-obese diabetic (NOD) mice, as evidenced by decreasing diabetes incidence and fasting glucose levels in LMP fed NOD mice. Further microbiota analysis revealed that LMP supplementation prevented T1D-associated caecal dysbiosis and selectively enriched caecal bacterial species to produce more SCFAs. The LMP-mediated microbial balance further enhanced caecal barrier function and shaped gut-pancreatic immune environment, as characterized by higher expression of tight junction proteins claudin-1, ZO-2 in caecum, increased Foxp3+ Treg population and decreased NLRP3 inflammasome activation in both caecum and pancreas. The microbiota-dependent beneficial effect of LMP on T1D was further proven by the fact that aberration of caecal microbiota by ABX treatment worsened T1D autoimmunity and could be restored with transfer of feces of LMP-fed NOD mice. These data demonstrate that this novel LMP limits T1D development by inducing caecal homeostasis to shape pancreatic immune environment. This finding opens a realistic option for gut microbiota manipulation and prevention of T1D in humans.

Introduction: Epithelioid hepatic angiomyolipoma (Epi-HAML) can easily be misdiagnosed as a malignant tumor such as hepatocellular carcinoma (HCC) because of the low-fat content on imaging. We analyzed and compared the magnetic resonance imaging (MRI) features of Epi-HAML and HCC, which would aid in disease diagnosis.Methods: We included 30 pathologically confirmed patients with Epi-HAML and 80 with HCC, who underwent both MRI unenhanced scan and three-phase contrast-enhanced MRI scan. The clinical and MRI features of the two groups were summarized and analyzed.Results: Epi-HAML showed significant differences compared to HCC group in terms of clinical features such as sex preference, age, concomitant diseases (hepatitis B and cirrhosis), and elevated plasma alpha-fetoprotein (AFP) (P < 0.001). In addition, there were statistically significant differences between both tumor types with regard to conventional MRI findings such as a solitary tumor (100 vs. 83.8%, P = 0.018), well-defined (93.3 vs. 71.3%, P = 0.027), mild hyperintensity (40.0 vs. 3.7%, P < 0.001) on DWI with high b-value, fat within the tumor (43.3 vs. 8.8%, P < 0.001), and rare necrosis (3.3 vs. 26.3%, P = 0.016). Besides, Epi-HAML displayed significant differences compared to HCC in terms of contrast-enhanced MRI characteristics such as draining hepatic vein (30.0 vs. 3.8%, P < 0.001), portal vein tumor thrombus (0 vs. 13.8%, P = 0.033), hypointensity at delayed phase (70.0 vs. 95%, P = 0.001), intra-tumor vessel at delayed phase (36.7 vs. 10.0%, P = 0.003), pseudocapsule (20.0 vs. 78.8%, P < 0.001), and prolonged enhancement (56.7 vs. 1.2%, P < 0.001).Conclusion: Epi-HAML frequently occurs in middle-aged women and usually lacks characteristic clinical symptoms. Typically, Epi-HAML presents as an isolated and well-defined tumor with rich vasculature. Specific MRI features such as intra-tumor fat, intra-tumor vessel, draining hepatic vein, prolonged enhancement, and lack of capsule may contribute to a more confident diagnosis of Epi-HAML.

Introduction: The emerging field of “radiomics” has considerable potential in disease diagnosis, pathologic grading, prognosis evaluation, and prediction of treatment response. We aimed to develop a novel radiomics nomogram based on radiomics features and clinical characteristics that could preoperatively predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy.Methods: A predictive model was developed from a training cohort comprising 139 ICC patients diagnosed between January 2010 and June 2014. Radiomics features were extracted from arterial-phase image of contrast-enhanced magnetic resonance imaging. Feature selection and construction of a “radiomics signature” were through Spearman's rank correlation and least absolute shrinkage and selection operator (LASSO) logistic regression. Combined with clinical characteristics, a radiomics nomogram was developed with multivariable logistic regression. Performance of the nomogram was evaluated with regard to discrimination, calibration, and clinical utility. An independent validation cohort involving 70 patients recruited from July 2014 to March 2016 was used to evaluate the utility of the nomogram developed.Results: The radiomics signature, consisting of nine features, differed significantly between ER patients and non-ER patients in training and validation cohorts. The area under the curve (AUC) of the radiomics signature in training and validation cohorts was 0.82 (confidence interval [CI], 0.74–0.88) and 0.77 (95% CI, 0.65–0.86), respectively. The AUC of the radiomics nomogram combining the radiomics signature and clinical stage in the two cohorts was 0.90 (95%CI, 0.83–0.94) and 0.86 (95% CI, 0.76–0.93), respectively. Decision curve analysis confirmed the clinical usefulness of the radiomics nomogram.Conclusion: The non-invasive radiomics nomogram developed using the radiomics signature and clinical stage could be used to predict ER of ICC after partial hepatectomy.

The performance of chemical reactions has been enhanced immensely with surface plasmon resonance (SPR)-based sensors. In this review, the principle and application of SPR sensors are introduced and summarized thoroughly. We introduce the mechanism of the SPR sensors and present a thorough summary about the optical design, including the substrate and excitation modes of the surface plasmons. Additionally, the applications based on SPR sensors are described by the Raman and fluorescence spectroscopy in plasmon-driven surface catalytic reactions and the measurement of refractive index sensing, especially.