[Research advances on the characteristics of fibroblast in keloid]

In re-cent 20 years, the development of cell biology technology has promoted the research of keloid. Keloid fibroblasts (KFbs) are the main effector cells in keloid, which are closely related to the occurrence and development of keloid. It is significantly different in terms of biological characteristics and gene expression between KFbs and normal fibroblasts. This articles reviews the characteristics of KFbs from multiple perspectives, describing its biological character- istics in details including microstructures, metabolic character- istics, and proliferation properties, and introducing the main characteristics of heterogeneity and genomics of KFbs. The further research on KFbs will help to elucidate the pathogenesis of keloids and provide valuable strategies for the prevention and treatment of keloids.

Evaluation of Ecological Suitability and Quality Suitability of Panax notoginseng Under Multi-Regionalization Modeling Theory

Panax notoginseng is an important medicinal plant in China, but there are some limitations in the ecological suitability study, such as incomplete investigation of species distribution, single regionalization modeling, and lack of collaborative evaluation of ecological suitability, and quality suitability. In this study, the maximum entropy model was used to analyze the ecological suitability of P. notoginseng under current and future climates. The multi-source chemical information of samples was collected to evaluate the uniformity between quality and ecology. The results showed that the current suitable habitat was mainly in southwest China. In the future climate scenarios, the high suitable habitat will be severely degraded. Modeling based on different regionalization could predict larger suitable habitat areas. The samples in the high suitable habitat had both quality suitability and ecological suitability, and the accumulation of chemical components had different responses to different environmental factors. Two-dimensional correlation spectroscopy combined with deep learning could achieve rapid identification of samples from different suitable habitats. In conclusion, global warming is not conducive to the distribution and spread of P. notoginseng. The high suitable habitat was conducive to the cultivation of high-quality medicinal materials. Actual regionalization modeling had more guiding significance for the selection of suitable habitats in a small area. The multi-regionalization modeling theory proposed in this study could provide a new perspective for the ecological suitability study of similar medicinal plants. The results provided a reference for the introduction and cultivation, and lay the foundation for the scientific and standardized production of high-quality P. notoginseng.

[Clinicopathological features of hepatic fibrinogen storage disease in children]

Objective: To investigate the clinicopathological and molecular characteristics of hepatic fibrinogen storage disease (FSD) in children. Methods: The clinical, histopathologic, immunophenotypic, ultrastructural and gene sequencing data of 4 FSD cases were collected from September 2019 to January 2021 in the Children's Hospital of Fudan University, Shanghai, China. Retrospective analysis and literature review were conducted. Results: There were 4 cases of FSD, 3 males and 1 female, aged 3 years and 3 months to 6 years (median age, 3 years and 4 months). The clinical manifestations were abnormal liver function and abnormal blood coagulation function, for which 2 cases had family genetic history. Liver biopsies revealed that, besides liver steatosis, fibrosis and inflammation, there were single or multiple eosinophilic inclusion bodies of various sizes and surrounding transparent pale halo in hepatocytes. Immunohistochemistry showed that the inclusion bodies were positive for anti-fibrinogen. Under the electron microscope, they corresponded to the dilated cisternae of the rough endoplasmic reticulum, which were occupied by compactly packed tubular structures and arranged into a fingerprint-like pattern with curved bundles. Gene sequencing revealed that the 2 cases of FGG mutation were located in exon 8 c.1106A>G (p.His369Arg) and c.905T>C (p.Leu302Pro), and 1 case was located in exon 9 c.1201C>T (p.Arg401Trp). No pathogenic variant was detected in the other case. Conclusions: FSD is a rare genetic metabolic disease and clinically manifests as abnormal liver function with hypofibrinogenemia. In the background of liver steatosis, fibrosis and inflammation, there are eosinophilic inclusions with pale halo in the hepatocytic cytoplasm, which can be identified by anti-fibrinogen immunohistochemical staining. The fingerprint-like structures under electron microscope are helpful for the diagnosis, while FGG sequencing detects the pathogenic mutation of exon 8 or 9 that can clearly explain the phenotype. However, the diagnosis of FSD cannot be completely ruled out if the relevant mutations are not detected.

[Establishment and application of a nomogram model for prognostic risk prediction in patients with epithelial ovarian cancer]

Objective: To explore the prognostic factors of epithelial ovarian carcinoma (EOC), construct a nomogram model, and evaluate the prognosis of EOC patients. Methods: A retrospective analysis was performed on clinicopathological data of 208 cases of EOC patients who received initial treatment in the First Affiliated Hospital of Army Medical University from August 11, 2016 to July 11, 2018, including age, preoperative ascites, preoperative neoadjuvant chemotherapy, surgical method, pathological type, pathological differentiation degree, surgical pathology stage, preoperative and post-chemotherapy serum cancer antigen 125 (CA₁₂₅) level, human epididymal protein 4 (HE4) level, platelet count and platelet/lymphocyte number ratio (PLR). The univariate and multivariate Cox risk ratio models were used to analyze the related factors affecting progression free survival (PFS) in EOC patients, and the prediction nomogram of PFS in EOC patients was established to evaluate its efficacy in predicting PFS. Results: Univariate analysis showed that preoperative neoadjuvant chemotherapy, pathological type, pathological differentiation degree, surgical pathology stage, serum CA₁₂₅ and HE4 level before operation and after chemotherapy, platelet count and PLR before operation and after chemotherapy were significantly correlated with PFS in EOC patients (all P<0.05). Multivariate analysis showed that surgical pathology stage, preoperative PLR, serum CA₁₂₅ and HE4 level after chemotherapy were independent prognostic factors affecting PFS of EOC patients (all P<0.01). The index coefficient of the prediction model for the prognosis of EOC patients established by this method was 0.749 (95% CI: 0.699-0.798), which had good prediction ability, and could help clinicians to more accurately evaluate the prognosis of EOC patients. Conclusion: The nomogram model constructed based on surgical pathology stage, preoperative PLR, serum CA₁₂₅ and HE4 level after chemotherapy could effectively predict the PFS of EOC patients after initial treatment, could help clinicians to screen high-risk patients, provide individualized treatment, and improve the prognosis of EOC patients.

The Traditional Usages, Chemical Components and Pharmacological Activities of Wolfiporia cocos: A Review

As an endemic species,Wolfiporia cocos (F.A. Wolf) Ryvarden & Gilb. is widely distributed, such as in China, Korea, Japan, and North America, which have had a dual-purpose resource for medicines and food for over 2000 years. The applications of W. cocos were used to treat diseases including edema, insomnia, spleen deficiency, and vomiting. What's more, there have been wide uses of such edible fungi as a function food or dietary supplement recently. Up until now, 166 kinds of chemical components have been isolated and identified from W. cocos including triterpenes, polysaccharides, sterols, diterpenes, and others. Modern pharmacological studies showed that the components hold a wide range of pharmacological activities both in vitro and in vivo, such as antitumor, anti-inflammatory, antibacterial, anti-oxidant, and antidepressant activities. In addition, present results showed that the mechanisms of pharmacological activities were closely related to chemical structures, molecular signaling paths and the expression of relate proteins for polysaccharides and triterpenes. For further in-depth studies on this fungus based on the recent research status, this review provided some perspectives and systematic summaries of W. cocos in traditional uses, chemical components, pharmacological activities, separation and analysis technologies, and structure-activity relationships.

[The stability and repeatability of radiomics features based on lung diffusion-weighted imaging]

Objective: To evaluate the feasibility, robustness and reproducibility of radiomics features derived from lung diffusion-weighted imaging (DWI). Methods: Thirty patients with pulmonary nodules/masses who underwent magnetic resonance imaging examination in the Department of Radiology, the First Affiliated Hospital of Guangzhou Medical University, from January 4 2019 to May 5 2019, including 16 males and 14 females, aged from 27 to 69 (57±11) years, were prospectively collected. Planar echo imaging (EPI) -DWI and fast spin-echo (TSE) -DWI scans were performed under free-breathing conditions. Each scan was repeated at an interval of 5 minutes, and the corresponding apparent diffusion coefficient (ADC) maps were reconstructed. Each DWI and ADC sequence (a total of eight groups of images) were manually segmented by two radiologists, and a total of 396 radiomics features in 6 categories were extracted from each group of images. Consistency correlation coefficient (CCC) and dynamic range (DR) were used to evaluate the robustness of features between two scans, and stable features were defined as both CCC values and DR values ≥0.85. Intra-observer and interobserver reproducibility were evaluated by intra-group correlation coefficient (ICC), and ICC values≥0.75 was considered to be good reproducibility. Results: Regardless of EPI or TSE technique, the number of robust features extracted fromDWI (TSE: n=197, EPI: n=169) were higher than that of the corresponding ADC (TSE: n=126, EPI: n=148). The proportion of robust features of TSE-DWI、EPI-DWI、TSE-ADC、EPI-ADC was 49.7% (197/396), 42.7% (169/396), 31.8% (126/396) and 37.4% (148/396), respectively. Of the 396 features, 54 (13.6%) of them demonstrated great robustness (CCC and DR≥0.85) and interobserver and interobserver reproducibility (ICC≥0.75) across all sequences. Conclusions: Radiomics features derived from lung DWI showed robustness and reproducibility. Different sequences and different feature clusters have different proportions of stable features, and some features have good robustness and reproducibility between different scans, different observers, and even different sequences.

Mitochondrial stress adaptation promotes resistance to aromatase inhibitor in human breast cancer cells via ROS/calcium up-regulated amphiregulin-estrogen receptor loop signaling

Many breast cancer patients harbor high estrogen receptor (ER) expression in tumors that can be treated with endocrine therapy, which includes aromatase inhibitors (AI); unfortunately, resistance often occurs. Mitochondrial dysfunction has been thought to contribute to progression and to be related to hormone receptor expression in breast tumors. Mitochondrial alterations in AI-resistant breast cancer have not yet been defined. In this study, we characterized mitochondrial alterations and their roles in AI resistance. MCF-7aro AI-resistant breast cancer cells were shown to have significant changes in mitochondria. Low expressions of mitochondrial genes and proteins could be poor prognostic factors for breast cancer patients. Long-term mitochondrial inhibitor treatments-mediated mitochondrial stress adaptation could induce letrozole resistance. ERα-amphiregulin (AREG) loop signaling was activated and contributed to mitochondrial stress adaptation-mediated letrozole resistance. The up-regulation of AREG-epidermal growth factor receptor (EGFR) crosstalk activated the PI3K/Akt/mTOR and ERK pathways and was responsible for ERα activation. Moreover, mitochondrial stress adaptation-increased intracellular levels of reactive oxygen species (ROS) and calcium were shown to induce AREG expression and secretion. In conclusion, our results support the claim that mitochondrial stress adaptation contributes to AI resistance via ROS/calcium-mediated AREG-ERα loop signaling and provide possible treatment targets for overcoming AI resistance.

The Storage Period Discrimination of Bolete Mushrooms Based on Deep Learning Methods Combined With Two-Dimensional Correlation Spectroscopy and Integrative Two-Dimensional Correlation Spectroscopy

Boletes are favored by consumers because of their delicious taste and high nutritional value. However, as the storage period increases, their fruiting bodies will grow microorganisms and produce substances harmful to the human body. Therefore, we need to identify the storage period of boletes to ensure their quality. In this article, two-dimensional correlation spectroscopy (2DCOS) images are directly used for deep learning modeling, and the complex spectral data analysis process is transformed into a simple digital image processing problem. We collected 2,018 samples of boletes. After laboratory cleaning, drying, grinding, and tablet compression, their Fourier transform mid-infrared (FT-MIR) spectroscopy data were obtained. Then, we acquired 18,162 spectral images belonging to nine datasets which are synchronous 2DCOS, asynchronous 2DCOS, and integrative 2DCOS (i2DCOS) spectra of 1,750–400, 1,450–1,000, and 1,150–1,000 cm^–1 bands. For these data sets, we established nine deep residual convolutional neural network (ResNet) models to identify the storage period of boletes. The result shows that the accuracy with the train set, test set, and external validation set of the synchronous 2DCOS model on the 1,750–400-cm^–1 band is 100%, and the loss value is close to zero, so this model is the best. The synchronous 2DCOS model on the 1,150–1,000-cm^–1 band comes next, and these two models have high accuracy and generalization ability which can be used to identify the storage period of boletes. The results have certain practical application value and provide a scientific basis for the quality control and market management of bolete mushrooms. In conclusion, our method is novel and extends the application of deep learning in the food field. At the same time, it can be applied to other fields such as agriculture and herbal medicine.

[Clinical features and prognostic analysis of hepatoblastoma in children under six years old]

Objective: To summarize and analyze the clinical features, treatment effects and related factors affecting the prognosis of hepatoblastoma (HB) in children under six years old. Methods: Clinical data of 382 children with HB under six years old who were pathologically diagnosed at the Pediatric Single Center of Beijing Tongren Hospital from May 2005 to May 2019 were analyzed retrospectively. The factors affecting the treatment effect and survival rate of HB were analyzed. The independent risk factors affecting the prognosis of HB were studied by Cox regression model. The χ(2) test was used to compare the enumeration data between groups. Kaplan-Meier method was used for survival analysis. Log-rank test was used to compare the survival rates among subgroups. Results: Children enrolled were with median age of 1.75 (0.08 ~ 5.92) years old and a male to female ratio of 1.5. Alpha-fetoprotein (AFP) median level was 197 406.5 μg/L at initial diagnosis, and the pathological tissue type was mainly epithelial (55.8%). Preoperative PRETEXT stage was mostly stage III (58.6%). 86 cases (22.5%) had portal vein or hepatic vein, and vena cava invasion. 73 cases (19.1%) had extrahepatic adjacent tissues and organs invasion. Twenty-four cases (6.3%) had tumor rupture and bleeding. 171 cases (44.8%) had distant metastases, and 96 cases (25.1%) had multiple intrahepatic lesions. Patients were followed-up to May 2020 (median follow-up time was 56 months). After comprehensive treatment, 218 cases were completely relieved, and 69 cases were partially relieved, and the treatment efficiency was 75.1%. Kaplan-Meier survival analysis showed that the 1, 3, and 5-years overall survival rates (OS) were 93.7%, 84.0%, and 73.9%, respectively, and the event-free survival rates were 90.5%, 79.2%, and 67.5%, respectively. Comparison of the clinical factors of 5-year OS showed that AFP < 100 μg/L (HR = 3.341, P = 0.005), PRETEXT stage IV (HR = 4.026, P = 0.001), vascular invasion (HR = 2.178, P = 0.019) and distant metastasis (HR = 2.634, P = 0.010) were independent risk factors in each subgroup affecting the prognosis of children with HB, and the difference was statistically significant. Conclusion: HB prognosis is related to AFP level, PRETEXT stage, presence or absence of vascular invasion and distant metastasis. Therefore, its survival and prognosis will be different in the presence of different risk factors.

Study on the identification and evaluation of growth years for Paris polyphylla var. yunnanensis using deep learning combined with 2DCOS

Paris polyphylla var. yunnanensis, as perennial plants, its quality is closely related to growth period. Different harvest years determine the dry matter accumulation of its medicinal parts and the dynamic accumulation of active ingredients, as well as its economic value and medicinal value. Therefore, it is necessary to establish a systematic evaluation method for the identification and evaluation of P. polyphylla var. yunnanensis with different growth years. Deep learning has a powerful ability in recognition. This study extends it to the identification analysis of medicinal plants from the perspective of spectrum. For the first time, two-dimensional correlation spectroscopy (2DCOS) based on the attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR) combined with residual neural network (Resnet) was used to identify growth years. 525 samples were collected, 4725 2DCOS images were drawn, and the dry matter accumulation in rhizomes of different growth years and different sampling sites were briefly analyzed. The results show that the eight-year-old P. polyphylla var. yunnanensis in Dali has higher economic value and medicinal value. The synchronous 2DCOS models based on ATR-FTIR can realize the identification of growth years with accuracy of 100%. Synchronous 2DCOS are more suitable for the identification of medicinal plants with complex systems. 2DCOS images with different colors and second derivative processing cannot optimize the modeling results. In summary, the method we established is innovative and feasible. It not only solved the identification of growth years, expanded the application field of deep learning, but could also be extended to further research on other medicinal plants.

A fast and effective way for authentication of Dendrobium species: 2DCOS combined with ResNet based on feature bands extracted by spectrum standard deviation

Dendrobium Sw., as a traditional herb and function food with over 1500 years of history, shows a significant effect in improving immunity and fatigue resistance. However, due of course the large number of species and the quality fluctuating in different species, a fast and effective discrimination method is in need. Recently, spectroscopic techniques combined with chemometrics have become an effective method for low-cost and fast analysis in food and herb. Nevertheless, chemometrics method which based on one-dimensional spectral dataset still encounter the difficulty that can not effectively extract useful information from the spectra. Different from one-dimensional spectra, the two-dimensional correlation spectroscopy (2DCOS) can reveal more detail information of the spectral dataset. Moreover, the appearance of convolutional neural network makes the application of deep learning in image recognition faster and more accurate. In this study, a novel method 2DCOS combined with residual convolutional neural network (ResNet) was used to discriminate the 20 species of Dendrobium. Five feature bands were selected based on spectrum standard deviation (SDD) method in NIR and MIR spectra. Moreover, the models based on full band, total five feature bands, and their fusion-bands had been compared. The results showed that two feature bands 1800-450 cm^-1 and 2400-1900 cm^-1 displayed 100% accuracy in both training set and test set. And also, the accurate discrimination of 10% external validation showed that these models have good generalization ability. In conclusion, 2DCOS combined with ResNet could be an effective and accurate method for classify different Dendrobium species.

Application of UV-Vis and Infrared Spectroscopy on Wild Edible Bolete Mushrooms Discrimination and Evaluation: A Review

Nowadays, wild edible bolete mushrooms are more and more attractive among consumers due to their natural health, nutrition, and delicious characteristics. Appropriate analytical techniques together with multivariate statistics analysis are required for the quality control and evaluation of these edible mushrooms. Ultraviolet-visible (UV-Vis) and infrared (IR) technologies have the advantages of time-saving, low-cost, and environmentally friendly, are now prominent among major analytical technologies for quality evaluation of bolete mushrooms. Chemometrics methods have been developed to solve classification and regression issues of bolete mushrooms in combination with spectrum. This paper reviewed the most recent applications of UV-Vis and IR technology coupled with chemometrics in wild edible bolete mushrooms, including the identification of species, origin, and storage duration, fraud detection, and antioxidant properties evaluation, and discussed the limitations and prospects of spectroscopy technologies in the researches of bolete mushrooms, excepting to provide a reference for further research and practical application of wild edible bolete mushrooms.

The traditional uses, phytochemistry, and pharmacological properties of Paris L. (Liliaceae): A review

ETHNOPHARMACOLOGICAL RELEVANCE

Paris L. (Liliaceae) consisted of 33 species, of which the study focused on Paris polyphylla Smith, P. polyphylla var. chinensis (Franch.) Hara, and P. polyphylla Smith var. yunnanensis (Franch.) Hand. -Mazz. Due of course to the good effects of analgesia and hemostasis, it was traditionally used to treat trauma by folk herbalists.

AIM OF THIS REVIEW

This study summarized the traditional uses, distributions, phytochemical components, pharmacological properties, and toxicity evaluation of the genus Paris, and reviewed the economic value of cultivate P. polyphylla. This aim was that of providing a new and comprehensive recognition of these medicinal plants for the further utilization of Paris plants.

MATERIALS AND METHODS

The literature about traditional and folk uses of genus Paris was obtained from Duxiu Search, and China National Knowledge Infrastructure (CNKI). The other literature about genus Paris was searched online on Web of Science, PubMed, Google Scholar, Baidu Scholar, Scifinder database, and Springer research. The Scientific Database of China Plant Species (DCP) (http://db.kib.ac.cn/Default.aspx) databases were used to check the scientific names and provide species, varieties, and distribution of genus Paris. The botany studies information of genus Paris was available online from Plant Plus of China (www.iplant.cn). All the molecular structures of chemical compounds displayed in the text were produced by ChemBioDraw Ultra 14.0.

RESULTS

The plants of genus Paris, containing about 33 species and 15 varieties, are mainly distributed in Southwest China (Yunnan, Sichuan, and Guizhou provinces). More than 320 chemical components have been isolated from genus Paris since 2020, including steroidal saponins, C-21 steroids, phytosterols, insect hormones, pentacyclic triterpenes, flavonoids, and other compounds. Arrays of pharmacological investigations revealed that compounds and extracts of Paris species possess a wide spectrum of pharmacological effects, such as antitumor, cytotoxic, antimicrobial, antifungal, hemostatic, and anti-inflammatory activities. The studies about toxicity evaluation suggested that Rhizome Paridis had slight liver toxicity.

CONCLUSIONS

The dried rhizomes of P. polyphylla, P. polyphylla var. chinensis, and P. polyphylla var. yunnanensis were used to treat wound, bleeding, and stomachache, etc. in folk medicine. Phytochemistry researches showed that different species had pretty similarities especially in terms of chemical constituents. Pharmacological studies witnessed that Rhizome Paridis has various activities. Among these activities, steroidal saponins were the main active ingredients. Furthermore, an important aspect responsible for increasing interest in genus Paris is the use of antifertility-nonhormonal contraceptives by women. Also, the development of TCM (Traditional Chinese medicine) planting industry can improve the income of ethnic minorities and promote economic development.

Superiority Verification of Deep Learning in the Identification of Medicinal Plants: Taking Paris polyphylla var. yunnanensis as an Example

Medicinal plants have a variety of values and are an important source of new drugs and their lead compounds. They have played an important role in the treatment of cancer, AIDS, COVID-19 and other major and unconquered diseases. However, there are problems such as uneven quality and adulteration. Therefore, it is of great significance to find comprehensive, efficient and modern technology for its identification and evaluation to ensure quality and efficacy. In this study, deep learning, which is superior to conventional identification techniques, was extended to the identification of the part and region of the medicinal plant Paris polyphylla var. yunnanensis from the perspective of spectroscopy. Two pattern recognition models, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were established, and the overall discrimination performance of the three types of models was compared. In addition, we also compared the effects of different sample sizes on the discriminant performance of the models for the first time to explore whether the three models had sample size dependence. The results showed that the deep learning model had absolute superiority in the identification of medicinal plant. It was almost unaffected by factors such as data type and sample size. The overall identification ability was significantly better than the PLS-DA and SVM models. This study verified the superiority of the deep learning from examples, and provided a practical reference for related research on other medicinal plants.

[Analysis of the relationship between the anatomical location of intrapulmonary metastatic lymph nodes and relapse risk and survival in patients with N1 non-small cell lung cancer]

Objective: To evaluate the relationship between the anatomical location of intrapulmonary metastatic lymph nodes and relapse risk and survival in patients with N1 non-small cell lung cancer(NSCLC). Methods: A retrospective analysis of the clinical and pathological data of 138 patients with completely resected N1 NSCLC was conducted. There were 79 males and 59 females, aged from 26 to 81 years with an average of (59±10) years. All of them were treated in the Department of Thoracic Surgery Ⅱ of Peking University Cancer Hospital between January 2007 and December 2015. Patients were stratified based on the 8th edition of the American Joint Committee on Cancer (AJCC) N1 classification and the modified pathological N1 classification strategy, respectively. According to modified pathological N1 classification strategy, which was defined based on the anatomical location of intrapulmonary metastatic lymph nodes, N1 nodes were subcategorized into the hilar (stations 10-11, mN1b) (n=36) and peripheral (stations 12-14, mN1a) (n=102) zones. The Kaplan-Meier curves were plotted to compare the relapse risk and survival analysis, disease-free survival (DFS), and overall survival (OS) were compared between the two staging methods through univariate and multivariate analysis to evaluate the effectiveness of the two classifications in stratifying patients with distinct risks of disease relapse and survival. Results: According to the modified N1 classification, the differences in 5-year DFS and OS between the subgroups (mN1a vs mN1b) were statistically significant(59.5% vs 35.7%; 81.2% vs 56.0%; both P<0.05). However, following the 8th edition of the AJCC N1 classification, no significant differences were found in DFS and OS between the subgroups (both P>0.05). Multivariate analysis showed that the modified N1 classification was an independent prognostic factor to DFS (HR=1.814, 95%CI: 1.005-3.275) and OS (HR=3.919, 95%CI: 1.918-8.009) (all P<0.05). However, the 8th edition of the AJCC N1 classification was not an independent prognostic factor to DFS (HR=1.360, 95%CI:0.767-2.412) or OS (HR=1.620, 95%CI:0.839-3.131) (both P>0.05) as revealed by multivariate analysis. Conclusions: The relapse risk and survival could be assessed effectively using the modified pathological N1 classification, which was defined and subcategorized based on the anatomical location of intrapulmonary metastatic lymph nodes for N1 NSCLC patients. The modified pathological N1 classification is superior to the 8th edition of the AJCC classification.

[Diagnostic value of platelet associated biomarkers in chronic periprosthetic joint infection]

Objective: To evaluate the diagnostic value of platelet count(PC),PC to mean platelet volume(MPV) ratio(PC/MPV) and plateletcrit(PCT) in chronic periprosthetic joint infection(PJI). Method: The medical records of 159 patients who underwent hip or knee revisions at Department of Joint Surgery,Affiliated Hospital of Qingdao University from August 2013 to June 2019 were retrospectively reviewed. There were 51 patients(26 knees and 25 hips) in the PJI group,which included 28 males and 23 females,aged (68.0±11.8)years (range:32 to 84 years)with a body mass index(BMI)of (26.1±3.6) kg/m².There were 116 patients(19 knees and 97 hips) in the aseptic loosening(AL) group,including 67 males and 49 females,aged (70.3±8.9)years(range:49 to 89 years)with a BMI of (25.0±3.6)kg/m².The plasma C-reactive protein(CRP),erythrocyte sedimentation rate(ESR),PC,MPV,PC/MPV and PCT levels of the two groups were recorded and analyzed. Receiver operating characteristic curve was used to calculate the sensitivity and specificity of each biomarker,expect for MPV,and the diagnostic value of each biomarker was compared according to the area under the curve(AUC).Independent-sample t test or Mann-Whitney U test were used for comparison between groups. Result: Compared with AL group,AJI group had significantly higher levels of CRP,ESR,PC,PC/MPV and PCT(all P<0.05),but lower level of MPV (P<0.05).The AUCs for CRP,ESR,PC,PC/MPV and PCT were 0.820, 0.829, 0.689, 0.668 and 0.676,respectively. Based on the Youden index,the optimal predictive cutoff for CRP was 11.12 mg/L,with a sensitivity of 74.4% and a specificity of 87.1%.The optimal predictive cutoff for ESR was 17.60 mm/1 h,with a sensitivity of 81.4% and a specificity of 75.3%.The optimal predictive cutoff for PC was 243.00×109/L,with a sensitivity of 60.6% and a specificity of 71.8%.The optimal predictive cutoff for PC/MPV was 24.95,the sensitivity was 58.1% and the specificity was 74.1%.And the optimal predictive cutoff for PCT was 0.24%,with a sensitivity of 69.8% and a specificity of 63.5%. Conclusion: PC,PC to MPV ratio and PCT were of limited value to diagnose PJI.

[Mesenchymal stem cells derived apoptotic extracellular vesicles attenuate pro-inflammatory macrophages induced by Porphyromonas gingivalis lipopolysaccharide]

Objective: To investigate whether bone marrow mesenchymal stem cells (BMMSCs) derived apoptotic extracellular vesicles (ApoEVs) could regulate the polarization of mouse macrophage cell line RAW264.7 and whether BMMSCs derived ApoEVs could attenuate pro-inflammatory condition of RAW264.7 induced by Porphyromonas gingivalis lipopolysaccharide (Pg-LPS), so as to provide experimental evidence and theoretical basis for using BMMSCs derived ApoEVs as a method to treat periodontitis. Methods: The Operetta CLS high-content analysis system was used to observe the time-dependent apoptosis process of BMMSCs. Besides, field emission scanning electron microscopy (FESEM), dynamic light scattering technology and streaming potential method were used to measure the surface characteristics of BMMSCs derived ApoEVs. The Operetta CLS high-content analysis system was used to observe the process of RAW264.7 phagocyting 5-carboxy-tetramethylrhodamine, succinimidyl ester (5-TAMRA-SE) labeled ApoEVs. Real-time quantitative PCR was used to detect the mRNA expression of arginase-1 (Arg-1). Cell immunofluorescence and Western blotting were used to detect the number of inducible nitric oxide synthase (iNOS)(+) macrophages and iNOS protein expression level in each experiment group. Enzyme linked immunosorbent assay was used to detect tumor necrosis factro-α (TNF-α) level in the Pg-LPS induced pro-inflammatory macrophage culture supernatant in each experiment group. Results: After treating with 0.5 μmol/L staurosporine for 12 hours, mouse BMMSCs underwent shrinking with obvious vesicles structure around. The FESEM showed the ApoEVs were in spherical shapes. The size range of ApoEVs was about 100-1 000 nm and the average Zeta potential was -16.6 mV. The Operetta CLS high-content analysis system showed RAW264.7 could phagocytose 5-TAMRA-SE labeled ApoEVs by pseudopodia. The relative mRNA expression of Arg-1 was significantly increased in RAW 264.7 after being treated with interleukin 4 (IL-4) and ApoEVs (261.97±15.91) compared to that with IL-4 alone (115.29±15.42) (P<0.01). Cell immunofluorescence showed that ApoEVs could reduce the number of iNOS(+) macrophages induced by Pg-LPS (39.33±4.70) comparing to those without ApoEVs (95.33±4.70) (P=0.007). In the meanwhile, ApoEVs could also down-regulate the iNOS protein level of macrophages induced by Pg-LPS (5.84±1.05) comparing to those without ApoEVs (14.91±3.87) (P<0.01). Besides, ApoEVs could also reduce the TNF-α secretion in the culture supernatant of pro-inflammatory macrophages induced by Pg-LPS [(21 899.71±409.73) ng/L] comparing to those without ApoEVs [(71 296.50±2 344.22) ng/L] (P=0.003). Conclusions: BMMSCs derived ApoEVs could regulate the polarization of macrophages and could also attenuate the pro-inflammatory condition of macrophages induced by Pg-LPS.

[Role and mechanism of low-dose lipopolysaccharide-treated human periodontal ligament stem cells on the expression of macrophage pro-inflammatory factors]

Objective: To investigate the effect of low dose lipopolysaccharide (LPS)-treated human periodontal ligament stem cells (HPDLSC) on the expression of macrophage pro-inflammatory factors and the mechanism involved. Methods: The primary HPDLSCs were obtained from healthy third molar periodontal ligament tissue. Phosphate buffer saline (PBS), 100 μg/L or 10 mg/L of LPS were used to treat HPDLSCs for 48 h, and their conditioned media were respectively co-cultured with THP-1-derived macrophages for 48 h. The corresponding experimental groups were PBS-treated HPDLSC-derived conditioned medium (CM-C) group, low dose LPS-treated HPDLSC-derived conditioned medium (CM-L) group, and high dose LPS-treated HPDLSC-derived conditioned medium (CM-H) group. Quantitative real-time PCR was performed to explore the mRNA expressions of macrophage interleukin (IL)-6, IL-8, IL-12, tumor necrosis factor-α (TNF-α) in the CM-C, CM-L and CM-H groups, and the expressions of nuclear factor (erythroid-derived 2)-like 2 (NRF2), glutamate-cysteine ligase catalytic subunit (GCLC), NAD(P)H quinone dehydrogenase 1 (NQO1) and heme oxygenase 1 (HO-1) in the CM-C and CM-L groups. Meanwhile, Western blotting was used to detect the change of nuclear and cytoplasmic NRF2 and the levels of GCLC and HO-1 in the CM-C and CM-L groups. The 2', 7'-dichlorofluorescein probe was adopted to detect the reactive oxygen species (ROS) levels of macrophages in the CM-C and CM-L groups and the data were characterized by the mean fluorescent intensity (MFI). Results: The mRNA expressions of macrophage pro-inflammatory factors IL-6, IL-8, IL-12 and TNF-α in the CM-H group (2.332±0.594, 3.601±0.639, 2.120±0.677 and 2.468±0.236) were significantly upregulated compared with those in the CM-C group (1.000±0.321, 1.000±0.151, 1.000±0.059 and 1.000±0.095) (P<0.05); while the relative mRNA levels of IL-6, IL-12 and TNF-α in the CM-L group (0.056±0.002, 0.215±0.024 and 0.567±0.071) were much lower than those in the CM-C group (1.000±0.209, 1.000±0.220 and 1.000±0.220) (P<0.05). At the mRNA level, the expression of NRF2 was significantly increased in the CM-L group (1.864±0.198) compared with that in the CM-C group (1.000±0.094) (P<0.05). At the protein level, the cytoplasmic NRF2 and nuclear NRF2 were increased in CM-L group (1.175±0.104 and 1.308±0.082) compared with those in the CM-C group (1.000±0.025 and 1.000±0.049) (P<0.05). Furthermore, the antioxidative genes, i.e. GCLC and NQO1, localized in NRF2 downstream, were significantly upregulated in the CM-L group (1.786±0.278 and 1.444±0.078) compared with the CM-C group (1.000±0.139 and 1.000±0.226) (P<0.05). The protein levels of GCLC and HO-1 were augmented in the CM-L group (1.159±0.036 and 1.412±0.075) in contrast with those in the CM-C group (1.000±0.050 and 1.000±0.013) (P<0.05). In addition, the MFI in the CM-L group (123 419±1 302) was significantly lower than that in the CM-C group (139 193±1 241) (P<0.05). Conclusions: Low-dose LPS-treated HPDLSCs could regulate oxidative stress response through activating the NRF2 signaling pathway of macrophages and further downregulating the expressions of macrophage pro-inflammatory factors.

Measurement of the Cosmic Ray Helium Energy Spectrum from 70 GeV to 80 TeV with the DAMPE Space Mission

The measurement of the energy spectrum of cosmic ray helium nuclei from 70 GeV to 80 TeV using 4.5 years of data recorded by the Dark Matter Particle Explorer (DAMPE) is reported in this work. A hardening of the spectrum is observed at an energy of about 1.3 TeV, similar to previous observations. In addition, a spectral softening at about 34 TeV is revealed for the first time with large statistics and well controlled systematic uncertainties, with an overall significance of 4.3σ. The DAMPE spectral measurements of both cosmic protons and helium nuclei suggest a particle charge dependent softening energy, although with current uncertainties a dependence on the number of nucleons cannot be ruled out.

[Inflammatory periodontal stem cells mediate interleukin-1β secretion of macrophage by regulating macrophage endoplasmic reticulum stress]

Objective: To investigate the effect and mechanism of periodontal ligament stem cell (PDLSC) from inflammatory environment on the secretion of interleukin-1β (IL-1β) by macrophages. Methods: PDLSCs were pretreated with lipopolysaccharide (LPS) in order to simulate the inflammatory environment. Human monocyte cell line (THP-1) cells were treated with conditioned media collected from healthy and inflammatory PDLSCs respectively and divided into conditioned medium of health PDLSC (CM-H) group and conditioned medium of LPS-PDLSC (CM-LPS) group. After 24 h of co-culture, the condition media were abandoned and THP-1 cells were then cultured for another 24 h. The expression of IL-1β in THP-1 cells supernatant was detected by enzyme-linked immunosorbent assay (ELISA). Quantitative real time-PCR (qRT-PCR) was used to detect the expression of glucose regulated protein 78 (GRP78), activating transcription factor-6 (ATF6), inositol requiring enzyme 1 (IRE1), protein kinase R-like endoplasmic reticulum kinase (PERK), CCAAT enhancer binding protein homologous protein (CHOP), activating transcription factor-4 (ATF4) and X box binding protein 1 spliced (XBP1s), which were all related with endoplasmic reticulum stress (ERS), in THP-1 cells. The expressions of proteins GRP78 and CHOP were detected by Western blotting. Furthermore, THP-1 cells, which pretreated with ER inhibitor 4-phenylbutyrate (4-PBA) for intervention experiments were grouped by various concentrations of 4-PBA including groups 0 (control group), 1, 10 and 20 mmol/L and treated with condition medium of inflammatory PDLSC. ELISA was used to detect IL-1β expression and qRT-PCR to detect expression of ERS related genes. Results: ELISA results showed that the expression of IL-1β in THP-1 cells of group CM-LPS [(31.35±2.11) ng/L] was significantly higher than group CM-H [(8.19±1.51) ng/L] (t=12.60, P<0.01). qRT-PCR results showed that the relative expressions of GRP78, ATF6, IRE1, PERK, CHOP, ATF4 and XBP1s genes in THP-1 cells of group CM-LPS (1.782±0.070, 1.387±0.204, 1.404±0.119, 1.777±0.187, 1.325±0.156, 1.295±0.066 and 1.137±0.149, respectively) were significantly higher than those in group CM-H (P<0.05). In the 4-PBA intervention experiment, compared with group 0 mmol/L, the expressions of GRP78, IRE-1, ATF-6, PERK and CHOP were significantly lower in group 1, 10 and 20 mmol/L (P<0.05). Moreover, compared with control group [(31.23±1.98) ng/L], the expression of IL-1β in THP-1 cells were significantly lower in group 10 mmol/L [(21.20±0.37) ng/L] and group 20 mmol/L [(23.85±1.80) ng/L] (P<0.05) with ERS inhibited. Conclusions: PDLSC from inflammatory environment could promote IL-1β secretion of macrophages through upregulating macrophages ERS.

Deep learning for species identification of bolete mushrooms with two-dimensional correlation spectral (2DCOS) images

Bolete is well-known and widely consumed mushroom in the world. However, its medicinal properties and nutritional are completely different from one species to another. Therefore, the consumers need a fast and effective detection method to discriminate their species. A new method using directly digital images of two-dimensional correlation spectroscopy (2DCOS) for the species discrimination with deep learning is proposed in this paper. In our study, a total of 2054 fruiting bodies of 21 wild-grown bolete species were collected in 52 regions from 2011 to 2014. Firstly, we intercepted 1750-400 cm^-1 fingerprint regions of each species from their mid-infrared (MIR) spectra, and converted them to 2DCOS spectra with matlab2017b. At the same time, we developed a specific method for the calculation of the 2DCOS spectra. Secondly, we established a deep residual convolutional neural network (Resnet) with 1848 (90%) 2DCOS spectral images. Therein, the discrimination of the bolete species using directly 2DCOS spectral images instead of data matric from the spectra was first to be reported. The results displayed that the respective identification accuracy of these samples was 100% in the training set and 99.76% in the test set. Then, 203 samples were accurately discriminated in 206 (10%) samples of external validation set. Thirdly, we employed t-SNE method to visualize and evaluate the spectral dataset. The result indicated that most samples can be clustered according to different species. Finally, a smartphone applications (APP) was developed based on the established 2DCOS spectral images strategy, which can make the discrimination of bolete mushrooms more easily in practice. In conclusion, deep learning method by using directly 2DCOS spectral image was considered to be an innovative and feasible way for the species discrimination of bolete mushrooms. Moreover, this method may be generalized to other edible mushrooms, food, herb and agricultural products in the further research.

Geographical traceability and multielement analysis of edible and medicinal fungi: Taking Wolfiporia cocos (F.A. Wolf) Ryvarden and Gilb. as an example

Different geographical environment has a certain influence on the accumulation of fungi elements and chemical components. However, our knowledge is limited to elucidate the fungi elements in response to heterogeneous environmental and the quality differences among different habitats. Here, multielement analysis, FTIR spectrum, and feature-level fusion technique combined with chemometrics were used to study Wolfiporia cocos from different geographical areas, different sampling sites and different altitude sources. From the results, (1) there is significant difference in element content of samples from different sampling sites and no positive correlation with geographical ranges. (2) There is a correlation between elevation and elements, and relatively low elevation (<1,800 m) is conducive to the enrichment of elements. (3) From the perspective of elements, the W. cocos in Yuxi have relatively better quality. (4) FTIR and feature-level models can well realize origin identification. The SVM models are better than the PLS-DA models, and the feature-level model is better than the single FTIR models. In summary, this study demonstrated that the developed method was reliable and could realize the genuineness evaluation and origin identification of W. cocos. The results have implications for the establishment of the technology system of geographical traceability and the development of high-quality geographical indication products of W. cocos.

[Epidemiological research in the big data era: opportunities, challenges and prospectives]

Recent years with the rapid progress in high-throughput omics techniques, the accumulation of population cohorts and biobanks, great advances in internet and information technology, and the emerging tools for big data utilization, health care big data provide abundant data resources and broad research platforms for epidemiological research. We aimed to review the opportunities and challenges of epidemiological research in the era of big data, and explore the future development of epidemiology. Epidemiology should seize the opportunities, open up new directions, develop new methods, and promote the translation of research results into public health and clinical medicine, which will eventually realize the vision of "Healthy China".