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Rui Shi, Ziwei Wang, Jun Zhang, Zhicheng Yu, Lanfen An, Sitian Wei, Dilu Feng, Hongbo Wang Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, People’s Republic of ChinaCorrespondence: Dilu Feng; Hongbo WangDepartment of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430022, People’s Republic of ChinaTel +86 027 85350583Fax +86 278 572 6362Email fengdilu@126.com; hb_wang1969@sina.comPurpose: Endometrial cancer (EC) is a common gynaecologic malignancy with an increasing incidence rate and mortality in recent years. N6-methylandenosine (m6A)-related long noncoding RNA (lncRNA) plays a vital role in EC, emerging as one of the most abundant RNA modifications.Materials and Methods: The Cancer Genome Atlas (TCGA) database and UCSC Xena were used to download data related to EC. Survival and univariate and multifactorial prognostic analyses were performed for m6A-related lncRNAs. The expression levels of the three lncRNAs were verified using q-PCR. A nomogram was used to create a clinical tool to assess overall survival. To investigate the relationship between m6A-related lncRNA and EC, we downloaded differential genes related to EC from the TCGA database and mined three m6A-related lncRNAs, namely SCARNA9, TRAF3IP2-AS1, and AL133243.2. The data were categorized into high- and low-risk groups based on m6A-associated lncRNA.Results: Survival analysis revealed that the high-risk group had a lower survival rate. Survival analysis of three m6A-associated lncRNAs revealed that cases with high expression of SCARNA9 tended to have a poorer prognosis, whereas the opposite was true for TRAF3IP2-AS1, AL133243.2. Univariate and multifactorial prognostic analyses suggested statistical differences in patients’ age, FIGO stage, pathological grade, risk score, and prognosis of EC, which was confirmed by results of the separate prognostic factor analysis for the three lncRNAs. Risk status was validated as an independent prognostic indicator, and the prognostic nomogram combined patient age, pathological stage, and FIGO classification to assess 3– 5-year survival. Cases from high- and low-risk groups were analysed for the tumour microenvironment and immune cell scores, and stromal cell scores were found to be lower in the high-risk group. Correlations were analysed using different databases for immune cell classification.Conclusion: m6A-related lncRNAs may play a key role in the diagnosis and treatment of EC as targets of prognosis and the immune microenvironment.Keywords: N6-methylandenosine, long noncoding RNAs, endometrial cancer, tumour microenvironment

Zhicheng Yu,* Sitian Wei,* Jun Zhang, Rui Shi, Lanfen An, Dilu Feng, Hongbo Wang Department of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hongbo WangDepartment of Obstetrics and Gynecology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of ChinaTel +86 137-2022-8749Fax +86 027 857-26114Email hb_wang1969@sina.comObjective: Existing prognostic models for endometrial cancer are short of facility and effective validation. In this study, we aim to develop and validate a novel prognostic model for endometrial cancer based on clinical characteristics.Methods: The clinical data such as age, BMI (body mass index), FIGO stage, surgical approach, myometrial invasion, grade, lymph node metastasis, pathology and menopause status were collected for constructing and validating the prognostic model from The Cancer Genome Atlas (TCGA) and Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, respectively. COX regression and the least absolute shrinkage and selection operator (LASSO) COX were applied to identify the significant predictors of overall survival (OS) and construct the prognostic model. The discrimination, calibration, and clinical usefulness of the model were evaluated in both cohorts.Results: Three hundred and sixty-seven and 286 EC patients were collected for training and validation cohort, respectively. A clinical prognostic model integrating six clinical variables including age, BMI, FIGO stage, surgical approach, myometrial invasion and grade was established. K-M analysis shows a significant difference between the low- and high-risk groups. The area under the receiver operating characteristic curve (AUC-ROC) was 0.775 (95% CI, 0.708 to 0.843) and 0.870 (95% CI, 0.758 to 0.982) for the training and validation cohorts which indicating reliable discrimination. The calibration curve revealed excellent predictive accuracy and the Hosmer–Lemeshow test also verified this. Decision curve analysis (DCA) for the prognostic model indicated that it would add more benefits than either the detect-all-patients scheme or the detect-none scheme. In addition, our model has a superior AUC comparing with any single factor as predicting OS.Conclusion: Our predictive model offers a convenient and accurate tool for clinicians to estimate the prognosis of EC patients.Keywords: clinical characteristics, endometrial cancer, prognostic model, TCGA

Objective: The outbreak of Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) threatens a surging number of community groups within society, including women actively breastfeeding. Breastfeeding involves intimate behaviors, a major transmission route of SARS-CoV-2, and is integral to the close mother-baby relationship highly correlated with maternal psychological status. Materials and Methods: Twenty-three pregnant women and puerperae with either confirmed or suspected diagnoses of COVID-19 were enrolled in the study. The clinical characteristics and outcomes of the mothers and neonates were recorded. The presence of SARS-CoV-2, IgG, and IgM in breast milk, maternal blood, and infant blood, together with feeding patterns, was assessed within 1 month after delivery. Feeding patterns and maternal psychological status were also recorded in the second follow-up. Results: No positive detection of SARS-CoV-2 was found in neonates. All breast milk samples were negative for the detection of SARS-CoV-2. The presence of IgM for SARS-CoV-2 in breast milk was correlated with IgM presence in the maternal blood. The results of IgG detection for SARS-CoV-2 were negative in all breast milk samples. All infants were in a healthy condition in two follow-ups, and antibody tests for SARS-CoV-2 were negative. The rate of breast milk feeding increased during two follow-ups. All mothers receiving a second follow-up experienced negative psychological factors and status. Conclusions: Our findings support the feasibility of breastfeeding in women infected with SARS-CoV-2. The additional negative psychological status of mothers due to COVID-19 should also be considered during the puerperium period.

In this work, the light coupling efficiency of organic light-emitting diode (OLED) and polymer optical waveguide integrated device was improved by the grating coupler. To maximize light coupling efficiency, the grating coupler was optimized by finite-difference time-domain (FDTD) method. Based on the simulation results, the grating coupler was fabricated via laser interference lithography process and an OLED was integrated on the surface of it. Comparing the integrated devices without and with grating coupler, light coupling efficiency of the grating-based integrated device was improved by about 5%. The proposed integrated device has the potential application for low-cost and flexible monolithic optical sensors.

Behavioral sensitization is a progressive increase in locomotor or stereotypic behaviours in response to drugs. It is believed to contribute to the reinforcing properties of drugs and to play an important role in relapse after cessation of drug abuse. However, the mechanism underlying this behaviour remains poorly understood. In this study, we showed that mTOR signaling was activated during the expression of behavioral sensitization to cocaine and that intraperitoneal or intra-nucleus accumbens (NAc) treatment with rapamycin, a specific mTOR inhibitor, attenuated cocaine-induced behavioural sensitization. Cocaine significantly modified brain lipid profiles in the NAc of cocaine-sensitized mice and markedly elevated the levels of phosphatidylinositol-4-monophosphates (PIPs), including PIP, PIP(2,) and PIP(3). The behavioural effect of cocaine was attenuated by intra-NAc administration of LY294002, an AKT-specific inhibitor, suggesting that PIPs may contribute to mTOR activation in response to cocaine. An RNA-sequencing analysis of the downstream effectors of mTOR signalling revealed that cocaine significantly decreased the expression of SynDIG1, a known substrate of mTOR signalling, and decreased the surface expression of GluA2. In contrast, AAV-mediated SynDIG1 overexpression in NAc attenuated intracellular GluA2 internalization by promoting the SynDIG1–GluA2 interaction, thus maintaining GluA2 surface expression and repressing cocaine-induced behaviours. In conclusion, NAc SynDIG1 may play a negative regulatory role in cocaine-induced behavioural sensitization by regulating synaptic surface expression of GluA2.

Background The carcinogenic effect of NUP37 has been reported recently in a variety of tumors, but its research in the field of glioma has not been paid attention. The main purpose of this study is to reveal the relationship between NUP37 and prognosis or clinical characteristics of glioma patients. Methods First, as a retrospective study, this study included thousands of tissue samples based on a variety of public databases and clinicopathological tissues. Second, a series of bioinformatics analysis methods were used to analyze the NUP37 and glioma samples from multiple databases such as the CGGA, TCGA, GEO, HPA, and GEPIA. Third, to analyze the relationship between the expression level of NUP37 in tumor tissues and cells and a variety of clinical prognostic molecular characteristics, whether it can be an independent risk factor leading to poor prognosis in glioma and whether it has clinical diagnostic value; GSEA was used to analyze the cancer‐related signaling pathways that may be activated by high expression of NUP37. Fifth, CMap was used to analyze small molecule drugs that may inhibit NUP37 expression. Finally, the meta‐analysis of thousands of tissue samples from seven datasets and cell proliferation and migration experiments confirmed that NUP37 has a malignant effect on glioma. Results NUP37 is highly expressed in glioma patient tissues and glioma cells, significantly correlates with reduced overall survival, and may serve as an independent prognostic factor with some diagnostic value. Silencing NUP37 suppresses malignant biological behaviors of glioma cells. 4 small molecule drugs that had potential targeting inhibitory effects on NUP37 overexpression. Conclusions This study demonstrates for the first time a malignant role of NUP37 in glioma and provides a vision to unravel the complex pathological mechanisms of glioma and a potentially valuable biomarker for implementing individualized diagnosis and treatment of glioma., The present study used a series of analytical methods and confirmed that the NUP37 expression level was elevated in gliomas and led to a poor prognosis of patients. We partially revealed the mechanism of NUP37 in glioma and provided a novel potential diagnostic and therapeutic target. ​

Recent studies show that the performance of deep convolutional neural network (CNN) applied to steganalysis is better than that of traditional methods. However, the existing network structure is still caused by artificial design, which may not be the optimal training network. This paper describes a deep residual network based on a neural architecture search (NAS) algorithm, to minimize the artificial design of network elements to achieve better detection results. In this algorithm, we add a long-span residual structure to the traditional layer of the residual structure, which can better capture the complex statistical information of digital images and actively enhance the signals from secret messages, which is suitable for distinguishing cover and stego images. Two of the most advanced steganographic algorithms, WOW (wavelet obtained weights) and SUNIWARD (spatial universal wavelet relative distortion), are used to evaluate the effectiveness of this model in the spatial domain. Compared with a recently proposed method based on CNN, our model achieves excellent performance on all tested algorithms for various payloads

Fuel consumption is an important factor to be considered in the process of weather routing. How to choose an appropriate route according to the requirements is particularly important. This paper proposes a method to optimize the ship weather routing. Based on the original genetic algorithm, the trigonometric function selection operator is introduced, the mutation operator is improved to increase the search range in the initial stage of the algorithm, and gradually narrow the search range in the middle and late stages of the algorithm, thus the convergence is sped up and the running time of the algorithm is reduced. Aiming at the incomplete ship speed fuel consumption comparison table, this paper uses SPSS (Statistical Product and Service Solutions) software to perform curve fitting and a curve with the best fitting degree is found. Then the curve equation is used to calculate the total fuel consumption of the case ship (S175 container ship) sailing through between the two ports Yokohama (35° N, 141° E) and San Francisco (37° N, 123° W), to verify the performance of the improved algorithm. Aiming at the minimum fuel consumption, the fuel consumption of the optimized route is reduced by 7.84% compared with that of the Rhumb Line.

Background: Lumbar paraspinal hemangiopericytoma is rare. The hemorrhagic nature of the tumor causes problems of hemostasis and makes the resection delicate. We report a rare case of lumbar paraspinal hemangiopericytoma managed with preoperative embolization. Clinical Case: It is about a woman of 31 years, admitted for a large left lumbar paraspinal mass that evolved for 6 years. The clinical exam showed an asymmetry of the left paraspinal muscle. The mass painless was extended from the lumbar region. The neurological exam was normal. MRI showed the left large paraspinal mass tissue. It was extended from lumbar vertebrae, L1 to L4, and measured 100 × 50 × 50 mm. It was an iso-intense signal on T1-weighted with strong enhancement after gadolinium. It was hypervascular and supplied by left intercostal T12, L1, and L2 pedicles. The complete exclusion of the hyper-vascular left paraspinal tumor was obtained after selective embolization of the artery left L1 of the pedicle of the intercostal left L1 and trunks intercostal T12 and L2 left. The total resection of a mass encapsulated was performed. The operative outcome was good. The histology concluded to a hemangiopericytoma. No chemotherapy or radiotherapy was prescribed. After 5 years, the patient was asymptomatic. MRI control confirmed tumor resection with a residue at the level of the left intervertebral foramen L1 - L2. Conclusion: Lumbar paraspinal hemangiopericytoma is an extremely rare tumor. Selective preoperative embolization is recommended before the resection of large tumors to reduce vascular supply. A follow-up extended for these patients is necessary, given the frequency of recurrences.

In this work, we present the performance improved InGaZnO thin film transistors by inserting low temperature processed 10 nm thick SiOCH buffer layers between SiNx insulator and InGaZnO channel layer. The influences of oxygen flow rate during the deposition of SiOCH buffer layer have been intensively investigated. Basing on the analysis of hall effect measurement and Fourier transform infrared spectrum, the SiOCH buffer layer can effectively increase the carrier concentration of the channel layer by the hydrogen doping due to re-sputtering and diffusion effect. The InGaZnO thin film transistor with buffer layer exhibits an enhanced performance with mobility of 13.09 cm2/vs, threshold voltage of −0.55 V and Ion/Ioff over 106.

Response characteristics of key strata during the periodic weighting process in Dongjiahe coal mine were investigated using micro-seismic (MS) monitoring. Fracture types of key strata were identified through the moment tensor inversion. Finally, fracture mechanism of roof key strata was revealed from a microscopic viewpoint. The results show that there are three concentrations of MS events distributed along the dip direction. And two MS event clusters were formed in “pairs” before and behind the working face. Along the strike direction, tensile and shear factures occur in front of the working face with a dip angle of 54°, while the micro-fractures are mainly mixed and partial shear types behind the working face. By contrast, the rock fracture usually occurs behind the working face along the dip direction. The micro-fractures are mainly tensile and mixed types before fracturing compared to mainly mixed and shear fractures with slight tensile ones after fracturing. The fracture pattern basically conforms to the “O-X” type. The X-shaped fracture extends outward with an angle of 46° with the due north. The findings in this paper provide a theoretical reference for strata behaviours and hazard risk assessment under similar conditions.

Developing multimodal wearable textile sensors to simulate the complex human skin characteristics is central for healthcare, electronic skins, artificial intelligence and biomedical electronic applications. In this paper, stretchable piezoresistive carbon nanotubes-embedded nanofiber sensing yarns are successfully produced and mechanically robust enough to be woven to a wearable textile sensor that can detect and differentiate the multiple mechanical stimuli of pressure, stretching and bending. The smart nanofiber sensing yarn is obtained by wrapping piezoresistive elastic nanofibers onto a stretchable fiber-shaped core electrode with a facile electrospinning technique. The delicate hierarchical structure of this textile sensor ranges from the 1D macroscopic yarns to the submicron elastic nanofibers and internal nanoscale CNT percolation networks. This type of sensor offers a relatively larger contact area, multiple contact sites and larger deformation space for multimodal sensing various mechanical stimuli with improved sensitivity and broad sensing range. The textile-based sensor can be conformally attached to complex surfaces or integrated into a textile, demonstrating an excellent capability of continuous transient detection and differentiation of dynamic human movements. Moreover, a textile sensing platform is successfully integrated for spatially mapping the pressure and strain distribution, which makes it a promising candidate for electronic textiles and wearable devices.

Exosomes, nanoscale vesicles with a diameter of 30 to 150 nm, are composed of a lipid bilayer, protein, and genetic material. Exosomes are secreted by virtually all types of cells in the human body. They have key functions in cell-to-cell communication, immune regulation, inflammatory response, and neovascularization. Mounting evidence indicates that exosomes play an important role in various diseases, such as cancer, cardiovascular diseases, and brain diseases; however, the role that exosomes play in eye diseases has not yet been rigorously studied. This review covers current exosome research as it relates to ocular diseases including diabetic retinopathy, age-related macular degeneration, autoimmune uveitis, glaucoma, traumatic optic neuropathies, corneal diseases, retinopathy of prematurity, and uveal melanoma. In addition, we discuss recent advances in the biological functions of exosomes, focusing on the toxicity of exosomes and the use of exosomes as biomarkers and drug delivery vesicles. Finally, we summarize the primary considerations and challenges to be taken into account for the effective applications of exosomes.

Nanostructured silicon has been regarded as a promising next-generation anode material for high energy density lithium-ion batteries. However, costly synthesis methods and low initial coulombic eff...

Metal oxide photocatalysts have the disadvantages of large band gap and high internal resistance, and their photoelectrochemical properties are restricted. Metal selenides are generally characterized by narrow bandgap width, low internal resistance, high utilization rate of sunlight and superior photoelectrochemical performance. The ZnSe/MoSe2 heterostructure composite was successfully constructed by loading ZnSe nanoparticles onto MoSe2 nanoplates with three-dimensional flower-like structure. In this heterostructure composite, ZnSe nanoparticles are uniformly encapsulated by MoSe2 nanoplates, and the larger contact surface facilitates the transfer of carriers between heterojunction, while the three-dimensional flower structure of MoSe2 can transport and collect photogenerated carriers. This heterojunction composite has a full-band absorption capability of UV and visible light. Photocatalytic tests showed that the photocatalytic activity of the heterojunction photocatalyst was more than twice of MoSe2 and more than 4 times of ZnSe at the optimum ZnSe composite ratio, and photoelectric performance of that was 2.75 times of MoSe2. The results show that the photoelectrochemical performance of ZnSe/MoSe2 has been greatly improved, mainly because of the 0D/2D structure and band matching of ZnSe/MoSe2, so that the photogenerated electrons excited on the ZnSe conduction band can be transported to the conduction band of MoSe2, thereby improving the carriers’ separation efficiency and photoelectrochemical performance.

To improve the diagnosis and identification of ovarian clear cell carcinoma (CCC) and ovarian endometrioid carcinoma (EC), we evaluated CT imaging findings and cut-off values for CEA and CA125. The CT features and tumour markers (tumour size, location, morphology, composition, number of cysts, growth pattern of the mural nodules, mural nodule HWR, enhancement of the mural nodules, ascites, complications, CEA level, CA125 level) of 55 tumours in 52 patients with CCC, confirmed by surgery and pathology at the Yunnan Cancer Hospital from January 1, 2012 to December 30, 2018, were compared with those of 41 tumours in 36 patients with EC. All patients had a long history of endometriosis. Statistical analysis was performed using t test, chi-square test, Mann–Whitney U test, univariate analysis, multivariate logistic regression analysis and receiver-operating characteristic (ROC) curves. CCC and EC presented as large oval or irregular mixed cystic-solid masses in the pelvic region, with moderately delayed enhancement of the solid components. There was a statistically significant difference between the number of cysts, the growth pattern of the mural nodules, the presence/absence of ascites, and the levels of CEA and CA125 (P

The issue of quality of experience (QoE) evaluation in Internet video is challenging for mainly two facts. One is the sophisticated interactions between features from different entities: user, system and context. The other is the heterogeneity of feature type, i.e., sequential and non-sequential characteristics of features. To address above challenges, we propose a hybrid network model that integrates a deep neural network (DNN) and an improved recurrent neural network (RNN) for representation learning of view-level QoE evaluation. Non-sequential side information and time difference of sequential features are incorporated to different layers of RNN. Attention mechanism is applied for further improvement of RNN. Based on the output of attention network, we propose a graph-based ranking algorithm to conduct user behavior analyzing, which is useful to online decision of service providers. We conduct experiments on a real-world dataset from a large-scale VoD services provider. The results demonstrate that our method is more effective over the state-of-the-art methods for QoE evaluation.

In the photoelectrochemistry reaction, the electrode is most important. As a common electrode material, the metal oxide has a large band gap and high internal resistance, which is disadvantageous for photocatalytic hydrogen production. Metal selenide generally has a narrow band gap and low internal resistance, which is a promising new type of photocatalyst. A FeSe2/ZnSe heterojunction photocatalyst is constructed by loading ZnSe nanoparticles on FeSe2 nanorods. In this heterostructure, ZnSe is uniformly supported on the surface of FeSe2 to form a 0D/1D structure. Experiments have confirmed that the photoelectrochemical activity and photocatalytic H2 production rate of this heterojunction photocatalyst is greatly improved, and its optimum performance is three times of ZnSe in photoelectrochemical activity and 2.3 times in photocatalytic H2 production rate. Further analysis reveals that the internal resistance of the composite photocatalyst is greatly reduced due to the compositing of FeSe2, and the carrier separation efficiency is also improved. In this FeSe2/ZnSe heterojunction, the conduction band of ZnSe is more negative than that of FeSe2, and the photogenerated electrons generated on the conduction band of ZnSe can be transferred to that of FeSe2, thereby prolonging the carrier lifetime and improving photoelectrochemical activity. This work confirms that FeSe2/ZnSe is a very effective heterostructure, which avoids the addition of precious metals and rare earth metals and shows great application prospects.

Highly sensitive wearable textile pressure sensors represent the key components of smart textiles and personalized electronics, with potential applications in biomedical monitoring, electronic skin, and human-machine interfacing. Here, we present a simple and low-cost strategy to fabricate highly sensitive wearable textile pressure sensors for non-invasive human motion and physiological signal monitoring and the detection of dynamic tactile stimuli. The wearable textile sensor was woven using a one-dimensional (1D) weavable core-sheath nanofiber yarn, which was obtained by coating a Ni-coated cotton yarn electrode with carbon nanotube (CNT)-embedded polyurethane (PU) nanofibers using a simple electrospinning technique. In our design, the three-dimensional elastic porous nanofiber structure of the force-sensing layer and hierarchical fiber-bundled structure of the conductive Ni-coated electrode provide the sensor with a relatively large surface area, and a sufficient surface roughness and elasticity. This leads to rapid and sharp increases in the contact area under stimuli with low external pressure. As a result, the textile pressure sensor exhibits the advantages of a high sensitivity (16.52 N−1), wide sensing range (0.003–5 N), and short response time (~0.03 s). Owing to these merits, our textile-based sensor can be directly attached to the skin as usual and conformally fit the shape deformations of the body’s complex flexible curved surfaces. This contributes to the reliable real-time monitoring of human movements, ranging from subtle physiological signals to vigorous movements. Moreover, a large-area textile sensing matrix is successfully fabricated for tactile mapping of spatial pressure by being worn on the surface of wrist, highlighting the tremendous potential for applications in smart textiles and wearable electronics.

Ubiquitin-conjugating enzyme E2C (UBE2C) plays important roles in tumor progression; nevertheless, its function in endometrial cancer remains unclear. This study elucidated the impact of UBE2C on endometrial cancer and its underlying mechanism. Human endometrial cancer and normal endometrial tissues were acquired from patients at Wuhan Union Hospital and UBE2C expression was detected by Western blotting and qRT-PCR. Endometrial cancer cells were transfected with a UBE2C overexpression plasmid or UBE2C-specific short hairpin RNA (shRNA) to up- or downregulate UBE2C expression, respectively. CCK8 and transwell assays were applied to assess the effects of UBE2C on cell proliferation, migration, and invasion. We found a significant elevation of UBE2C expression in patients with endometrial cancer, and that UBE2C upregulation was associated with advanced histologic grade, FIGO stage, recurrence, and shorter overall survival. UBE2C knockdown inhibited endometrial cancer cell proliferation, migration, invasion, and epithelial–mesenchymal transition (EMT), whereas UBE2C overexpression exerted the opposite effects. UBE2C downregulation increased p53 and its downstream p21 expression, with p53 overexpression reversing the EMT-promoting effects of UBE2C. UBE2C enhanced p53 ubiquitination to facilitate its degradation in endometrial cancer cells. Estradiol (E2) induced UBE2C expression via estrogen receptor α, which binds directly to the UBE2C promoter element. Silencing of UBE2C inhibited E2-promoted migration, invasion, and EMT in vitro and in vivo. Implications: UBE2C-mediated tumor EMT promotion by estrogen is a novel mechanism for the progression of estrogen-induced endometrial cancer, which could offer new biomarkers for diagnosis and therapy of endometrial cancer in the future.

Person re-identification, identifying and tracking pedestrians in cross-domain monitoring systems, is an important technology in the computer vision field and of real significance for the construction of smart cities. With the development of deep learning techniques, especially convolutional neural networks, this technology has received more extensive attention and improvement in recent years and a large number of noteworthy achievements have emerged. This paper provides a comprehensive overview of person re-identification approaches to assist researchers in quickly understand this field with preference as well as to provide a more structured framework. By reviewing more than 300 re-identification related papers, the focus of these studies is summarized as information extraction, metric learning, post-processing, efficiency improvement, labeling cost reduction, and data type expansion. This classification is then organized based on different technologies, and on this basis, the pros and cons of each technology are analyzed. Moreover, this overview summarizes the difficulties and challenges of re-identification and discusses the possible research directions for reference.

The repeated puncture of vessels with a conventional syringe needle causes frequent pain and fear in patients and particularly increases the risk of infections. An indwelling needle implanted in veins for a long time can avoid repeated punctures. However, blood coagulation during implantation and bleeding after the withdrawal of the needle are still key problems. Herein, we present a novel strategy to engineer a smart indwelling needle with on-demand switchable anticoagulation and hemostatic activities by modifying the outer surface and the inner surface of the indwelling needle with a coagulant catechol-functionalized chitosan coating and anticoagulant magnetic FeNP–dopamine-conjugated heparin (FeNP–HepDA), respectively. The smart indwelling needle is implanted into a rabbit's ear vein. Remarkably, under a magnetic field, the FeNP–HepDA-coated cannula inner wall maintains excellent anticoagulation activity, ensuing the patency of the needle due to the firm fixation of FeNP–HepDA. Upon removing the magnetic field, FeNP–HepDA can be shed. Under this condition, the cannular inner surface loses anticoagulation activity and when the needle is extracted from the vein, the hemostatic CHCS coating on the external surface serves to prevent bleeding. The strategy reported in this study opens up an avenue for designing biomaterials and biodevices exhibiting the coexistence of anticoagulation and coagulation.

Breast cancer is a frequent tumor threatening the health of women. Circular RNAs (circRNAs) play vital roles in cancer progression and chemoresistance. Herein, we mainly investigate the role and potential mechanism of circRNA ataxin 7 (circATXN7; circ_0066436) in breast cancer. RNA expression levels were detected via quantitative real-time PCR (qPCR), western blot and immunohistochemistry. Cell viability and half inhibitory concentration (IC50) of doxorubicin were assessed by cell counting kit-8 (CCK-8) method. Cell proliferation, migration and invasion were determined by CCK-8, 5-ethynyl-2'-deoxyuridine, colony formation and transwell assays. The binding relationship between microRNA-149-5p (miR-149-5p) and circATXN7 or homeobox A11 (HOXA11) was validated via dual-luciferase reporter assay and RNA immunoprecipitation assay. Xenograft assay was conducted to analyze the effect of circATXN7 on doxorubicin resistance of breast cancer. CircATXN7 and HOXA11 levels were enhanced, whereas miR-149-5p level was declined in breast cancer tissues and cells. CircATXN7 silencing suppressed breast cancer development and doxorubicin resistance. Additionally, circATXN7 upregulated HOXA11 via absorbing miR-149-5p, thereby inducing breast cancer cell progression and reducing doxorubicin sensitivity. Besides, depletion of circATXN7 enhanced doxorubicin sensitivity in vivo. Interference of circATXN7 inhibited breast cancer progression and doxorubicin resistance via mediating miR-149-5p/HOXA11 axis, which might provide a possible biomarker for breast cancer therapy.

PURPOSE To non-invasively evaluate the Ki-67 level in digital breast tomosynthesis (DBT) images of breast cancer (BC) patients based on subregional radiomics. METHODS A total of 266 patients who underwent DBT scans were consecutively enrolled at two centers, between September 2017 and September 2021. The whole tumor region was partitioned into various intratumoral subregions, based on individual- and population-level clustering. Handcrafted radiomics features and deep learning-based features were extracted from the subregions and from the whole tumor region, and were selected by least absolute shrinkage and selection operator (LASSO) regression, yielding radiomics signatures (RSs). The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the developed RSs. RESULTS Each breast tumor region was partitioned into an inner subregion (S1) and a marginal subregion (S2). The RSs derived from S1 always generated higher AUCs compared with those from S2 or from the whole tumor region (W), for the external validation cohort (AUCs, S1 vs. W, handcrafted RSs: 0.583 [95% CI, 0.429-0.727] vs. 0.559 [95% CI, 0.405-0.705], P value: 0.920; deep RSs: 0.670 [95% CI, 0.516-0.802] vs. 0.551 [95% CI, 0.397-0.698], P value: 0.776). The fusion RSs, combining handcrafted and deep learning-based features derived from S1, yielded the highest AUCs of 0.820 (95% CI, 0.714-0.900) and 0.792 (95% CI, 0.647-0.897) for the internal and external validation cohorts, respectively. CONCLUSIONS The subregional radiomics approach can accurately predict the Ki-67 level based on DBT data; thus, it may be used as a potential non-invasive tool for preoperative treatment planning in BC. This article is protected by copyright. All rights reserved.

Background: A major concern about the Laparoscopy Approach to Cervical Cancer trial is the disparities in laparoscopic radical hysterectomy experience between the participating centers and the potential effects of the learning curve of minimally invasive surgery on the oncologic outcomes of patients. Thus, it is necessary to assess the survival of cervical cancer patients undergoing laparoscopy in a minimally invasive gynecology center.Methods: A consecutive series of patients undergoing first laparoscopic radical hysterectomy (LRH) for cervical cancer from May 2008 to December 2017 at a national laparoscopic training center were retrospectively analyzed. The overall survival (OS) and progression-free survival (PFS) were compared between groups.Results: In total, 1316 women with FIGO (2009) stage IA-IIB cervical cancer received LRH. Among them, 1114 (84.7%) were followed-up for 3 months or longer; the median follow-up period was 48 months (range, 3-144 months). In patients with stage IA, IB1 (≤ 2 cm), IB1 (> 2 cm), IB2, IIA1 and IIA2-IIB tumors, the 4-year PFS rates were 98.6%, 94.5%, 87.4%, 65.6%, 80.0% and 67.4%, respectively, and the 4-year OS rates were 98.6%, 96.8%, 91.1%, 77.4%, 85.6% and 76.2%, respectively. The 4-year PFS and OS were as high as 96.2% and 97.5%, respectively, in patients with squamous cell carcinoma of 2 cm or smaller in diameter. A stable high 4-year OS and PFS was achieved after completing 100 LRHs. In patients operated on by the same surgeon, an improvement in survival was observed after 40 LRHs. Conclusion: Favorable oncologic outcomes can be achieved in patients with IA-IB1 cervical cancer after LRH in a center with a high surgery volume.

Research has confirmed that extra spindle pole bodies-like 1 (ESPL1), an etiological factor, promotes the malignant progression of cancers. However, the relationship between ESPL1 and glioma has not yet been demonstrated. The purpose of this study was to reveal the potential mechanisms of ESPL1-mediated malignant glioma progression. Gene expression data and detailed clinical information of glioma cases were obtained from multiple public databases. Subsequently, a series of bioinformatics analyses were used to elucidate the effects of ESPL1 on glioma. The results demonstrated that the mRNA and protein levels of ESPL1 in glioma were higher than those in normal brain tissues. In addition, ESPL1 expression was considerably associated with the clinical and pathological features of gliomas, such as World Health Organization grade, histology, and 1p19q co-deletion status. Importantly, ESPL1 reduced the overall survival (OS) of glioma patients and had prognostic value for gliomas. Gene set enrichment analysis (GSEA) indirectly revealed that ESPL1 regulates the activation of cancer-related pathways, such as the cell cycle and base excision repair pathways. In addition, we used the Connectivity Map (CMap) database to screen three molecular drugs that inhibit ESPL1: thioguanosine, antimycin A, and zidovudine. Finally, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression levels of ESPL1 in glioma cell lines. This study plays an important role in revealing the etiology of glioma by revealing the function of ESPL1, providing a potential molecular marker for the diagnosis and treatment of glioma, especially low-grade glioma.

One of the challenges in the field of medical image classification is the expensiveness of labeled data. Most of the previous computer-aided diagnostic methods are based on a paradigm of object detection. Such ways need tons of labeled sample images with positioning annotations, which always need practicing radiologists to process data manually. We focus on Chest X-ray(CXR) images classification and propose an effective framework for lung disease diagnosis based on a self-supervised feature extracting mechanism trained in a constrained contrastive method. Our proposed framework can train on a relatively small dataset in a semi-supervised way and without any positioning annotation. We experiment with the proposed framework on several lung disease diagnosis tasks, including pneumonia and tuberculosis diagnosis, and obtain state-of-the-art results even outperform previous supervised transfer-learning methods.

Wearable electronics are becoming one of the key technologies in health care applications including health monitoring, data acquisitions, and real‐time diagnosis. The commercialization of next‐generation devices has been stymied by the lack of ultrathin, flexible, and reliable power sources. Wearable thermo‐electrochemical cells (TECs), which can convert body heat to electricity via an electrochemical process, are showing great promise as power sources for such wearable systems. TECs harvest orders of magnitude more voltage per temperature difference (Seebeck coefficient (1–34 mV K−1)) when compared to the more common thermoelectric generators (Seebeck coefficient ≈tens or hundreds of µV K−1). However, there still remain great challenges for TECs progressing towards wearable applications. This review summarizes the recent development of potentially wearable TECs with promise for body‐heat harvesting, with a specific focus on flexible electrode materials, solid‐state electrolytes, device fabrication, and strategies toward applications. It also clarifies the challenges and gives some future direction to enhance future investigations on high‐performance wearable TECs for practical and self‐powered wearable devices.

Currently, the occurrence and mortality rate of cervical cancer is high, particularly in low-to-middle-income countries. Therefore, the development of novel diagnostic and treatment strategies for cervical cancer is urgently required. The aim of the present study was to assess the prognostic significance of fibronectin type III domain containing 3B (FNDC3B) expression in patients with cervical cancer and to determine the underlying mechanism of FNDC3 in tumor development. Analysis of the ONCOMINE database revealed that FNDC3B was significantly upregulated in cervical cancer tissue compared with normal tissue. Additionally, FNDC3B expression data and the clinical characteristics of patients with cervical cancer were obtained from the cBioPortal database. Correlations between FNDC3B expression and overall survival were subsequently investigated. The results revealed that increased FNDC3B expression was significantly correlated with a lower overall survival in patients with cervical cancer. A co-expression network was subsequently constructed to elucidate the function of FNDC3B in cervical cancer. Co-expression genes for FNDC3B were obtained from the cBioPortal database and were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The results demonstrated that the genes were enriched in pathways associated with migration, invasion, endoplasmic reticulum (ER) stress and the unfolded protein response (UPR). Furthermore, immunofluorescence results obtained from the Human Protein Atlas revealed that the FNDC3B protein was localized to the ER. The results revealed that upregulated FNDC3B expression may be a biomarker for poor prognosis for patients with cervical cancer. Additionally, the results revealed that FNDC3B may serve an oncogenic role in cancer development via ER stress, UPR, cell migration and invasion. However, further studies are required to determine the exact molecular mechanism of FNDC3B in the development of cervical cancer and to assess its potential as a novel therapeutic target for the treatment of this disease.

Background Activation of NLPR3 inflammasome is associated with the development and progression of some types of malignant tumors, but its role in endometrial cancer is unclear. This study aimed to investigate the expression and function of NLRP3 inflammasome in endometrial cancer. Materials and methods The expression levels of NLRP3, its inflammasome components and estrogen receptor β in endometrial cancer and paired non-tumor tissues were detected. The effects of NLPR3 silencing or overexpression on the proliferation, migration, and invasion of Ishikawa and HEC-1A cells were determined. The impact of NLPR3 silencing on the growth of implanted tumors was determined in vivo. The effects of estrogen on NLPR3 inflammasome activation and Ishikawa cell proliferation were determined. Results The upregulation of NLRP3, ASC, caspase-1, and IL-1β was associated with the progression of endometrial cancer and poor survival. NLPR3 silencing inhibited the proliferation, migration, and invasion of endometrial cancer cells while NLPR3 overexpression had opposite effects. NLPR3 silencing reduced IL-1β and caspase-1 expression and the growth of implanted endometrial tumors, accompanied by decreased pro-IL-1β maturation. Estrogen enhanced NLPR3, ERβ, pro-IL-1β, IL-1β expression, and endometrial cancer cell proliferation, which were mitigated by treatment with ERβ inhibitor but not ERα inhibitor. Conclusion Our results suggest that estrogen acts through ERβ to enhance the activation of NLPR3 inflammasome and promote the progression of endometrial cancer. NLPR3 inflammasome may be a new therapeutic target for endometrial cancer.

Nanochannels are critical components for the fundamental and applied studies of nanofluids. However, the intrinsic low efficiency and high cost of conventional bulk-/surface-/mold-machining methods severely hinder the wide application of nanochannels. Here, we reported a fast, low-cost and maskless fabrication strategy based on friction-induced selective etching in HF/HNO3 mixtures for controllable preparation of diversified and high-quality Si nanochannels. Owing to its distinct anisotropic etching characteristic to scratched area, this novel integrated fabrication process eliminated the limitation of HF/HNO3 mixtures in nanofabrication. Particularly, the etching efficiency and depth of scratched Si in HF/HNO3 mixtures are 12 and 2 times of those in HF solution, respectively. Furthermore, the effects of the volume ratio of HF and HNO3 as well as scratching parameters on nanochannel fabrication were investigated systematically. Cross-sectional transmission electron microscopy observation indicated that the as-fabricated nanochannels have no structural damage. Finally, the corresponding nanofluidic device was designed, fabricated and verified in sequence. The results demonstrate the feasibility of proposed approach for nanochannel fabrication in the area of nanofluids, particularly in analytical chemistry, biochemistry, liquid transport and metering, and energy conversion.

Afatinib, a selective and irreversible inhibitor of tyrosine kinase, was approved for the treatment of advanced non-small-cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) overexpression in 2013. Cetuximab (CTX), an anti-EGFR monoclonal antibody, is co-administered with afatinib to improve efficacy. Unfortunately, dose-related adverse reactions caused by combination therapy have affected patient compliance, and have resulted in treatment discontinuation in severe cases. In the present study, afatinib was encapsulated in "liposomes" (LPs) to achieve longer circulation in the blood and an enhanced permeability-and-retention effect in tumors. Concomitantly, CTX was designed to bind to drug-loaded LPs to form "immuno-LPs" for tumor-cell selectivity and therapeutic activity. In vitro, the cellular internalization rate of immuno-LPs was significantly higher than that of LPs (p 0.05). In vivo, a markedly increased area under the curve and prolonged terminal half-life were detected in rats injected with the two LP formulations, indicating that LP encapsulation protected afatinib from binding to hemoglobin to control the risk of idiosyncratic drug reactions. Compared with free afatinib and LPs, immuno-LPs exhibited strongly enhanced drug delivery and antitumor efficacy in an NSCLC xenograft model, with stronger tumor selectivity and potentially fewer side-effects. Hence, EGFR-targeting immuno-LPs appear to be promising for NSCLC treatment.

UV-assisted selective etching was proposed to raise the etching rate for rapid fabrication on GaAs without templates. Within the same time, protrusive hillocks stemming from the photochemical etching are obvious higher than that of traditional chemical etching. The hillock height produced by the photochemical etching increases linearly and then gradually decreases with etching time, and the scratch produced by higher load can change into higher hillock after etching. By programming tip traces, various patterns, including pyramidal tips, were fabricated on GaAs surface. This study provides opportunities for fabricating high-quality GaAs-based optical structures and devices with low cost and high efficiency.

In this work, ultrathin 2D SnS2 nanosheets were coupled with 2D MoS2 nanolayers as face-to-face 2D/2D heterojunction photocatalysts. Compared with pristine SnS2, this face-to-face 2D/2D SnS2/MoS2 heterojunction exhibited obvious improvement in photocatalytic and photoelectrochemical performance. The highest heterojunction composite activity was nearly two times and 12 times than that of pristine SnS2 in photocatalytic activity and photoelectrochemical performance, respectively. The good performance was ascribed to the face-to-face 2D/2D heterojunction structure and suitable energy band matching. In this face-to-face 2D/2D heterojunction structure, the migration distance between the photoinduced carriers' separation site to the heterojunction interface was very short, but the contact surface was large. Furthermore, the conduction band position of MoS2 was more positive than that of SnS2. Therefore, the photoinduced electrons at the conduction band of SnS2 could flow into the conduction band of MoS2. The transmission between the SnS2/MoS2 heterojunction prolonged the carriers' life and improved the carriers' separation efficiency. In this way, photoinduced carriers produced in SnS2 and MoS2 could flow across the heterojunction quickly, which increased the carriers' separation efficiency. This work successfully developed a new structure to improve the heterojunction property for photocatalytic applications.

In this work, three-dimensional In2S3 dandelions were coupled with embedded two-dimensional ultrathin hexagonal SnS2 nanosheets as 3D/2D heterojunction photocatalysts and related photocatalytic and photoelectrochemical activities were studied. Compared with pristine In2S3, this 3D/2D In2S3/SnS2 heterojunction exhibited excellent enhancement in photocatalytic and photoelectrochemical performance. The 3D/2D In2S3/SnS2 heterojunction composite with the highest activity displayed nearly 5 times enhancement in photocatalytic performance and 7 times increase in photoelectrochemical property. The excellent performance can be ascribed to the 3D/2D heterojunction structure and appropriate energy band structure between In2S3 and SnS2. As the conduction band and valence band of In2S3 are both higher than those of SnS2, the photo-induced electrons at the conduction band of In2S3 will flow into the conduction band of SnS2 while the photo-induced holes at the valence band of SnS2 will flow into the valence band of In2S3. In this way, the photo-induced carriers will separate into different semiconductors. In the 3D/2D heterojunction structure, the three-dimensional In2S3 offers a network structure to load SnS2 nanosheets, and this network structure can collect and transfer photo-induced carriers very well which leaded to a high carriers’ separation efficiency. The work develops a new strategy to improve the heterojunction property for photocatalytic and photoelectrochemical application.

In this work, Sb 8 O 11 Cl 2 was composited with TiO 2 with different exposed facets to construct heterostructure and related photocatalytic activity was studied. The results reveal that this TiO 2 /Sb 8 O 11 Cl 2 heterostructure is crystal facets sensitive. When Sb 8 O 11 Cl 2 was loaded on the {001} facets of TiO 2 nanosheets with coexposed {101} and {001} facets, the photo-induced carriers' separation efficiency is enhanced and related photocatalytic activity is improved with a ratio of 74% under optimal composited ratio. However, the carriers' separation efficiency and related photocatalytic activity almost had no variation when Sb 8 O 11 Cl 2 was composited with P25 which is mainly constituted by anatase TiO 2 with exposed {101} facets. Pure anatase TiO 2 nanooctahedrons with mainly {101} facets were also composited with Sb 8 O 11 Cl 2 and related composites displayed persistent decline in the carriers' separation efficiency and photocatalytic activity. The results can be explained by the different energy band structure of TiO 2 /Sb 8 O 11 Cl 2 heterostructures. When Sb 8 O 11 Cl 2 was composited on the {101} facets of anatase TiO 2 , an n-n type heterostructure will be constructed and the photo-induced electrons can hardly transform between N-type TiO 2 and Sb 8 O 11 Cl 2 . But as Sb 8 O 11 Cl 2 was composited on the {101} facets of anatase TiO 2 nanosheets with coexposed {101} and {001} facets, a novel n-p-n dual heterojunction will form. In this n-p-n dual heterojunction, photo-induced electrons produced in the conduction band of Sb 8 O 11 Cl 2 will flow into the conduction band of P-type {001} facets and finally flow into the {101} facets of TiO 2 . In this way, the photo-induced carriers will separate into different semiconductors and the photocatalytic activity of TO/Sb 8 O 11 Cl 2 heterostructures is enhanced.

Nano-MnS were coupled with ultrathin two-dimensional MoS2 nanolayers as heterojunction photocatalysts. The well heterojunction contact can be confirmed by high resolution TEM images. The heterojunction composites display higher absorption intensity of visible light and the S XPS peaks show obvious shift. Compared with pristine MnS, this MnS/MoS2 heterojunction exhibited vast enhancement in photocatalytic and photoelectrochemical performance. The heterojunction composite with highest activity displayed 161% enhancement in photocatalytic activity, 2.6–11.5 times increase of photocurrent density. This vast improvement can be assigned to the energy band matching of MnS/MoS2 heterojunction. Both the conduction band and valence band of MnS are more negative than those of MoS2, the photo-induced electrons at the conduction band of MnS will transfer into the conduction band of MoS2 while the photo-induced holes at the valence band of MoS2 will transfer into the valence band of MnS. In this way, the photo-produced carriers will flow into different semiconductors and the carriers' separation efficiency is enhanced. The work develops a new approach to improve the heterojunction property for photocatalytic and photoelectrochemical application.

Vehicle re-identification is one of the core technologies of intelligent transportation systems, and it is crucial for the construction of smart cities. With the rapid development of deep learning, vehicle re-identification technologies have made significant progress in recent years. Therefore, making a comprehensive survey about the vehicle re-identification methods based on deep learning is quite indispensable. There are mainly five types of deep learning-based methods designed for vehicle re-identification, i.e. methods based on local features, methods based on representation learning, methods based on metric learning, methods based on unsupervised learning, and methods based on attention mechanism. The major contributions of our survey come from three aspects. First, we give a comprehensive review of the current five types of deep learning-based methods for vehicle re-identification, and we further compare them from characteristics, advantages, and disadvantages. Second, we sort out vehicle public datasets and compare them from multiple dimensions. Third, we further discuss the challenges and possible research directions of vehicle re-identification in the future based on our survey.

BackgroundIn combined with neurofeedback, Motor Imagery (MI) based Brain-Computer Interface (BCI) has been an effective long-term treatment therapy for motor dysfunction caused by neurological injury in the brain (e.g., post-stroke hemiplegia). However, individual neurological differences have led to variability in the single sessions of rehabilitation training. Research on the impact of short training sessions on brain functioning patterns can help evaluate and standardize the short duration of rehabilitation training. In this paper, we use the electroencephalogram (EEG) signals to explore the brain patterns’ changes after a short-term rehabilitation training.Materials and MethodsUsing an EEG-BCI system, we analyzed the changes in short-term (about 1-h) MI training data with and without visual feedback, respectively. We first examined the EEG signal’s Mu band power’s attenuation caused by Event-Related Desynchronization (ERD). Then we use the EEG’s Event-Related Potentials (ERP) features to construct brain networks and evaluate the training from multiple perspectives: small-scale based on single nodes, medium-scale based on hemispheres, and large-scale based on all-brain.ResultsResults showed no significant difference in the ERD power attenuation estimation in both groups. But the neurofeedback group’s ERP brain network parameters had substantial changes and trend properties compared to the group without feedback. The neurofeedback group’s Mu band power’s attenuation increased but not significantly (fitting line slope = 0.2, t-test value p > 0.05) after the short-term MI training, while the non-feedback group occurred an insignificant decrease (fitting line slope = −0.4, t-test value p > 0.05). In the ERP-based brain network analysis, the neurofeedback group’s network parameters were attenuated in all scales significantly (t-test value: p < 0.01); while the non-feedback group’s most network parameters didn’t change significantly (t-test value: p > 0.05).ConclusionThe MI-BCI training’s short-term effects does not show up in the ERD analysis significantly but can be detected by ERP-based network analysis significantly. Results inspire the efficient evaluation of short-term rehabilitation training and provide a useful reference for subsequent studies.

Verification code recognition system based on convolutional neural network. In order to strengthen the network security defense work, this paper proposes a novel verification code recognition system based on convolutional neural network. The system combines Internet technology and big data technology, combined with advanced captcha technology, can prevent hackers from brute force cracking behavior to a certain extent. In addition, the system combines convolutional neural network, which makes the verification code combine numbers and letters, which improves the complexity of the verification code and the security of the user account. Based on this, the system uses threshold segmentation method and projection positioning method to construct an 8-layer convolutional neural network model, which enhances the security of the verification code input link. The research results show that the system can enhance the complexity of captcha, improve the recognition rate of captcha, and improve the security of user accounting.

In recent years, Artificial Neural Network (ANN) has been widely used in digital handwriting recognition by virtue of its strong fault-tolerant ability and classification ability. However, in traditional recognition methods, taking the number of image pixels as the input number of neurons will cause problems such as long learning and training time and low efficiency. This paper combines principal component analysis (PCA) algorithm with BP algorithm for handwritten digit recognition. After image preprocessing, PCA algorithm is used to reduce dimension of original data. The first 10 principal components, the first 30 principal components, the first 45 principal components, and the first 60 principal components are sent to the neural network as input neurons for training. Then, the test data set was used for testing. Finally, the simulation was analyzed from three dimensions: training efficiency, learning time and identification accuracy. The results show that when the number of input neurons is 60 and the number of hidden layer neurons is 30, the highest recognition rate is only 0.13% lower than that of the number of input neurons is 784, but the training time of the neural network is reduced by 94 seconds, and the efficiency is improved by 32%. When the number of hidden layer neurons is 50, the highest recognition rate is only 0.25% lower than that of input neurons is 784, but the time is reduced by 237 seconds and the efficiency is improved by 63%. This design solves the problem of low learning efficiency in digital recognition well.

An increasing number of evidences have shown that the carcinogenic effect of DRAXIN plays an important role in the malignant process of tumors, but the mechanism of its involvement in glioma has not yet been revealed. The main aim of this study is to explore the relationship between DRAXIN and the prognosis and pathogenesis of glioma through a large quality of data analysis. Firstly, thousands of tissue samples with clinical information were collected based on various public databases. Then, a series of bioinformatics analyses were performed to mine data from information of glioma samples extracted from several reputable databases to reveal the key role of DRAXIN in glioma development and progression, with the confirmation of basic experiments. Our results showed that high expression of the oncogene DRAXIN in tumor tissue and cells could be used as an independent risk factor for poor prognosis in glioma patients and was strongly associated with clinical risk features. The reverse transcription-quantitative PCR technique was then utilized to validate the DRAXIN expression results we obtained. In addition, co-expression analysis identified, respectively, top 10 genes that were closely associated with DRAXIN positively or negatively. Finally, in vitro experiments demonstrated that knockdown of DRAXIN significantly inhibited proliferation and invasion of glioma cell. To sum up, this is the first report of DRAXIN being highly expressed in gliomas and leading to poor prognosis of glioma patients. DRAXIN may not only benefit to explore the pathogenesis of gliomas, but also serve as a novel biological target for the treatment of glioma.

Depression has become one of the main afflictions that threaten people's mental health. However, the current traditional diagnosis methods have certain limitations, so it is necessary to find a method of objective evaluation of depression based on intelligent technology to assist in the early diagnosis and treatment of patients. Because the abnormal speech features of patients with depression are related to their mental state to some extent, it is valuable to use speech acoustic features as objective indicators for the diagnosis of depression. In order to solve the problem of the complexity of speech in depression and the limited performance of traditional feature extraction methods for speech signals, this article suggests a Three-Dimensional Convolutional filter bank with Highway Networks and Bidirectional GRU (Gated Recurrent Unit) with an Attention mechanism (in short 3D-CBHGA), which includes two key strategies. (1) The three-dimensional feature extraction of the speech signal can timely realize the expression ability of those depression signals. (2) Based on the attention mechanism in the GRU network, the frame-level vector is weighted to get the hidden emotion vector by self-learning. Experiments show that the proposed 3D-CBHGA can well establish mapping from speech signals to depression-related features and improve the accuracy of depression detection in speech signals.

Background XRCC2, a homologous recombination-related gene, has been reported to be associated with a variety of cancers. However, its role in glioma has not been reported. This study aimed to find out the role of XRCC2 in glioma and reveal in which glioma-specific biological processes is XRCC2 involved based on thousands of glioma samples, thereby, providing a new perspective in the treatment and prognostic evaluation of glioma. Methods The expression characteristics of XRCC2 in thousands of glioma samples from CGGA and TCGA databases were comprehensively analyzed. Wilcox or Kruskal test was used to analyze the expression pattern of XRCC2 in gliomas with different clinical and molecular features. The effect of XRCC2 on the prognosis of glioma patients was explored by Kaplan–Meier and Cox regression. Gene set enrichment analysis (GSEA) revealed the possible cellular mechanisms involved in XRCC2 in glioma. Connectivity map (CMap) was used to screen small molecule drugs targeting XRCC2 and the expression levels of XRCC2 were verified in glioma cells and tissues by RT-qPCR and immunohistochemical staining. Results We found the overexpression of XRCC2 in glioma. Moreover, the overexpressed XRCC2 was associated with a variety of clinical features related to prognosis. Cox and meta-analyses showed that XRCC2 is an independent risk factor for the poor prognosis of glioma. Furthermore, the results of GSEA indicated that overexpressed XRCC2 could promote malignant progression through involved signaling pathways, such as in the cell cycle. Finally, doxazosin, quinostatin, canavanine, and chrysin were identified to exert anti-glioma effects by targeting XRCC2. Conclusions This study analyzed the expression pattern of XRCC2 in gliomas and its relationship with prognosis using multiple datasets. This is the first study to show that XRCC2, a novel oncogene, is significantly overexpressed in glioma and can lead to poor prognosis in glioma patients. XRCC2 could serve as a new biomarker for glioma diagnosis, treatment, and prognosis evaluation, thus bringing new insight into the management of glioma.

Being a best-known prototype of phase-change materials, GeTe was reported to possess many high-pressure phases, whose structural evolution and superconductivity remain under debate for decades. Herein, we systematically investigated the pressure dependence of electrical transport and the structural evolution of the GeTe viain situangle-dispersive synchrotron x-ray diffraction and resistance measurements up to 55 GPa. At room temperature, the structural phase transitions from the initial rhombohedral phase to theFm3mphase, and then to an orthorhombicPnmaphase, were observed at pressures of about 4 and 13.4 GPa, respectively. Furthermore, the metallization occurred at around 11 GPa, where the superconductivity could also be observed. With increasing pressure, the superconducting transition temperature increases monotonically from 5.7 to 6.4 K and then is independent of pressure above 23 GPa in the purePnmaphase. These results provide insights into the pressure-dependent evolution of the structure and superconductivity in GeTe and have implications for the understanding of other IV-VI semiconductors at high pressure.

The undetectable onset of glioma and the difficulty of surgery lead to a poor prognosis. Appropriate biomarkers for diagnosis and treatment need to be identified. Interleukin-1 receptor-associated kinase 4 (IRAK4) is involved in the initiation and progression of cancer. However, up until now, no report has revealed the relationship between IRAK4 and glioma. The present study aimed to examine the expression of IRAK4 in glioma, and to determine if there was a relationship between IRAK4 expression and clinical outcomes or survival prognosis. Thousands of glioma tissue samples and corresponding clinical information were obtained from various databases. Then a series of bioinformatics methods were used to reveal the role of IRAK4 in glioma. Finally, reverse transcription-quantitative PCR technology was used to verify the bioinformatics results. The study found that the expression of IRAK4 was significantly increased in glioma compared with the control brain tissue samples, and IRAK4, as an independent prognostic factor, shortened the overall survival time of patients with glioma. Gene Set Enrichment Analysis showed that IRAK4 promoted the activation of cell signalling pathways, such as NOD-like and Toll-like receptor signalling pathways. Co-expression analysis showed that the expression of IRAK4 was correlated with CMTM6, MOB1A and other genes. The present study demonstrated the role of IRAK4 as an oncogene in the pathological process of glioma for the first time, and highlights the potential of IRAK4 as a biomarker for prognostic evaluation and treatment of glioma.

Background. Endometrial cancer is among the most common malignant tumors threatening the health of women. Recently, immunity and long noncoding RNA (lncRNA) have been widely examined in oncology and shown to play important roles in oncology. Here, we searched for immune-related lncRNAs as prognostic biomarkers to predict the outcome of patients with endometrial cancer. Methods. RNA sequencing data for 575 endometrial cancer samples and immune-related genes were downloaded from The Cancer Genome Atlas (TCGA) database and gene set enrichment analysis (GSEA) gene sets, respectively. Immune-related lncRNAs showing a coexpression relationship with immune-related genes were obtained, and Cox regression analysis was performed to construct the prognostic model. Survival, independent prognostic, and clinical correlation analyses were performed to evaluate the prognostic model. Immune infiltration of endometrial cancer samples was also evaluated. Functional annotation of 12 immune-related lncRNAs was performed using GSEA software. Prognostic nomogram and survival analysis for independent prognostic risk factors were performed to evaluate the prognostic model and calculate the survival time based on the prognostic model. Results. Twelve immune-related lncRNAs (ELN-AS1, AC103563.7, PCAT19, AF131215.5, LINC01871, AC084117.1, NRAV, SCARNA9, AL049539.1, POC1B-AS1, AC108134.4, and AC019080.5) were obtained, and a prognostic model was constructed. The survival rate in the high-risk group was significantly lower than that in the low-risk group. Patient age, pathological grade, the International Federation of Gynecology and Obstetrics (FIGO) stage, and risk status were the risk factors. The 12 immune-related lncRNAs correlated with patient age, pathological grade, and FIGO stage. Principal component analysis and functional annotation showed that the high-risk and low-risk groups separated better, and the immune status of the high-risk and low-risk groups differed. Nomogram and receiver operating characteristic (ROC) curves effectively predicted the prognosis of endometrial cancer. Additionally, age, pathological grade, FIGO stage, and risk status were all related to patient survival. Conclusion. We identified 12 immune-related lncRNAs affecting the prognosis of endometrial cancer, which may be useful as therapeutic targets and molecular biomarkers.