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C32H44O6, monoclinic, P21 (no. 4), a = 12.2561 Å, b = 10.3674(4) Å, c = 23.3835(8) Å, β = 98.463°, V = 2938.85(19) Å3, Z = 2, Rgt(F) = 0.0602, wRref(F2) = 0.1537, T = 273(2) K.

C22H26O6, orthorhombic, P212121 (no. 19), a = 7.6648(5) Å, b = 11.2663(6) Å, c = 22.7321(7) Å, V = 1963.0(2) Å3, Z = 4, Rgt (F) = 0.0652, wRref (F 2) = 0.1399, T = 273(2) K.

Abstract Background Gene expression signatures can be used as prognostic biomarkers in various types of cancers. We aim to develop a gene signature for predicting the response to radiotherapy in glioma patients. Methods Radio-sensitive and radio-resistant glioma cell lines (M059J and M059K) were subjected to microarray analysis to screen for differentially expressed mRNAs. Additionally, we obtained 169 glioblastomas (GBM) samples and 5 normal samples from The Cancer Genome Atlas (TCGA) database, as well as 80 GBM samples and 4 normal samples from the GSE7696 set. The “DESeq2” R package was employed to identify differentially expressed genes (DEGs) between the normal brain samples and GBM samples. Combining the prognostic-related molecules identified from the TCGA, we developed a radiosensitivity-related prognostic risk signature (RRPRS) in the training set, which includes 152 patients with glioblastoma. Subsequently, we validated the reliability of the RRPRS in a validation set containing 616 patients with glioma from the TCGA database, as well as an internal validation set consisting of 31 glioblastoma patients from the Nanfang Hospital, Southern Medical University. Results Based on the microarray and LASSO COX regression analysis, we developed a nine-gene radiosensitivity-related prognostic risk signature. Patients with glioma were divided into high- or low-risk groups based on the median risk score. The Kaplan–Meier survival analysis showed that the progression-free survival (PFS) of the high-risk group was significantly shorter. The signature accurately predicted PFS as assessed by time-dependent receiver operating characteristic curve (ROC) analyses. Stratified analysis demonstrated that the signature is specific to predict the outcome of patients who were treated using radiotherapy. Univariate and multivariate Cox regression analysis revealed that the predictor was an independent predictor for the prognosis of patients with glioma. The prognostic nomograms accompanied by calibration curves displayed the 1-, 2-, and 3-year PFS and OS in patients with glioma. Conclusion Our study established a new nine-gene radiosensitivity-related prognostic risk signature that can predict the prognosis of patients with glioma who received radiotherapy. The nomogram showed great potential to predict the prognosis of patients with glioma treated using radiotherapy.

The physiological processes involved in adaptation to osmotic pressure in euryhaline crustaceans are highly energy demanding, but the effects of dietary lipids (fat) on low salinity adaptations have not been well evaluated. In the present study, a total of 120 mud crabs (Scylla paramamosain, BW = 17.87 ± 1.49 g) were fed control and high-fat (HF) diets, at both medium salinity (23‰) and low salinity (4‰) for 6 wk, and each treatment had 3 replicates with each replicate containing 10 crabs. The results indicated that a HF diet significantly mitigated the reduction in survival rate, percent weight gain and feed efficiency induced by low salinity (P

C28H41NO2, monoclinic, C2 (no. 5), a = 4.8622(5) Å, b = 6.7853(7) Å, c = 14.3349(17) Å, β = 96.556(3)°, V = 469.84(9) Å3, Z = 2, R gt(F) = 0.0482, wRref (F 2) = 0.1257, T = 284(2) K.

C20H32O3, monoclinic, P21 (no. 4), a = 7.8981(17) Å, b = 10.302(2) Å, c = 11.028(3) Å, β = 90.020(2)°, V = 897.3(3) Å3, Z = 2, R gt(F) = 0.0603, wR ref(F 2) = 0.1342, T = 273(2) K.

Objective No consensus has been reached regarding optimal implantation for a syndesmotic screw. Thus, we aimed to explore the feasibility of a reliable and static fibular incisura plane reference for ideal syndesmotic screw placement. Methods A retrospective review of computed tomography (CT) scans of 42 uninjured adult ankles with foot fractures were analyzed to measure the tibiofibular vertical distance (TFVD) at 2.5 cm proximal to the plafond from August 2016 to June 2017 in our hospital. The patients (20 females, 22 males) were divided into four groups according to their TFVD: 0–1, 1–2, 2–3, and 3–4 mm, and patients in each group were counted. We retrospectively assessed 41 patients (15 females, 26 males) who underwent syndesmotic screw fixation for ankle fractures from December 2015 to June 2020. We performed t‐testing of two independent samples to determine the differences in the angle between the anatomic axis of the syndesmosis and screw axis (AAS) and ankle function using the American Orthopaedic Foot and Ankle Society (AOFAS) score at 3 and 6 months postoperatively between the conventional (20 patients) and K‐wire marker (21 patients) groups. The correlation between the AAS and AOFAS score was analyzed. Results The TFVD measured 2.23 ± 1.01 mm at 2.5 cm proximal to the plafond, and occurred at 25% of the distance from 2 to 3 mm in 47.6% of the patients. This new technique decreased AAS deformation by 62%, from 13.01° ± 2.84° to 4.89° ± 2.43°, in the conventional group (p

C30H40O5, orthorhombic, P212121 (no. 19), a = 6.5012(3) Å, b = 15.3297(7) Å, c = 21.8138(14) Å, V = 2672.3(2) Å3, Z = 4, Rgt(F) = 0.0537, wRref(F2) = 0.1355, T = 273(2) K.

C24H30O7, orthorhombic, P212121 (no. 19), a = 11.4194(5) Å, b = 13.4657(6) Å, c = 14.7549(7) Å, V = 2268.86(18) Å3, Z = 4, Rgt(F) = 0.0535, wRref(F2) = 0.1239, T = 273(2) K.

The reform of digitalization has deeply influenced the development mode and production methods of traditional production in China. However, the impact of digitalization on the management performance of Chinese listed companies are not well investigated and there is a gap in the establishment of digitalization effective measurement variable. In order to fill this gap, this article constructs a variable to measure the application degree of “digitalization” at the company level. By analyzing the text of the annual reports of Chinese listed companies from 2009 to 2020, the effective variables to measure “digitalization” are determined. Based on this, the development status and determinants of enterprise digital applications and the impact of digitalization on enterprise performance are discussed. Thus, by analyzing the panel data of these companies, the relationship among the age of the enterprise, the knowledge level of the board of directors, the proportion of fixed assets, the company’s assets, and the degree of enterprise digitalization are evaluated. At last, according to the evaluated results, the relationship between the degree of digitalization and the performance of enterprises is analyzed. In this article, our analysis helps to solve the “IT production paradox” problem, and also to provides data and theoretical support for digitalization to improve corporate performance to a certain extent. Furthermore, the digitalization measurement variable laid out in this article provides a foundation for future research on the relationship between digitalization and corporate performance.

Glioma is the most common malignancy of the nervous system with high mortality rates. The MS4A family members have been reported as potential prognostic biomarkers in several cancers; however, the relationship between the MS4A family and glioma has not been clearly confirmed. In our study, we explored the prognostic value of MS4As as well as their potential pro-cancer mechanisms of glioma. Using bioinformatics analysis methods based on the data from public databases, we found that the expression of MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B was significantly overexpressed in glioma tissues compared with that of normal tissues. The Kaplan–Meier method and Cox proportional hazards models revealed that high levels of MS4As can be associated with a poorer prognosis; TMEM176A, TMEM176B, age, WHO grade, and IDH status were identified as independent prognostic factors. Enrichment analysis predicted that MS4As were related to tumor-related pathways and immune response, which might regulate the process of MS4As promoting tumorigenesis. Additionally, we analyzed the correlations of MS4A expression with immune cells and immune inhibitory molecules. Finally, data from the cell culture suggested that knockdown of the TMEM176B gene contributes to the decreased proliferation and migration of glioma cells. In conclusion, MS4A4A, MS4A4E, MS4A6A, MS4A7, TMEM176A, and TMEM176B may act as potential diagnostic or prognostic biomarkers in glioma and play a role in forming the immune microenvironment in gliomas.

Abstract Background Thymocyte selection‐associated high mobility group box (TOX) plays a crucial role on the development of innate immunity and tumor microenvironment. This study aims to explore the prognostic potential of TOX and comprehensively analyze the correlations between TOX, immune infiltration, and T cells function in diverse cancers particularly lung adenocarcinoma (LUAD). Methods TIMER was used to analyze TOX expression in different cancers. Potential prognostic value of TOX was evaluated by the PrognoScan, Kaplan‐Meier Plotter, and GEPIA2. The relationships between TOX, immune infiltration, and related gene marker sets were analyzed by TIMER and GEPIA2. Single‐cell RNA‐seq for T cells in LUAD was analyzed to further investigate the correlations between TOX expression and different T cells populations. Results TOX downregulates in most of the cancer types and correlates with poor prognosis in LUAD. TOX shows significant impacts on survival of LUAD with early stage, ever‐smoking, or low‐TMB status. Increased TOX expression positively correlates with high immune infiltration levels in most of the immune cells and functional T cells including exhausted T cells. Moreover, multiple key genes of exhausted T cells comprising PD‐1, TIM‐3, TIGHT, and CXCL13 have remarkable interaction with TOX. Specifically, TOX is observed with high enrichment in exhausted CD4+ and CD8+ T cells populations in single‐cell RNA‐seq analysis for LUAD. Conclusion TOX is a prognosis‐related biomarker for multiple cancer types especially LUAD. Increased TOX expression significantly increase immune infiltration levels in most of the immune cells comprising CD8+ T cells, CD4+ T cells, mast cells, and functional T cells. Moreover, we verified that TOX highly correlates with exhausted T cells and is probable a critical regulator promoted T cells exhaustion in LUAD. Detection of TOX expression could help to predict prognosis and regulating TOX expression in exhausted T cells may offer a novel strategy in maximizing immunotherapy efficacy for LUAD.

The recognition, identification, and differentiation of closely related plant species present significant and notorious challenges to taxonomists. The Maddenia group of Prunus, which comprises four to seven species, is an example of a group in which species delimitation and phylogenetic reconstruction have been difficult, due to the lack of clear morphological distinctions, limited sampling, and low informativeness of molecular evidence. Thus, the precise number of species in the group and the relationships among them remain unclear. Here, we used genome skimming to generate the DNA sequence data for 22 samples, including 17 Maddenia individuals and five outgroups in Amygdaloideae of Rosaceae, from which we assembled the plastome and 446 single-copy nuclear (SCN) genes for each sample. The phylogenetic relationships of the Maddenia group were then reconstructed using both concatenated and coalescent-based methods. We also identified eight highly variable regions and detected simple sequence repeats (SSRs) and repeat sequences in the Maddenia species plastomes. The phylogenetic analysis based on the complete plastomes strongly supported three main subclades in the Maddenia group of Prunus, while five subclades were recognized based on the nuclear tree. The phylogenetic network analysis detected six hybridization events. Integrating the nuclear and morphological evidence, we proposed to recognize five species within the Maddenia group, i.e., Prunus fujianensis, P. himalayana, P. gongshanensis, P. hypoleuca, and P. hypoxantha. Within this group, the first three species are well-supported, while the gene flow occurring throughout the Maddenia group seems to be especially frequent between P. hypoleuca and P. hypoxantha, eroding the barrier between them. The phylogenetic trees based on eight concatenated hypervariable regions had a similar topology with the complete plastomes, showing their potential as molecular markers and effective barcodes for further phylogeographic studies on Maddenia.

Car-following model is indispensable to evaluate the characteristics of car-following behaviors. Through an analysis and comparison of data-driven and theoretically driven car-following models, it shows that the data-driven model has poor interpretability and high quality of training data set is required, while for the theoretical-driven model, it is unable to describe the individualized features and models of the driver so as to a low model accuracy. To solve the problem, a novel modelling method is proposed using adaptive Kalman filter algorithm to integrate the long-short-time memory neural network (LSTM) data-driven model with the IDM theoretical-driven model to build the car-following model. Test results of real driving data from a single driver prove that the fusion car-following model has higher accuracy than a single model, while at the same time highlighting the driver's personality compared to the IDM model. Besides, it improves the generalization ability of the traditional data model, which is reflected by better fitting in the extreme case (for example, the stable state when the acceleration, velocity is zero). Finally, the trajectory simulation results show that the proposed integrated data-driven car-following model can better simulate the micro-traffic behavior of car following.

The fault diagnosis of power transformers is a challenging problem. The massive multisource fault is heterogeneous, the type of fault is undetermined sometimes, and one device has only met a few kinds of faults in the past. We propose a fault diagnosis method based on deep neural networks and a semi-supervised transfer learning framework called adaptive reinforcement (AR) to solve the above limitations. The innovation of this framework consists of its enhancement of the consistency regularization algorithm. The experiments were conducted on real-world 110 kV power transformers’ three-phase fault grounding currents of the iron cores from various devices with four types of faults: Phases A, B, C and ABC to ground. We trained the model on the source domain and then transferred the model to the target domain, which included the unbalanced and undefined fault datasets. The results show that our proposed model reaches over 95% accuracy in classifying the type of fault and outperforms other popular networks. Our AR framework fits target devices’ fault data with fewer dozen epochs than other novel semi-supervised techniques. Combining the deep neural network and the AR framework helps diagnose the power transformers, which lack diagnosis knowledge, with much less training time and reliable accuracy.

It is well-known that genomic mutational analysis plays a significant role in patients with NSCLC for personalized treatment. Given the increasing use of stereotactic radiosurgery (SRS) for brain metastases (BM), there is an emerging need for more precise assessment of survival outcomes after SRS. Patients with BM and treated by SRS were eligible in this study. The primary endpoint was overall survival (OS). Cox regression models were used to identify independent prognostic factors. A survival predictive nomogram was developed and evaluated by Concordance-index (C-index), area under the curve (AUC), and calibration curve. From January 2016 to December 2019, a total of 356 BM patients were eligible. The median OS was 17.7 months [95% confidence interval (CI) 15.5–19.9] and the actual OS at 1- and 2-years measured 63.2 and 37.6%, respectively. A nomogram for OS was developed by incorporating four independent prognostic factors: Karnofsky Performance Score, cumulative tumor volume, gene mutation status, and serum lactate dehydrogenase. The nomogram was validated in a separate cohort and demonstrated good calibration and good discriminative ability (C-index = 0.780, AUC = 0.784). The prognostic accuracy of the nomogram (0.792) was considerably enhanced when compared with classical prognostic indices, including the Graded Prognostic Assessment (0.708), recursive partitioning analysis (0.587), and the SRS (0.536). Kaplan–Meier curves showed significant differences in OS among the stratified low-, median- and high-risk groups (P < 0.001). In conclusion, we developed and validated an individualized prognostic nomogram by integrating physiological, volumetric, clinical chemistry, and molecular biological surrogates. Although this nomogram should be validated by independent external study, it has a potential to facilitate more precise risk-stratifications to guide personalized treatment for BM.

During the normalization phase of the COVID-19 epidemic, society has gradually reverted to using building space, especially for public buildings, e.g., offices. Prevention of airborne pollutants has emerged as a major challenge. Ventilation strategies can contribute to mitigating the spread of airborne disease in an indoor environment, including increasing supply air rate, modifying ventilation mode, etc. The larger ventilation rate can inevitably lead to high energy consumption, which may be also ineffective in reducing infection risk. As a critical factor affecting the spread of viral contaminant, the potential of ventilation modes for control of COVID-19 should be explored. This study compared several ventilation strategies in the office, including mixing ventilation (MV), zone ventilation (ZV), stratum ventilation (SV) and displacement ventilation (DV), through analyzing ventilation performance and infection risk for the optimal one. By using ANSYS Fluent, the distributions of airflow and pollutant were simulated under various ventilation modes and infected occupants. The SV showed greater performance in mitigating infection disease spread than MV, ZV and DV, with an air distribution performance index (ADPI) of 90.5% and minimum infection risk of 13%. This work can provide a reference for development of ventilation strategies in public space oriented the prevention of COVID-19.

Phylogenetic analyses were performed using multiple nuclear (ITS and ETS) and chloroplast regions (ndhF-trnL, psbA-trnH, psbD-trnT, and trnT-trnL) to test the monophyly of Aconitum subgen. Lycoctonum (Ranunculaceae) and reconstruct the phylogenetic relationships within the subgenus. The subgenus as currently circumscribed is revealed to be polyphyletic. To achieve its monophyly, sect. Galeata and sect. Fletcherum, both being unispecific and each having a unique array of characters (the latter even having the aberrant base chromosome number of x = 6), must be removed from the subgenus. The subgenus Lycoctonum should thus be redefined to include only two sections, the unispecific sect. Alatospermum and the relatively species-rich sect. Lycoctonum. The section Alatospermum, which is both morphologically and karyologically in the primitive condition, is resolved as the first diverging lineage of the subgenus Lycoctonum clade. The monophyly of sect. Lycoctonum is strongly supported, but all the ten series currently recognized within the section are revealed to be para- or poly-phyletic. Five major clades are recovered within the section. We propose to treat them as five series: ser. Crassiflora, ser. Scaposa, ser. Volubilia, ser. Longicassidata, and ser. Lycoctonia. Thus, a formal reclassification of subgen. Lycoctonum is presented, which involves segregating both sect. Galeata and sect. Fletcherum from the subgenus as two independent subgenera within the genus Aconitum, reinstating one series (ser. Crassiflora) and abolishing six series (ser. Laevia, ser. Longibracteolata, ser. Micrantha, ser. Ranunculoidea, ser. Reclinata, and ser. Umbrosa) within sect. Lycoctonum. The series affiliation of some species within the section is adjusted accordingly.

Due to its agility, flexibility and accuracy, airborne repeat-pass Interferometric Synthetic Aperture Radar (InSAR) is capable of overcoming the disadvantages of long revisit time and low resolution in space-borne SAR interferometry, and play an irreplaceable role in monitoring the deformation of landslides, volcanoes, earthquakes, etc. In this paper, the history and status in the world wide about the technology of airborne repeat-pass SAR interferometry are reviewed detailedly. Then after the accuracy of this technology is analyzed, its key problems in practice are presented, and the related researches in this field are also introduced comprehensively. The development trend and the prospect of this technology are also described in this paper. Finally, it is pointed that several problems still need to be studied further for accurate parameter inversion.

motion errors, frequently occur in SAR images. For airborne SAR system with very high resolution and airborne repeat-pass SAR interferometry, the residual motion errors must be estimated and compensated. Multi-squint Technique with Point Targets (MTPT) is able to estimate the residual motion errors for an individual SAR image, but errors in the platform velocity and the slant range will deteriorate the accuracy of the method. Based on the detailed analysis of the velocity and slant range to residual motion error estimation, simulated and real SAR data are used to validate it in this paper. It is also pointed out that though MTPT is able to estimate the errors in the velocity and slant range, it is sensitive to the phase error. Therefore, it is advised that the errors in the velocity and slant range should be removed with other precise method before MTPT is utilized to estimate the residual motion errors.

Senecio changii (Asteraceae: Senecioneae), a new species from Muli, Sichuan, southwestern China, is described. It is distinguished in Chinese Senecio s.s. by having lyrate-pinnatisect to pinnatisect leaves and a single terminal large discoid capitulum which is somewhat nodding. Evidence from floral micromorphology, karyology and molecular phylogenetic analyses based on the nuclear ITS/ETS sequence data all support its membership within Senecio s.s.