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To examine the hypoglycemic effects and myocardial protection of Sanghuangporus vaninii polysaccharide (SP) in T2DM rats, these effects were assessed in rats fed a high glucose and high fat diet combined with streptozotocin (STZ). The rats were randomly assigned to one of the following six groups: the diabetes mellitus (DM), metformin (MET), low-, medium-, and high-dose SP (SPL, SPM, and SPH), and control (CN) groups. Following 4 weeks of continuous intervention by gavage, the weights and multiple physiological and biochemical indicators of rats were measured and recorded, and performed pathological observations of the pancreatic and myocardial tissues of rats. Results revealed that SP at all assessed doses could reduce weight loss in T2DM rats compared to the DM group, significantly reduce fasting blood glucose and serum insulin levels, and improve glucose tolerance (P

Purpose – This study aims to analyze the development direction of track geometry inspection equipment for high-speed comprehensive inspection train in China. Design/methodology/approach – The development of track geometry inspection equipment for high-speed comprehensive inspection train in China in the past 20 years can be divided into 3 stages. Track geometry inspection equipment 1.0 is the stage of analog signal. At the stage 1.0, the first priority is to meet the China's railways basic needs of pre-operation joint debugging, safety assessment and daily dynamic inspection, maintenance and repair after operation. Track geometry inspection equipment 2.0 is the stage of digital signal. At the stage 2.0, it is important to improve stability and reliability of track geometry inspection equipment by upgrading the hardware sensors and improving software architecture. Track geometry inspection equipment 3.0 is the stage of lightweight. At the stage 3.0, miniaturization, low power consumption, self-running and green economy are co-developing on demand. Findings – The ability of track geometry inspection equipment for high-speed comprehensive inspection train will be expanded. The dynamic inspection of track stiffness changes will be studied under loaded and unloaded conditions in response to the track local settlement, track plate detachment and cushion plate failure. The dynamic measurement method of rail surface slope and vertical curve radius will be proposed, to reveal the changes in railway profile parameters of high-speed railways and the relationship between railway profile, track irregularity and subsidence of subgrade and bridges. The 200 m cut-off wavelength of track regularity will be researched to adapt to the operating speed of 400 km/h. Originality/value – The research can provide new connotations and requirements of track geometry inspection equipment for high-speed comprehensive inspection train in the new railway stage.

Abstract Investigate the impact of remnant cholesterol (RC) levels on carotid artery intima thickness (CIT) in type 2 diabetes mellitus (T2DM) patients. From September 2021 to September 2023, a prospective multicenter study involved 158 T2DM patients. They were divided into a higher RC group (n = 80) and a lower RC group (n = 78) based on median RC levels. Additionally, 92 healthy volunteers served as the control group. CIT, carotid media thickness (CMT), and carotid intima-media thickness (CIMT) were measured. General clinical data, lab results, CIMT, CIT, and CMT differences among the three groups were compared. Multiple regression analysis explored CIT factors in T2DM patients. 1. No significant sex, age, BMI, high-density lipoprotein cholesterol (HDL-C), T2DM duration, fasting blood glucose, or glycated hemoglobin differences were found among the groups (p > 0.05). 2. CIMT and CIT were significantly higher in T2DM than the control group (p 0.05). Multiple linear regression analysis showed RC as an influencing CIT factor in T2DM patients (β = 0.473, p = 0.005). CIT is significantly thicker in T2DM patients with higher RC than in those with lower RC, and RC is the influence factor of CIT, which suggests that more attention should be paid to the detection of RC in T2DM patients.

IntroductionNeedle-free injection system (NFIS) is easy to operate and can decrease needle phobia. Besides, NFIS can increase the interaction of antigens in a more dispersed manner with immune cell at local injection site, which may improve the immune responses of mRNA vaccines. Although SARS-CoV-2 mRNA vaccines have great success, universal vaccines are urgently needed. Delivering universal mRNA vaccines by NFIS is preferred to combat COVID-19.MethodsRBD3-Fc mRNA expressing BA.4, Delta, and prototype RBD, and human IgG Fc with YTE mutation was designed and synthesized. The safety and immune responses of universal RBD3-Fc naked mRNA and mRNA-LNP vaccines delivered intradermally using NFIS (named GV-01) and intramuscularly via needles were evaluated and compared in rats.ResultsThe prime-boost regimen administered by two routes resulted in potent immune responses and intradermal delivery displays comparable or better performance in terms of binding antibodies, neutralizing antibodies and T cell responses. Naked mRNA vaccines were functional, but less effective than mRNA-LNP vaccines.DiscussionThe above results suggest that RBD3-Fc vaccines are safe and immunogenic and NFIS can be used as an alternative to needles/syringes for the inoculation of mRNA-LNP vaccines to elicit robust systematic immune responses.

Abstract Background The prognosis of advanced ovarian cancer is often poor. Although there are several treatment options for stage IV epithelial ovarian cancer, it is not clear which treatment will benefit the patient’s prognosis.We conducted an analysis using the SEER database to compare the impact of different treatment modalities on the prognosis of advanced ovarian cancer. Methods The present study conducts a retrospective analysis of relevant data from the SEER database pertaining to patients diagnosed with stage IV epithelial ovarian cancer between 2011 and 2020 (n = 5345). Statistical methods including Kaplan-Meier curves, log-rank tests, and Cox regression analysis are employed to ascertain the impact of different treatment regimens on the prognosis of patients with stage IV epithelial ovarian cancer. Results Among patients with stage IV epithelial ovarian cancer, age ≥ 60 and the presence of lung metastases or multiple metastases were identified as poor prognostic factors. Conversely, being Asian or Pacific Islander, married, and testing negative for CA125 were associated with favorable prognoses. In terms of the choice of treatment for patients, surgery plus chemotherapy was the best treatment modality, and timely surgery could significantly improve the prognosis of patients, but there was no difference between chemoradiotherapy alone and the surgery group among patients with lung metastases. Conclusion The prognosis of patients with stage IV epithelial ovarian cancer is influenced by many factors. In terms of the choice of treatment, patients with surgery plus chemotherapy have the best prognosis. In cases where lung metastases are inoperable, a combination of radiotherapy and chemotherapy can be used. In other cases, radiotherapy does not improve outcomes in patients with stage IV epithelial ovarian cancer. This study provides a basis for the choice of treatment for patients with stage IV epithelial ovarian cancer.

Osteoarthritis (OA) progresses due to the excessive generation of reactive oxygen and nitrogen species (ROS/RNS) and abnormal ATP energy metabolism related to the oxidative phosphorylation pathway in the mitochondria. Highly active single-atom nanozymes (SAzymes) can help regulate the redox balance and have shown their potential in the treatment of inflammatory diseases. In this study, we innovatively utilised ligand-mediated strategies to chelate Pt4+ with modified g-C3N4 by π–π interaction to prepare g–C3N4–loaded Pt single-atom (Pt SA/C3N4) nanozymes that serve as superoxide dismutase (SOD)/catalase (CAT) mimics to scavenge ROS/RNS and regulate mitochondrial ATP production, ultimately delaying the progression of OA. Pt SA/C3N4 exhibited a high loading of Pt single atoms (2.45 wt%), with an excellent photothermal conversion efficiency (54.71%), resulting in tunable catalytic activities under near-infrared light (NIR) irradiation. Interestingly, the Pt–N6 active centres in Pt SA/C3N4 formed electron capture sites for electron holes, in which g-C3N4 regulated the d-band centre of Pt, and the N-rich sites transferred electrons to Pt, leading to the enhanced adsorption of free radicals and thus higher SOD- and CAT-like activities compared with pure g-C3N4 and g–C3N4–loaded Pt nanoparticles (Pt NPs/C3N4). Based on the use of H2O2-induced chondrocytes to simulate ROS-injured cartilage in vitro and an OA joint model in vivo, the results showed that Pt SA/C3N4 could reduce oxidative stress-induced damage, protect mitochondrial function, inhibit inflammation progression, and rebuild the OA microenvironment, thereby delaying the progression of OA. In particular, under NIR light irradiation, Pt SA/C3N4 could help reverse the oxidative stress-induced joint cartilage damage, bringing it closer to the state of the normal cartilage. Mechanistically, Pt SA/C3N4 regulated the expression of mitochondrial respiratory chain complexes, mainly NDUFV2 of complex 1 and MT-ATP6 of ATP synthase, to reduce ROS/RNS and promote ATP production. This study provides novel insights into the design of artificial nanozymes for treating oxidative stress-induced inflammatory diseases.

Summary: Constructing electric vehicle charging piles (EVCPs) is crucial for promoting electric vehicle (EV) sales. Yet, empirical evidence on the bidirectional relationship between EV sales and public EVCPs is limited, with most related works relying on simulations. We empirically investigate this relationship using panel vector autoregression (PVAR) across 95 Chinese cities from 2018 to 2022. Results show EVCPs significantly boost EV sales, especially in colder regions. Higher air pollution and purchase subsidies inhibit the promoting impact of EV sales on EVCPs. The propelling effect of EVCPs on EV sales is impaired in higher housing prices regions. A significant and positive bidirectional relationship exists between EVCPs and battery electric vehicles (BEVs) sales exists, but not with plug-in hybrid electric vehicles (PHEVs) present. Our findings have implications for stakeholders, such as the construction of fast charging infrastructure under lower temperatures, and differentiated charging demands of EVs with different powertrains need to be addressed.

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Background and aim: A genome-wide association study has indicated the association of numerous genes in the 6p21.3 region with chronic hepatitis B virus (HBV) infection. In this study, we screened 12 representative single-nucleotide polymorphisms (SNPs) from the 6p21.3 region and investigated their association with the risk of chronic hepatitis B (CHB) to better understand the molecular etiology underlying CHB risk in the Han Chinese population. Methods: Between March 2021 and November 2022, we included 183 patients with CHB (case group) and 196 with natural HBV clearance (control group). Allele typing of the selected SNPs was performed using snapshot technology. The correlation between the 12 chosen SNPs and the risk of chronic HBV infection was examined using binary logistic regression analysis. Interacting genes of the variants were identified, and expression quantitative trait loci (eQTL) were analyzed using the 3DSNP database. Results: We validated 12 previously reported CHB susceptibility sites, including rs1419881 of transcription factor 19 (TCF19), rs3130542 and rs2853953 of human leukocyte antigen (HLA)-C, rs652888 of euchromatic histone-lysine-methyltransferase 2 (EHMT2), rs2856718, rs9276370, rs7756516, and rs7453920 of HLA-DQ, rs378352 of HLA-DOA, and rs3077, rs9277535, and rs9366816 of HLA-DP. Logistic regression analyses revealed that polymorphisms such as rs9276370, rs7756516, rs7453920, rs3077, rs9277535, and rs9366816 were positively correlated with natural HBV clearance in the dominant model. Conversely, rs3130542 and rs378352 were identified as risk factors for CHB. Haplotype analysis revealed that rs9276370, rs7756516, and rs7453920 in HLA-DQ were TTG and GCA haplotypes. Although the TTG haplotype was positively correlated with a higher risk of CHB, the GCA haplotype significantly influenced the natural clearance of HBV. Bioinformatics analysis demonstrated that rs378352, rs3077, and rs9366816 were located within enhancer states; rs3077 and rs9366816 overlapped with nine transcription factor-binding sites, whereas rs378352 altered five sequence motifs. Furthermore, eQTL analysis demonstrated the functional tendencies of eight statistically significant SNPs (rs3130542, rs9276370, rs7756516, rs7453920, rs378352, rs3077, rs9277535, and rs9366816). Conclusions: Genetic variations within the 6p21.3 region were associated with chronic HBV infection in the Han Chinese population in southern China. Furthermore, the GCA haplotype including rs9276370, rs7756516, and rs7453920 of HLA-DQ contributed significantly to natural HBV clearance, implying that multiple SNPs exert a cumulative allelic effect on HBV infection.

PurposeTo construct and validate radiomics models that utilize ultrasound (US) and digital breast tomosynthesis (DBT) images independently and in combination to non-invasively predict the Ki-67 status in breast cancer.Materials and methods149 breast cancer women who underwent DBT and US scans were retrospectively enrolled from June 2018 to August 2023 in total. Radiomics features were acquired from both the DBT and US images, then selected and reduced in dimensionality using several screening approaches. Establish radiomics models based on DBT, and US separately and combined. The area under the receiver operating characteristic curve (AUC), accuracy, specificity, and sensitivity were utilized to validate the predictive ability of the models. The decision curve analysis (DCA) was used to evaluate the clinical applicability of the models. The output of the classifier with the best AUC performance was converted into Rad-score and was regarded as Rad-Score model. A nomogram was constructed using the logistic regression method, integrating the Rad-Score and clinical factors. The model’s stability was assessed through AUC, calibration curves, and DCA.ResultsSupport vector machine (SVM), logistic regression (LR), and random forest (RF) were trained to establish radiomics models with the selected features, with SVM showing optimal results. The AUC values for three models (US_SVM, DBT_SVM, and merge_SVM) were 0.668, 0.704, and 0.800 respectively. The DeLong test indicated a notable disparity in the area under the curve (AUC) between merge_SVM and US_SVM (p = 0.048), while there was no substantial variability between merge_SVM and DBT_SVM (p = 0.149). The DCA curve indicates that merge_SVM is superior to unimodal models in predicting high Ki-67 level, showing more clinical values. The nomogram integrating Rad-Score with tumor size obtained the better performance in test set (AUC: 0.818) and had more clinical net.ConclusionThe fusion radiomics model performed better in predicting the Ki-67 expression level of breast carcinoma, but the gain effect is limited; thus, DBT is preferred as a preoperative diagnosis mode when resources are limited. Nomogram offers predictive advantages over other methods and can be a valuable tool for predicting Ki-67 levels in BC.

Abstract The cutting process of the cantilever tunneling machine mainly generates excitation through the cutting motor or the hydraulic cylinder driven by the hydraulic system. Regardless of the driving method, the frequency width of the excitation system is limited, difficult to control, and the excitation effect is poor. Therefore, in order to improve excavation efficiency, the excitation system parallel to the original cutting and rotating system is designed. Based on the excitation characteristics caused by alternating fluid flow, the core component of the excitation system, hydraulic exciter, is designed, and the dynamics and dynamic characteristics of the excitation system are analyzed. Based on AMESim software, analyze the impact of factors such as pump displacement, excitation frequency, and pipeline parameters on the operational performance of the electro-hydraulic vibration cutting system, and conduct experimental verification by building a cutting test bench. The experimental results show that as the inner diameter of the pipeline increases, the fluctuation at the acceleration turning point decreases in each cycle and approaches the peak faster. As the excitation frequency increases, the cutting acceleration of the electro-hydraulic excitation cutting system decreases first and then increases, verifying the accuracy of the simulation results. In the experiment, it was found that the acceleration transformation range of the cutting head of the excitation system is the smallest and most stable when the excitation frequency is 30 Hz. In order to verify that the excitation frequency of 30 Hz is the optimal frequency, further contact force tests were conducted on the cutting teeth. It was found that when the hydraulic excitation system adds a 30 Hz excitation frequency, the contact force on the cutting teeth is the smallest. It is more conducive to reducing the damage and wear of the cutting head, and the cutting effect of the cutting head is more obvious. The research results are beneficial for improving the cutting performance of the electro-hydraulic excitation cutting system, providing theoretical support for the selection of cutting parameters for excavation machinery and hydraulic excitation, and improving the existing theoretical system for active excitation cutting vibration analysis of excavation machines.

The direct yaw-moment control (DYC) system consisting of an upper controller and a lower controller is developed on the basis of sliding mode theory and adaptive control technique. First, the two-degree of freedom (2-DOF) model is utilized to calculate the ideal yaw rate. Then, the seven-degree of freedom (7-DOF) electric vehicle model is given to design the upper controller by employing first-order sliding mode (FOSM) method, which is constructed to guarantee the actual yaw rate to approach the ideal value and gain the additional yaw moment. On this basis, an adaptive first-order sliding mode (AFOSM) controller is designed to enhance the system robustness against probable modelling error and parametric uncertainties. In order to mitigate the chattering issue present in the FOSM controller, a novel adaptive super-twisting sliding mode (ASTSM) controller is proposed for the design of DYC. Furthermore, the lower controller converting the additional yaw moment into driving or braking torque acting on each wheel is also developed. Finally, The simulation results indicate that the proposed DYC system can improve the electric vehicle driving stability effectively.

In this study, we propose a big data-based method for characterizing the feature distributions of multiple technologies within a specific domain. Traditional approaches, such as Gartner’s hype cycle or S-curve model, portray the developmental trajectory of individual technologies. However, these approaches are insufficient to encapsulate the aggregate characteristic distribution of multiple technologies within a specific domain. Thus, this study proposes an innovative method in terms of four proposed features, namely versatility, significance, commerciality, and disruptiveness, to characterize the technologies within a given domain. The research methodology involves that the features of technologies are quantitively portrayed using the representative keywords and volumes of returned search results from Google and Google Scholar in two-dimensional analytical spaces of technique and application. We demonstrate the applicability of this method using 452 technologies in the domain of intelligent robotics. The results of our assessment indicate that the versatility values are normally distributed, while the values of significance, commerciality, and disruptiveness follow power-law distributions, in which few technologies possess higher feature values. We also show that significant technologies are more likely to be commercialized or cause potential disruption, as such technologies have higher scores in these features. Further, we validly prove the robustness of our approach by comparing historical trends with the literature and characterizing technologies in reduced analytical spaces. Our method can be widely applied in analyzing feature distributions of technologies in different domains, and it can potentially be exploited in decisions like investment, trade, and science policy.

Abstract Talking about osteoporosis, we tend to focus on post-menopause women who are at increased risk due to estrogen depletion, while less attention has been paid to the disease in men. Currently, there is a lack of understanding about the difference of osteoporosis incidence and burden by sex. In this study, we used data from the Global Burden of Disease Study 2019 (GBD 2019) to compare the difference in the prevalence and burden of low bone mineral density (LBMD) between men and women, by location, year, age and socio-demographic index. We found the prevalence of LBMD was higher in women than in men. However, the age standardized mortality rate was greatly higher in men than in women. Using disability-adjusted life year (DALY) to measure the burden, we also observed higher age standardized DALY rate in men. Using sociodemographic index (SDI) as the measure of social development level, we found that higher mortality and DALY rates were mainly seen in middle and high SDI countries. Falls were the leading cause for of deaths and disabilities in both men and women with LBMD, followed by transport injuries. Fall-related mortality was higher in women, while transport injuries caused more deaths and disabilities in men. Conclusively, more attention should be paid to osteoporosis in men, and related policies, clinical practices, and guidelines are in need to reduce the burden of LBMD and osteoporosis in men.

Manipulating electrical and magnetic anisotropies will stimulate multi-terminal device applications. Here, the authors discover axis dependence of current rectifications, magnetic properties and magnon modes in van der Waals multiferroic CuCrP2S6.

Track smoothness has become an important factor in the safe operation of high-speed trains. In order to ensure the safety of high-speed operations, studies on track smoothness detection methods are constantly improving. This paper presents a track irregularity identification method based on CNN-Bi-LSTM and predicts track irregularity through car body acceleration detection, which is easy to collect and can be obtained by passenger trains, so the model proposed in this paper provides an idea for the development of track irregularity identification method based on conventional vehicles. The first step is construction of the data set required for model training. The model input is the car body acceleration detection sequence, and the output is the irregularity sequence of the same length. The fluctuation trend of the irregularity data is extracted by the HP filtering (Hodrick Prescott Filter) algorithm as the prediction target. The second is a prediction model based on the CNN-Bi-LSTM network, extracting features from the car body acceleration data and realizing the point-by-point prediction of irregularities. Meanwhile, this paper proposes an exponential weighted mean square error with priority inner fitting (EIF-MSE) as the loss function, improving the accuracy of big value data prediction, and reducing the risk of false alarms. In conclusion, the model is verified based on the simulation data and the real data measured by the high-speed railway comprehensive inspection train.

Abstract Resource recommendation is extremely challenging under low-resource conditions because representation learning models require sufficient triplets for their training, and the presence of massive long-tail resources leads to data sparsity and cold-start problems. In this paper, an industrial knowledge graph is developed to integrate resources for manufacturing enterprises, and we further formulate long-tail recommendations as a few-shot relational learning problem of learning-to-recommend resources with few interactions under low-resource conditions. First, an industrial knowledge graph is constructed based on the predesigned resource schema. Second, we conduct schema-based reasoning on the schema to heuristically complete the knowledge graph. At last, we propose a multi-head attention-based meta relational learning model with schema-based reasoning to recommend long-tail resources under low-resource conditions. With the IN-Train setting, 5-shot experimental results on the NELL-One and Wiki-One datasets achieve average improvements of 28.8 and 13.3% respectively, compared with MetaR. Empirically, the attention mechanism with relation space translation learns the most important relations for fast convergence. The proposed graph-based platform specifies how to recommend resources using the industrial knowledge graph under low-resource conditions.

To establish an analytical method for the determination of total polyphenols and catechins and rutin in tea by electrochemical sensors. The nanogold/carboxylated carbon nanotube-modified polyphenol electrochemical sensors were prepared by modifying carboxylated carbon nanotubes (SWNTs-COOH) on glassy carbon electrodes by drop coating method and then depositing nanogold (AuNPs) on their surfaces by electrodeposition, and the morphological observations and performance tests were performed by scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). Electrochemical characterization of gallic acid (GA), epigallocatechin gallate (EGCG), rutin and other standard substances in tea leaves as well as mixed systems simulating tea leaves was carried out with the constructed polyphenol sensors. SEM observation confirmed that the nanogold/carboxylated multi-carbon nanotubes were successfully modified on the surface of the glassy carbon electrode, and the impedance of the modified electrode was 78.2% lower than that of the bare electrode, and the peak current response value of the electrode was 253.5% of that of the bare electrode, which significantly improved the sensitivity of the modified electrode. The redox characterization of GA, EGCG and other standards revealed that the Peak I peak potentials of GA, EGCG, quercetin and epicatechin were all 0.50±0.05 V, and the corresponding peak currents Ip were linearly correlated with the concentration of substance c, which can be used as a common landmark oxidation peak for total phenol detection. While EGCG besides Peak I also has an oxidation peak Peak III with a peak potential of 0.42±0.05 V, and the rutin oxidation peak Peak I with a potential of 0.56 V. These two distinct peaks potentials can be quantified separately for EGCG and rutin along with the determination of total phenols. In the tea simulation system containing mixed polyphenols, the peak current of the sensor and the concentration of total polyphenols showed a good linear relationship in the range of 5.0×10-6~6.0×10-5 mol/L, and the correlation coefficient R2 was 0.982. The detection limit was 3.1×10-7 mol/L (S/N=3), and the recovery rate of standard addition was 96.60%~101.17%. This method is characterized with simple operation, short detection time, and no complicated sample pretreatment, which could be a new method for rapid detection of polyphenols.

IntroductionGut-microbiota-brain axis is a potential treatment to decrease the risk of chronic traumatic encephalopathy following traumatic brain injury (TBI). Phosphoglycerate mutase 5 (PGAM5), a mitochondrial serine/threonine protein phosphatase, resides in mitochondrial membrane and regulates mitochondrial homeostasis and metabolism. Mitochondria mediates intestinal barrier and gut microbiome.ObjectivesThis study investigated the association between PGAM5 and gut microbiota in mice with TBI.MethodsThe controlled cortical impact injury was established in mice with genetically-ablated Pgam5 (Pgam5−/−) or wild type, and WT male mice were treated with fecal microbiota transplantation (FMT) from male Pgam5−/− mice or Akkermansia muciniphila (A. muciniphila). Then the gut microbiota abundance, blood metabolites, neurological function, and nerve injury were detected.ResultsTreated with antibiotics for suppressing gut microbiota in Pgam5−/− mice partially relieved the role of Pgam5 deficiency in the improvement of initial inflammatory factors and motor dysfunction post-TBI. Pgam5 knockout exhibited an increased abundance of A. muciniphila in mice. FMT from male Pgam5−/− mice enabled better maintenance of amino acid metabolism and peripherial environment than that in TBI-vehicle mice, which suppressed neuroinflammation and improved neurological deficits, and A. muciniphila was negatively associated with intestinal mucosal injury and neuroinflammation post-TBI. Moreover, A. muciniphila treatment ameliorated neuroinflammation and nerve injury by regulating Nlrp3 inflammasome activation in cerebral cortex with TBI.ConclusionThus, the present study provides evidence that Pgam5 is involved in gut microbiota-mediated neuroinflammation and nerve injury, with A. muciniphila-Nlrp3 contributing to peripheral effects.

Abstract The impacts of weather forecast uncertainties have not been quantified in current air quality forecasting systems. To address this, we developed an efficient 2‐D convolutional neural network‐surface ozone ensemble forecast (2DCNN‐SOEF) system using 2‐D convolutional neural network and weather ensemble forecasts, and we applied the system to 216‐hr ozone forecasts in Shenzhen, China. The 2DCNN‐SOEF demonstrated comparable performance to current operating forecast systems and met the air quality level forecast accuracies required by the Chinese authorities up to 144‐hr lead time. Uncertainties in weather forecasts contributed 38%–54% of the ozone forecast errors at 24‐hr lead time and beyond. The 2DCNN‐SOEF enabled an “ozone exceedance probability” metric, which better represented the risks of air pollution given the range of possible weather outcomes. Our ensemble forecast framework can be extended to operationally forecast other meteorology‐dependent environmental risks globally, making it a valuable tool for environmental management.

Abstract Background This retrospective study investigated biomarkers that can reflect coagulation, inflammation, and lipid abnormalities: platelet-to-albumin ratio (PAR), platelet-to lymphocyte ratio (PLR), low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (LDL-C/HDL-C), apolipoprotein B-to-apolipoprotein ratio (ApoB/ApoA1) whether may be viable prognostic predictors in children and adolescents with osteosarcoma. Methods The retrospective review has enrolled a total of 118 children and adolescent patients diagnosed with osteosarcoma. Analyses with a receiver operating characteristic (ROC) curve were performed to evaluate the optimal cut-off values and to compare the area under curves (AUC). Kaplan–Meier curves were used to visualize survival outcome and a Cox proportional hazards model were used to confirm independent prognostic factors. Results Osteosarcoma patients in high PAR group (> 4.41) and high ApoB/ApoA1 group (> 0.82) experienced significantly shorter overall survival compared with those in low PAR group (≤ 4.41) and low ApoB/ApoA1 group (≤ 0.82). In univariate and multivariable analyses, preoperative PAR and ApoB/ApoA1 were identified as independent prognostic factors for OS in children and adolescents with osteosarcoma. Conclusion Preoperative PAR and ApoB/ApoA1 can be used as promising predictors in children and adolescents with osteosarcoma to help clinicians recognize patients with an increased risk of poor prognosis.

Abstract Background Hepatocellular carcinoma (HCC) developed in fibrotic liver does not respond well to immunotherapy, mainly due to the stromal microenvironment and the fibrosis-related immunosuppressive factors. The characteristic of liver sinusoidal endothelial cells (LSECs) in contributing to fibrosis and orchestrating immune response is responsible for the refractory to targeted therapy or immunotherapy of HCC. We aim to seek a new strategy for HCC treatment based on an old drug simvastatin which shows protecting effect on LSEC. Method The features of LSECs in mouse fibrotic HCC model and human HCC patients were identified by immunofluorescence and scanning electron microscopy. The effect of simvastatin on LSECs and hepatic stellate cells (HSCs) was examined by immunoblotting, quantitative RT-PCR and RNA-seq. LSEC-targeted delivery of simvastatin was designed using nanotechnology. The anti-HCC effect and toxicity of the nano-drug was evaluated in both intra-hepatic and hemi-splenic inoculated mouse fibrotic HCC model. Results LSEC capillarization is associated with fibrotic HCC progression and poor survival in both murine HCC model and HCC patients. We further found simvastatin restores the quiescence of activated hepatic stellate cells (aHSCs) via stimulation of KLF2-NO signaling in LSECs, and up-regulates the expression of CXCL16 in LSECs. In intrahepatic inoculated fibrotic HCC mouse model, LSEC-targeted nano-delivery of simvastatin not only alleviates LSEC capillarization to regress the stromal microenvironment, but also recruits natural killer T (NKT) cells through CXCL16 to suppress tumor progression. Together with anti-programmed death-1-ligand-1 (anti-PD-L1) antibody, targeted-delivery of simvastatin achieves an improved therapeutic effect in hemi-splenic inoculated advanced-stage HCC model. Conclusions These findings reveal an immune-based therapeutic mechanism of simvastatin for remodeling immunosuppressive tumor microenvironment, therefore providing a novel strategy in treating HCC. Graphical Abstract

The immune checkpoint blockade therapy has profoundly revolutionized the field of cancer immunotherapy. However, despite great promise for a variety of cancers, the efficacy of immune checkpoint inhibitors is still low in colorectal cancer (CRC). This is mainly due to the immunosuppressive feature of the tumor microenvironment (TME). Emerging evidence reveals that certain chemotherapeutic drugs induce immunogenic cell death (ICD), demonstrating great potential for remodeling the immunosuppressive TME. In this study, the potential of ginsenoside Rg3 (Rg3) as an ICD inducer against CRC cells was confirmed using in vitro and in vivo experimental approaches. The ICD efficacy of Rg3 could be significantly enhanced by quercetin (QTN) that elicited reactive oxygen species (ROS). To ameliorate in vivo delivery barriers associated with chemotherapeutic drugs, a folate (FA)-targeted polyethylene glycol (PEG)-modified amphiphilic cyclodextrin nanoparticle (NP) was developed for co-encapsulation of Rg3 and QTN. The resultant nanoformulation (CD-PEG-FA.Rg3.QTN) significantly prolonged blood circulation and enhanced tumor targeting in an orthotopic CRC mouse model, resulting in the conversion of immunosuppressive TME. Furthermore, the CD-PEG-FA.Rg3.QTN achieved significantly longer survival of animals in combination with Anti-PD-L1. The study provides a promising strategy for the treatment of CRC.

With intensified market competition, product development procedure is accelerated, requiring rapid product innovation and efficient collaboration between design and manufacturing. However, there still exist information islands, prohibiting integration of product life cycle processes. To address this issue, bionics and digital twin (DT) are combined as a potential solution. The concepts, framework, and features of digital twin bionics (DTB) is originally proposed, with co-evolution mechanism of product-twins (including virtual and physical products) and production-twins (including virtual and physical production) elaborated. A symbiotic co-evolution mechanism is presented to integrate the processes of product development and manufacturing. In detail, the supporting technologies, such as industrial internet of things, cloud edge computing, big data, and artificial intelligence, as well as the potential key technologies, are illustrated. A case study for rapid development of automotive body-in-white in an industrial robotics welding production line is investigated to verify the applicability of the proposed framework. The results suggest that the integration of bionics and DTs can accelerate the innovations and developments of new products and also help to achieve efficient management of production construction.

Abstract Background FOLFOX is a combinational regimen of folinic acid (FnA, FOL), fluorouracil (5-Fu, F) and oxaliplatin (OxP, OX), and has been long considered as the standard treatment of colorectal cancer (CRC) and hepatocellular carcinoma (HCC). Recent developments of nano delivery systems have provided profound promise for improving anticancer efficacy and alleviating side effects of FOLFOX. Previously, a nanoformulation (termed Nano-Folox) containing OxP derivative and FnA was developed in our laboratory using nanoprecipitation technique. Nano-Folox induced OxP-mediated immunogenic cell death (ICD)-associated antitumor immunity, which significantly suppressed tumor growth in the orthotopic CRC mouse model when administrated in combination with free 5-Fu. Methods A nanoformulation (termed Nano-FdUMP) containing FdUMP (5-Fu active metabolite) was newly developed using nanoprecipitation technique and used in combination with Nano-Folox for CRC and HCC therapies. Results Synergistic efficacy was achieved in orthotopic CRC and HCC mouse models. It resulted mainly from the fact that Nano-FdUMP mediated the formation of reactive oxygen species (ROS), which promoted the efficacy of ICD elicited by Nano-Folox. In addition, combination of Nano-Folox/Nano-FdUMP and anti-PD-L1 antibody significantly inhibited CRC liver metastasis, leading to long-term survival in mice. Conclusion This study provides proof of concept that combination of two nano delivery systems can result in successful FOLFOX-associated CRC and HCC therapies. Further optimization in terms of dosing and timing will enhance clinical potential of this combination strategy for patients. Graphical abstract

Carbon emission trading is an important market-based policy instrument to reduce GHG emission using reward-punishment mechanism. Here the authors show that the EU emission trading schemes operate at its designed purpose and there is a positive and linear relationship between firm profits and the firms’ efforts in abatement.

The delayed and incomplete healing of diabetic wounds remains a major concern of global healthcare. The complex biological processes within the diabetic wound, such as chronic inflammation, impaired blood vessel growth and immature collagen remodeling, dramatically cause the failure of current treatments. Thus, emerging therapeutic strategies are highly desirable. Ginkgolide B (GB, a natural product extracted from the leaves of Ginkgo biloba L.) has been applied in the treatment of cerebrovascular and cardiovascular disorders, which is mainly due to the anti-oxidative, anti-inflammatory and proliferative effects. In this study, the role of GB in facilitating the anti-inflammatory and pro-healing effects on diabetic wounds was for the first time confirmed using in vitro, ex vivo and in vivo experimental methods. As a consequence, GB was able to significantly achieve the activities of anti-inflammation, re-epithelialization, and pro-angiogenesis. Previously, a hydrogel has been developed using the high molecular weight hyaluronan (hyaluronic acid, HA) in our laboratory. In this study, this hydrogel was utilized in vivo for local administration of GB to the full-thickness wounds of diabetic mice. The resultant hydrogel formulation (HA-GB) resulted in the reduction of inflammation, the enhancement of re-epithelialization and angiogenesis, and the modulation of collagens from type III to type I, significantly promoting the healing outcome as compared with a commercially available wound dressing product (INTRASITE Gel). This study confirms a great therapeutic promise of HA-GB for the chronic wounds of diabetic patients.

The impaired wound healing in diabetes is a central concern of healthcare worldwide. However, current treatments often fail due to the complexity of diabetic wounds, and thus, emerging therapeutic approaches are needed. Macrophages, a prominent immune cell in the wound, play key roles in tissue repair and regeneration. Recent evidence has demonstrated that macrophages in diabetic wounds maintain a persistent proinflammatory phenotype that causes the failure of healing. Therefore, modulation of macrophages provides great promise for wound healing in diabetic patients. In this study, the potential of paeoniflorin (PF, a chemical compound derived from the herb Paeonia lactiflora) for the transition of macrophages from M1 (proinflammatory phenotype) to M2 (anti-inflammatory/prohealing phenotype) was confirmed using ex vivo and in vivo experimental approaches. A hydrogel based on high molecular weight hyaluronic acid (HA) was developed for local administration of PF in experimental diabetic mice with a full-thickness wound. The resultant formulation (HA-PF) was able to significantly promote cutaneous healing as compared to INTRASITE Gel (a commercial hydrogel wound dressing). This outcome was accompanied by the amelioration of inflammation, the improvement of angiogenesis, and re-epithelialization, and the deposition of collagen. Our study indicates the significant potential of HA-PF for clinical translation in diabetic wound healing.

Objective Intramuscular fat (IMF) content plays an important role in meat quality. Identification of single nucleotide polymorphisms (SNPs) and genes related to pig IMF, especially using pig populations with high IMF content variation, can help to establish novel molecular breeding tools for optimizing IMF in pork and unveil the mechanisms that underlie fat metabolism. Methods We collected muscle samples of 453 Chinese Lulai black pigs, measured IMF content by Soxhlet petroleum-ether extraction method, and genotyped genome-wide SNPs using GeneSeek Genomic Profiler Porcine HD BeadChip. Then a genome-wide association study was performed using a linear mixed model implemented in the GEMMA software. Results A total of 43 SNPs were identified to be significantly associated with IMF content by the cutoff p

Background Ovarian cancer is the most common gynecological malignancy and is difficult to manage due to the emergence of resistance to various chemotherapeutic drugs. New efforts are urgently awaited. Aspirin, which is traditionally considered a nonsteroidal anti-inflammatory drug (NSAID), has been reported to exert potential chemopreventive effects. Therefore, we aimed to investigate the anticancer effect and explore the underlying molecular mechanisms of aspirin on epithelial ovarian cancer (EOC) cells. Methods We conducted wound healing, transwell migration, EdU cell proliferation, colony formation and apoptosis detection assays to observe the effects of aspirin on the migration, proliferation and apoptosis of EOC cells (A2870, Caov-3, and SK-OV-3). EOC cells were treated with a combination of aspirin and cisplatin (CDDP) to observe the effect of aspirin on enhancing CDDP sensitivity. Orthotopic xenograft models of ovarian cancer established with A2780-Luciferase-GFP cells were applied to compare tumor growth inhibition in the control, CDDP and CDDP plus aspirin groups through in vivo imaging, which can be used to continuously monitor tumor growth. The expression and acetylation levels of p53 in EOC cells treated with aspirin were determined using western blotting, and p53 acetylation levels were examined in tumors harvested from the transplanted mice. Quantitative real-time PCR was used to assess the mRNA expression of p53 target genes. Results Aspirin inhibited migration and proliferation and induced apoptosis in EOC cell lines in a concentration-dependent manner. In vitro, aspirin enhanced the sensitivity of EOC cells to CDDP by increasing its inhibitory effect on proliferation and its effect on inducing apoptosis. In vivo, the differences in the tumor growth inhibition rates among the different CDDP experimental groups were statistically significant (p

Human papillomavirus (HPV) has been the leading cause of cervical cancer for over 25 years. Approximately 5.5–11% of all cervical cancers are reported to be HPV-negative, which can be attributed to truly negative and false-negative results. The truly HPV-negative cervical cancers are almost all cervical adenocarcinomas with unclear etiology. False HPV negativity can arise from histological misclassification, latent HPV infection, disruption of the targeting fragment, non-high risk HPV infection, and HPV testing methods. HPV-negative cervical cancers are often diagnosed at an advanced FIGO stage and have a poor prognosis; thus, the management of these cases requires greater attention.

As an essential direction for developing inclusive finance, digital financial inclusion breaks through the time and space constraints of inclusive finance development and has extensive connections between different regions. However, no research has modelled the network connections and the role and position of different digital financial inclusion development regions. This study constructed the spatial association network of China’s digital financial inclusion development and used the network analysis method and the quadratic assignment procedure (QAP) method to study the structural and locational properties and the influencing factors of the network. We found that (1) although the network had a relatively low density, its connectivity and stability were excellent, and the network structure is not hierarchical; (2) the centrality of some rapidly developing central and western provinces was greater than that of some developed eastern provinces; (3) developed eastern provinces played a net spillover role, driving the development of digital financial inclusion in central and western provinces; and (4) the spatial association was affected by the development level of the PC Internet and economy, the industrial structure, and the spatial adjacency. This study enriches the research on digital financial inclusion and provides a scientific basis for the formulation and implementation of policies to promote the further development of digital financial inclusion.

Objective Cluster of differentiation 4 protein (CD4) gene is an important immune related gene which plays a significant role in T cell development and host resistance during viral infection. Methods In order to unravel the relationship of CpG island methylation level of CD4 gene with its gene expression and T lymphocyte subpopulation traits, we used one typical Chinese indigenous breed (Dapulian, DP) and one commercial breed (Landrace), then predicted the CpG island of CD4 gene, determined the methylation status of CpG sites by bisulfite sequencing polymerase chain reaction (BSP), and carried out the correlation analyses of methylation frequencies of CpG sites with mRNA expression and T lymphocyte subpopulation traits. Results There was one CpG island predicted in the upstream −2 kb region and exon one of porcine CD4 gene, which located 333 bp upstream from the start site of gene and contained nine CpG sites. The correlation analysis results indicated that the methylation frequency of CpG_2 significantly correlated with CD4 mRNA expression in the DP and Landrace combined population, though it did not reach significance level in DP and Landrace separately. Additionally, 15 potential binding transcription factors (TFs) were predicted within the CpG island, and one of them (Jumonji) contained CpG_2 site, suggesting that it may influence the CD4 gene expression through the potential binding TFs. We also found methylation frequency of CpG_2 negatively correlated with T lymphocyte subpopulation traits CD4+CD8−CD3−, CD4−CD8+CD3− and CD4+/CD8+, and positively correlated with CD4−CD8+CD3+ and CD4+CD8+CD3+ (for all correlation, p

Living cells are complex systems characterized by fluids crowded by hundreds of different elements, including, in particular, a high density of polymers. They are an excellent and challenging laboratory to study exotic emerging physical phenomena, where entropic forces emerge from the organization processes of many-body interactions. The competition between microscopic and entropic forces may generate complex behaviors, such as phase transitions, which living cells may use to accomplish their functions. In the era of big data, where biological information abounds, but general principles and precise understanding of the microscopic interactions is scarce, entropy methods may offer significant information. In this work, we developed a model where a complex thermodynamic equilibrium resulted from the competition between an effective electrostatic short-range interaction and the entropic forces emerging in a fluid crowded by different sized polymers. The target audience for this article are interdisciplinary researchers in complex systems, particularly in thermodynamics and biophysics modeling.

Abstract Enhancer of zeste homolog 2 (EZH2) is often increased in malignant tumors and is involved in metastasis. EZH2 silences gene expression by tri-methylating the lysine 27 residue of histone H3 (H3K27me3). However, the mechanism underlying EZH2 promotion of ovarian cancer metastasis remains elusive. Here, we showed that EZH2 is up-regulated in ovarian cancer and is associated with tumor metastasis and poor survival by mRNA sequencing and microarray results from databases. Tissue microarray and immunohistochemistry results revealed that EZH2 was negatively correlated with the expression of tissue inhibitor of metalloproteinases 2 (TIMP2). EZH2 overexpression inhibited TIMP2 expression and promoted proteolytic activities of matrix metalloproteinases 2 and 9 and vice versa. EZH2 promoted ovarian cancer invasion and migration, which could be largely reversed by TIMP2 down-regulation in vitro and in vivo. Both H3K27me3 inhibition and demethylation could reduce methylation of the TIMP2 promoter and finally reactivate TIMP2 transcription. The presence of EZH2 and H3K27me3 at the TIMP2 promoter was confirmed by chromatin immunoprecipitation. H3K27me3 and DNA methyltransferases at the promoter were significantly increased by EZH2 overexpression. These results suggest that EZH2 inhibits TIMP2 expression via H3K27me3 and DNA methylation, which relieve the repression of MMP and facilitate ovarian cancer invasion and migration.

Background/Aims The association between the kinesin family member 1B (KIF1B) gene polymorphism and the risk of hepatitis B virus-related hepatocellular carcinoma (HCC) has been investigated in many peer-reviewed studies. However, scholars have failed to replicate these results in validation tests. The purpose of the present study was to explore whether the KIF1B rs17401966 polymorphism was associated with susceptibility to HCC. Methods The results of case-controlled studies on the correlation between the KIF1B rs17401966 polymorphism and HCC susceptibility were collected using Google Scholar and the EMBASE, PubMed and CNKI databases. Based on inclusion and exclusion criteria, 5 papers with a total of 12 cohorts were included in this study. Results The 12 cohorts were integrated, and the results showed that the rs17401966 polymorphism reduced the risk for HCC under the allele, heterozygous, homozygous, and dominant models but not under the additive or recessive models. Moreover, the merged results showed strong heterogeneity, and the cumulative meta-analysis results were unreliable. A genetic differentiation analysis of the 12 cohorts found different degrees of genetic differentiation between the 5 cohorts in Zhang et al.’s study and the cohorts in the other studies. We further divided the 12 study cohorts into 2 subgroups based on fixation index value; however, the results of that analysis were inconsistent. Conclusions The results of this meta-analysis were not able to verify the association between the KIF1B rs1740199 polymorphism and HCC risk. Therefore, a well-designed, large-scale, multicenter validation study is needed to confirm the relationship.

Polyinosinic-polycytidylic acid (poly I:C), a synthetic dsRNA analog, has been demonstrated to have stimulatory effects similar to viral dsRNA. To gain deep knowledge of the host transcriptional response of pigs to poly I:C stimulation, in the present study, we cultured and stimulated peripheral blood mononuclear cells (PBMC) of piglets of one Chinese indigenous breed (Dapulian) and one modern commercial breed (Landrace) with poly I:C, and compared their transcriptional profiling using RNA-sequencing (RNA-seq). Our results indicated that poly I:C stimulation can elicit significantly differentially expressed (DE) genes in Dapulian (g = 290) as well as Landrace (g = 85). We also performed gene set analysis using the Gene Set Enrichment Analysis (GSEA) package, and identified some significantly enriched gene sets in Dapulian (g = 18) and Landrace (g = 21). Most of the shared DE genes and gene sets were immune-related, and may play crucial rules in the immune response of poly I:C stimulation. In addition, we detected large sets of significantly DE genes and enriched gene sets when comparing the gene expression profile between the two breeds, including control and poly I:C stimulation groups. Besides immune-related functions, some of the DE genes and gene sets between the two breeds were involved in development and growth of various tissues, which may be correlated with the different characteristics of the two breeds. The DE genes and gene sets detected herein provide crucial information towards understanding the immune regulation of antiviral responses, and the molecular mechanisms of different genetic resistance to viral infection, in modern and indigenous pigs.

This study pioneers to investigate the impact of industry on the European Union carbon trading market based on network perspective. All the accounts in the European Union Emissions Trading System (EU ETS) are summarized at the industry level, and then the trading relationship between industries is constructed in the network layout. Based on this network, the centrality of each industry is measured—the industries of electricity, gas, steam and air conditioning supply (EGSAS), bank, broker, exchange, and wholesale trade excluding motor vehicles and motorcycles (WTEM) have higher centrality. Finally, the impact of industry on the evolution of networks is analyzed, Findings show that the financial intermediaries play important roles at the beginning of each phase, while their influences on the network will decrease as the market goes on. On the contrary, influences of some other industries like WTEM are gradually increasing.

Low back pain (LBP) is a common worldwide disease that causes an enormous social economic burden. Intervertebral disc degeneration (IDD) is considered as a major cause of LBP. The process of IDD is complicated and involves both inflammation and senescence. The production of pro-inflammatory cytokines, including tumor necrosis factor (TNF)α and interleukin (IL)-1β, is increased in the degenerating intervertebral disc, inducing extracellular matrix degradation. Urolithin A (UA) is a metabolite compound resulting from the degradation of ellagitannins by gut bacteria. UA has been reported to be useful for the treatment of diseases associated with inflammation, senescence, and oxidative damage. Therefore, we hypothesized that UA may be an effective treatment for IDD. This study examined the effects of UA on IDD in vitro and in vivo and explored their underlying mechanisms. Our findings indicated that UA could attenuate cellular senescence induced by hydrogen peroxide in nucleus pulposus cells. UA treatment decreased TNFα-induced matrix metalloproteinase production and the loss of collagen II. At the molecular level, UA considerably blocked the phosphorylation of the extracellular signal-regulated kinase, c-JUN N-terminal kinase, and Akt pathways. In vivo study illustrated that UA treatment could ameliorate IDD in a needle-punctured rat tail model, which was evaluated by X-ray imaging, magnetic resonance imaging, and histological analysis. Thus, the results of our study revealed that UA may be a useful therapeutic agent for the treatment of IDD.

Investigating gene expression of immune cells of whole blood or peripheral blood mononuclear cells (PBMC) under polyinosinic:polycytidylic acid (poly I:C) stimulation is valuable for understanding the immune response of organism to RNA viruses. Quantitative real-time PCR (qRT-PCR) is a standard method for quantification of gene expression studies. However, the reliability of qRT-PCR data critically depends on proper selection of reference genes. In the study, using two different analysis programs, geNorm and NormFinder, we systematically evaluated the gene expression stability of six candidate reference genes (GAPDH, ACTB, B2M, RPL4, TBP, and PPIA) in samples of whole blood and PBMC with or without poly I:C stimulation. Generally, the six candidate genes performed a similar trend of expression stability in the samples of whole blood and PBMC, but more stably expressed in whole blood than in PBMC. geNorm ranked B2M and PPIA as the best combination for gene expression normalization, while according to NormFinder, TBP was ranked as the most stable reference gene, followed by B2M and PPIA. Comprehensively considering the results from the two programs, we recommended using the geometric mean of the three genes, TBP, PPIA and B2M, to normalize the gene expression of whole blood and PBMC with poly I:C stimulation. Our study is the first detailed survey of the gene expression stability in whole blood and PBMC with or without poly I:C stimulation and should be helpful for investigating the molecular mechanism involved in porcine whole blood and PBMC in response to poly I:C stimulation.

In this paper, a network model is constructed using real trading data from the EU carbon market. Metric indicators are then introduced to measure the network, and the economic meanings of the indicators are discussed. By integrating time windows with the network model, three types of network features are examined: growth features, structural features, and scale-free features. The growth pattern of the carbon trading network is then analyzed. As the market grow, the geodesic distances become shorter and the clustering coefficients become larger. The trends of these two indicators suggest that the market is evolving towards efficiency; however, their tiny changes are insufficient to have significant impact. By modeling the heterogeneity of the carbon trading network, we find that the trading relationships between firms obey a broken power law model, which consists of two power law models. The broken power law model can be approximately defined as a traditional power law but with a longer tail in distribution. Furthermore, we find that the model is valid for most of the time of both phases, the model only invalid when the market approaches a high growth rate.

Mitochondrial cytochrome b (Cytb) and partial control region (CR) DNA sequence of 165 individuals were sequenced to determine phylogenetic relationships of eight pig breeds (Laiwu Black, Dapulian Black, Licha Black, Yimeng Black, Yantai Black and Wulian Black, Luyan White and Changwei White) from Shandong province of China, and to what extent they were affected by modern commercial breeds (Landrace, Yorkshire and Duroc) in maternal lineage. The eight breeds from Shandong had lower maternal evolutionary divergence than the three commercial breeds. Additionally, they shared the same haplotype (T2) of Cytb. All these results suggest they may have originated from closely related maternal ancestors, if not from a single ancestor. The fact that haplotypes of Dapulian Black and Laiwu Black formed their own subclades, while those of other breeds of Shandong dispersed in the Asian clade of the tree based on CR, indicates that Dapulian Black and Laiwu Black are indigenous breeds with relatively independent maternal lineage while the other have extensively gene flow with other breeds. Except in Luyan White, no European haplotypes were found in pig breeds from Shandong, demonstrating the maternal introgression from the modern commercial pigs has had no or very little impact on the breeds from Shandong. Comparatively, CR is more suitable to analyze the phylogenetic relationships of closely related groups, whereas the four SNPs of Cytb are useful to determine whether modern commercial breeds (Duroc, Landrace and sometimes Yorkshire) were used as dam in the breeding process of new breeds or synthetic lines in China.