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Abstract Underwater object detection based on side-scan sonar (SSS) suffers from a lack of finely annotated data. This study aims to avoid the laborious task of annotation by achieving unsupervised underwater object detection through domain-adaptive object detection (DAOD). In DAOD, there exists a conflict between feature transferability and discriminability, suppressing the detection performance. To address this challenge, a domain collaborative bridging detector (DCBD) including intra-domain consistency constraint (IDCC) and domain collaborative bridging (DCB), is proposed. On one hand, previous static domain labels in adversarial-based methods hinder the domain discriminator from discerning subtle intra-domain discrepancies, thus decreasing feature transferability. IDCC addresses this by introducing contrastive learning to refine intra-domain similarity. On the other hand, DAOD encourages the feature extractor to extract domain-invariant features, overlooking potential discriminative signals embedded within domain attributes. DCB addresses this by complementing domain-invariant features with domain-relevant information, thereby bolstering feature discriminability. The feasibility of DCBD is validated using unlabeled underwater shipwrecks as a case study. Experiments show that our method achieves accuracy comparable to fully supervised methods in unsupervised SSS detection (92.16% AP50 and 98.50% recall), and achieves 52.6% AP50 on the famous benchmark dataset Foggy Cityscapes, exceeding the original state-of-the-art by 4.5%.

Shell–tube heat exchangers are commonly used equipment in large-scale industrial systems of wastewater heat exchange to reclaim the thermal energy generated during industrial processes. However, the internal surfaces of the heat exchanger tubes often accumulate fouling, which subsequently reduces their heat transfer efficiency. Therefore, regular cleaning is essential. We aim to detect circle holes on the end surface of the heat exchange tubes to further achieve automated positioning and cleaning tubes. Notably, these holes exhibit a regular distribution. To this end, we propose a circle-permutation-aware object detector for heat exchanger cleaning to sufficiently exploit prior information of the original inputs. Specifically, the interval prior to the extraction module extracts interval information among circle holes based on prior statistics, yielding prior interval context. The following interval prior fusion module slices original images into circle domain and background domain maps according to the prior interval context. For the circle domain map, prior-guided sparse attention using prior a circle–hole diameter as the step divides the circle domain map into patches and performs patch-wise self-attention. The background domain map is multiplied by a hyperparameter weak coefficient matrix. In this way, our method fully leverages prior information to selectively weigh the original inputs to achieve more effective hole detection. In addition, to adapt the hole shape, we adopt the circle representation instead of the rectangle one. Extensive experiments demonstrate that our method achieves state-of-the-art performance and significantly boosts the YOLOv8 baseline by 5.24% mAP50 and 5.25% mAP50:95.

Abstract Introduction Stage IB (deep myometrial invasion) high‐grade endometrioid adenocarcinoma (EA), regardless of LVSI status, is classified into high‐intermediate risk groups, requiring surgical lymph node staging. Intraoperative frozen section (IFS) is commonly used, but its adequacy and reliability vary between reports. Hence, we determined the utility of IFS in identification of high‐risk factors, including deep myometrial invasion and high‐grade. Method We retrospectively analyzed 9,985 cases operated with hysterectomy and diagnosed with FIGO stage I/II EA in postoperative paraffin section (PS) results at 30 Chinese hospitals from 2000 to 2019. We determined diagnostic performance of IFS and investigated whether the addition of IFS to preoperative biopsy and imaging could improve identification of high‐risk factors. Results IFS and postoperative PS presented the highest concordance in assessing deep myometrial invasion (Kappa: 0.834), followed by intraoperative gross examination (IGE Kappa: 0.643), MRI (Kappa: 0.395), and CT (Kappa: 0.207). IFS and postoperative PS presented the highest concordance for high‐grade EA (Kappa: 0.585) compared to diagnostic curettage (D&C 0.226) and hysteroscope (Hys 0.180). Sensitivity and specificity for detecting deep myometrial invasion were 86.21 and 97.20% for IFS versus 51.72 and 88.81% for MRI, 68.97 and 94.41% for IGE. These figures for detecting high‐grade EA were 58.21 and 96.50% for IFS versus 16.42 and 98.83% for D&C, 13.43 and 98.64% for Hys. Parallel strategies, including MRI‐IFS (Kappa: 0.626), D&C‐IFS (Kappa: 0.595), and Hys‐IFS (Kappa: 0.578) improved the diagnostic efficiencies of individual preoperative examinations. Based on the high sensitivity of IFS, parallel strategies improved the sensitivities of preoperative examinations to 89.66% (MRI), 64.18% (D&C), 62.69% (Hys), respectively, and these differences were statistically significant (p = 0.000). Conclusion IFS presented reasonable agreement rates predicting postoperative PS results, including deep myometrial invasion and high‐grade. IFS helps identify high‐intermediate risk patients in preoperative biopsy and MRI and guides intraoperative lymphadenectomy decisions in EA.

Abstract Introduction Myometrial invasion is a prognostic factor for lymph node metastases and decreased survival in non-endometrioid endometrial carcinoma patients. Herein, we explored the mode of myometrial invasion diagnosis in FIGO stage I non-endometrioid carcinoma and evaluated the differences in diagnostic efficiency among intraoperative frozen section (IFS), intraoperative gross examination (IGE), magnetic resonance imaging (MRI), and computed tomography (CT) in clinical practice. Finally, we suggested which test should be routinely performed. Method This was a historical cohort study nationwide with 30 centers in China between January 2000 and December 2019. Clinical data, including age, histology, method of myometrial invasion evaluation (MRI, CT, IGE, and IFS), and final diagnosis of postoperative paraffin sections, were collected from 490 non-endometrioid endometrial carcinoma (serous, clear cell, undifferentiated, mixed carcinoma, and carcinosarcoma) women in FIGO stage I. Results Among the 490 patients, 89.59% presented myometrial invasion. The methods reported for myometrial invasion assessment were IFS in 23.47%, IGE in 69.59%, MRI in 37.96%, and CT in 10.20% of cases. The highest concordance was detected between IFS and postoperative paraffin sections (Kappa = 0.631, accuracy = 93.04%), followed by IGE (Kappa = 0.303, accuracy = 82.40%), MRI (Kappa = 0.131, accuracy = 69.35%), and CT (Kappa = 0.118, accuracy = 50.00%). A stable diagnostic agreement between IFS and the final results was also found through the years (2000–2012: Kappa = 0.776; 2013–2014: Kappa = 0.625; 2015–2016: Kappa = 0.545; 2017–2019: Kappa = 0.652). Conclusion In China, the assessment of myometrial invasion in non-endometrioid endometrial carcinoma is often performed via IGE, but the reliability is relatively low in contrast to IFS. In clinical practice, IFS is a reliable method that can help accurately assess myometrial invasion and intraoperative decision-making (lymph node dissection or not). Hence, it should be routinely performed in non-endometrioid endometrial carcinoma patients.

Objective Systematically evaluate the clinical efficacy of mifepristone combined with methotrexate therapy for ectopic pregnancy (EP), analyze the experimental designs, put forward improvement ideas.Methods RCTs of mifepristone combined with mifepristone for EP until January 2022 in six databases were searched. The primary outcome indicator was the cure rate. RevMan 5.4 was used to analyse and the online GRADEpro tool was used to assess the certainty of the evidence.Results Twenty-five RCTs involved 2263 patients. The cure rate was higher in the investigational group (OR = 4.09, 95%CI: [3.20, 5.22]), time of vagina stopped bleeding (MD = −11.21, 95%CI: [−11.85, −10.57]) and time of abdominal pain disappeared (MD = −6.24, 95%CI: [−6.63, −5.86]) were shorter in the investigational group, β-HCG level (MD = −585.32, 95%CI: [−609.62, −561.03]) was lower and diameter of the mass (MD = −1.23, 95%CI: [−1.40, −106]) was smaller in the investigational group. The certainty of the evidence for most outcomes was moderate or high, and only one was low.Conclusions The combination of mifepristone and methotrexate can improve the efficacy of ectopic pregnancy without amplifying the toxic side effects. Larger scale and better design of the randomized controlled trials are needed.KEY MESSAGESIn recent years, the increase in ectopic pregnancies and their impacts on female fertility makes physicians have to find an effective medical treatment as soon as possible that can avoid surgery.The mifepristone combined with methotrexate therapy for EP has better curative effects on improving the cure rate, lowering β-HCG level, reducing the mass, and alleviating symptoms of abdominal pain and bleeding, without amplifying the toxic side effects.Literature with high quality is lacking, and well-designed, large-scale and high-quality multicenter randomized controlled trials are needed.

Plain language summary Ectopic pregnancy occurs when a fertilized ovum implants outside the endometrium of the uterine cavity, which is a life-threatening occurrence and is an important cause of pregnancy-related mortality. With the increase in pelvic and intrauterine operations, the distribution of ectopic sites has been changing, but the variation has been insufficiently studied. To investigate the distribution of ectopic sites and its variation trend in depth, we collected the data of 3915 ectopic pregnancy cases from the third affiliated hospital of Sun Yat-Sen University. Through χ2 test for trend, the ratio of caesarean scar pregnancy to ectopic pregnancy showed an upward trend (P = 0.005). From 2012 to 2015 and 2016–2019, the ratio of caesarean scar pregnancy to ectopic pregnancy increased from 5.74 to 11.81% (P

Background: Endometrial cancer (UCEC) is the sixth most common cancer in women, and although surgery can provide a good prognosis for early-stage patients, the 5-year overall survival rate for women with metastatic disease is as low as 16%. Long non-coding RNAs (LncRNAs) are thought to play an important role in tumor progression. Cuproptosis is a recently discovered form of cell death in which copper binds directly to the lipoacylated component of the tricarboxylic acid (TCA) cycle. The aggregation of these copper-bound listed mitochondrial proteins and the loss of Fe-S cluster proteins trigger proteotoxic stress, which leads to cell death. Therefore, the aim of this work was to investigate the role of Cuproptosis-related LncRNAs signaling in clinical prognostic prediction and immunotherapy, as well as the relationship between tumor mutation burden.Methods: Genomic, clinical and mutational data of endometrial cancer patients were presented in the TCGA database, and cuproptosis-related genes obtained from related studies. Coexpression analysis and Cox regression analysis were used to construct prognostic features. Patients were divided into high risk group and low risk group, and then ROC, survival rate, risk curve, principal component analysis, independent prognostic analysis and clinical subgroup model validation were performed to observe the prognostic value of characteristics. Subsequently, the GO and genomic KEGG enrichment and immune-related functions of LncRNAs as well as the tumor mutation burden were analyzed.Results: In 548 UCEC case data, we identified five associated LncRNAs co-expressed with cuproptosis genes, and we found that high-risk patients had poorer overall survival (OS), progression-free survival (PFS), and higher mortality. Independent prognostic analysis, ROC showed that the LncRNAs associated with cuproptosis could accurately predict the prognosis of patients. Enrichment analysis revealed that the biological functions of LncRNAs were related to tumorigenesis. We also discovered suppression of immune-related functions in high-risk patients with oncogene mutations, higher tumor mutation burden in low-risk patients, and longer overall survival in patients with higher tumor mutation burden.Conclusion: The identification of five LncRNAs associated with cuproptosis can accurately predict the prognosis of patients with endometrial cancer, and may provide a new perspective for clinical application and immunotherapy.

ObjectiveProtective color restoration of faded digital pathology images based on color transfer algorithm.MethodsTwenty fresh tissue samples of invasive breast cancer from the pathology department of Qingdao Central Hospital in 2021 were screened. After HE staining, HE stained sections were irradiated with sunlight to simulate natural fading, and every 7 days was a fading cycle, and a total of 8 cycles were experienced. At the end of each cycle, the sections were digitally scanned to retain clear images, and the color changes of the sections during the fading process were recorded. The color transfer algorithm was applied to restore the color of the faded images; Adobe Lightroom Classic software presented the histogram of the image color distribution; UNet++ cell recognition segmentation model was used to identify the color restored images; Natural Image Quality Evaluator (NIQE), Information Entropy (Entropy), and Average Gradient (AG) were applied to evaluate the quality of the restored images.ResultsThe restored image color met the diagnostic needs of pathologists. Compared with the faded images, the NIQE value decreased (PConclusionThe color transfer algorithm can effectively repair faded pathology images, restore the color contrast between nucleus and cytoplasm, improve the image quality, meet the diagnostic needs and improve the cell recognition rate of the deep learning model.

BackgroundCervical cancer is one of the leading causes of cancer-related deaths worldwide. The unspliced human papillomavirus (HPV) E6 plays an important role in tumor progression and immune regulation. Improved immunotherapy implementation might benefit from a better knowledge of HPV E6 splicing-related immune gene expressions and immunocyte infiltration in cervical cancer. This study aimed to identify the potential therapeutic and prognostic roles of unspliced/spliced E6 ratio (E6 ratio) in cervical cancer.MethodsData from the TCGA were used to analyze the E6 condition and clinical information. Nomogram and K-M analysis were used to analyze assess the prognostic significance, IOBR was used to investigate immunological infiltrates. Functions and pathway enrichment analysis of DEGs were investigated through GO analysis and KEGG pathway analysis, respectively. A core module was taken from the competitive endogenous RNA (ceRNA) network and used to build a lncRNA-miRNA-mRNA network. QT-qPCR was used to detect the expression of genes. CCK-8, colony formation, wound healing and migration assays were used to detect cell functions.ResultsOur study found that HPV E6 ratio had significantly correlation with overall survival. In cervical cancer, a high E6 ratio was adversely linked with infiltrating levels of aDC, M1 macrophages, monocytes, NKT, and Tgd. High E6 ratio phenotypes were shown to be implicated in immune response regulation, cell adhesion, and Wnt signaling pathways, according to functional enrichment analysis. Subsequently, we constructed an immune-related ceRNA network based on E6 splicing in cervical cancer, including three lncRNA (LINC00943, LIFR-AS1, DANT2, and RASSF8-AS1), four miRNA (miR-205-5p, miR-181d-5p, miR-222-3p, and miR-221-3p), and seven mRNA (FGFR1, PRLR, CXCL2, ISG20, ISG15, SDC1, and NR2F2). Among them, CXCL2, SDC1, and miR-221-3p were associated with survival and immune cell infiltration.ConclusionsThese data imply that a high E6 ratio in cervical cancer contributes to the immune-related ceRNA network, resulting in a low amount of infiltrating effector immune cells and tumor growth. As a result, the E6 ratio might be employed as a biomarker in cervical cancer to determine prognosis and treatment success.

At present, China is in the stage of the COVID-19 epidemic where regular prevention and control measures are required to contain the spread of disease. Reports of new sporadic cases are still widespread across China and medical personnel remain at high risk of exposure to infection. This is especially the case for medical staff working within emergency departments. Most gynecological emergency cases are complex and a high proportion require emergency surgical treatment. By referring to national regulations and requirements on COVID-19 prevention and control, and by summarizing our experiences in the battle against COVID-19 within Wuhan, this consensus report provides recommendations on the triage, reception, consultation, admission and surgical management of gynecological emergency patients. We also make suggestions for the environmental layout and disinfection and the medical waste management. This consensus aims to optimize the diagnosis and treatment process of gynecological emergency patients and reduce the exposure risk of medical staff within the current context of routine COVID-19 prevention and control.

Water segmentation is a critical task for ensuring the safety of unmanned surface vehicles (USVs). Most existing image-based water segmentation methods may be inaccurate due to light reflection on the water. The fusion-based method combines the paired 2D camera images and 3D LiDAR point clouds as inputs, resulting in a high computational load and considerable time consumption, with limits in terms of practical applications. Thus, in this study, we propose a multimodal fusion water segmentation method that uses a transformer and knowledge distillation to leverage 3D LiDAR point clouds in order to assist in the generation of 2D images. A local and non-local cross-modality fusion module based on a transformer is first used to fuse 2D images and 3D point cloud information during the training phase. A multi-to-single-modality knowledge distillation module is then applied to distill the fused information into a pure 2D network for water segmentation. Extensive experiments were conducted with a dataset containing various scenes collected by USVs in the water. The results demonstrate that the proposed method achieves approximately 1.5% improvement both in accuracy and MaxF over classical image-based methods, and it is much faster than the fusion-based method, achieving speeds ranging from 15 fps to 110 fps.

ObjectiveThe aim of the present study was to determine overall survival (OS) and risk factors associated with early recurrence in patients with FIGO I–II stage endometrial carcinoma (EC).MethodsClinical features were retrospectively extracted from the database of China Endometrial Cancer Consortium from January 2000 to December 2019. A total of 2,974 patients with Federation International of Gynecology and Obstetrics (FIGO) I–II stage endometrial cancer were included. Kaplan-Meier survival analysis was used to assess OS and disease-specific survival. Cox proportional hazard model and Fine-Gray model were used to determine the factors related to OS. Binary logistic regression model was used to determine independent predictors of early relapse patients.ResultsOf these 2,974 ECs, 189 patients were confirmed to have relapse. The 5-year OS was significantly different between the recurrence and non-recurrence patients (p < 0.001). Three quarters of the relapse patients were reported in 36 months. The 5-year OS for early recurrence patients was shorter than late recurrence [relapse beyond 36 months, p < 0.001]. The grade 3 [odds ratio (OR) = 1.55, 95%CI 1.17–2.05, p = 0.002], lymphatic vascular infiltration (LVSI; OR = 3.36; 95%CI 1.50–7.54, p = 0.003), and myometrial infiltration (OR = 2.07, 95%CI 1.17—3.65, p = 0.012) were independent risk factors of early relapse. The protective factor of that is progesterone receptor (PR)-positive (OR = 0.50, 95%CI 0.27–0.92, p = 0.02). Bilateral ovariectomy could reduce recurrence risk rate (OR = 0.26, 95%CI 0.14–0.51, p < 0.001).ConclusionThe OS of early relapse EC is worse. Grade 3, LVSI, and myometrial infiltration are independent risk factors for early relapse EC. In addition, the protective factor is PR-positive for those people and bilateral salpingo-oophorectomy could reduce the risk of recurrence.

BackgroundInduced abortion is a universal phenomenon and about 25% of pregnancies in the world end in induced abortion. Induced abortion refers to the use of artificial or drug methods to terminate the pregnancy in the early stage of pregnancy, which is a remedy for failed contraception and accidental pregnancy. Induced abortion means surgical abortion. There are two commonly used methods: negative pressure suction abortion and forceps curettage for induced abortion. Abortion is invasive and it will cause great harm to women's reproductive function. Clinically, there are also cases of re-pregnancy within 3 months after abortion or even re-pregnancy without recovery of menstruation. To improve symptoms and reduce these complications, antibiotics, motherwort, and Yasmin[Ethinylestradiol-Drospirenone (0.03/3 mg)] are clinically used alone or in combination after induced abortion.MethodsData were collected from six databases, including three English databases of Cochrane Library, PubMed and Embase, and three Chinese databases of CNKI, Wanfang, and Weipu. The original indicators of vaginal bleeding, menstrual recovery time, bleeding time, endometrial thickness 21 days after surgery and so on were included, and the incidence of postoperative bleeding less than menstrual volume, menstrual re-fluid time ≤ 37 days, bleeding time ≤ 7 days, re-pregnancy without menstruation, re-pregnancy within 3 months after the operation, the total incidence of postoperative complications were based on the ratio of the number of events in the group to the total number of people in the group reported in the literature. Review Manager 5.4 software was downloaded from the Cochrane website to evaluate the quality of the literature and analyze the results using random or fixed-effects models. The outcome of index data is divided into two types, one is dichotomy, and the other is measurement data. The binary data is expressed by odds ratio (OR), and the measurement data is expressed by mean difference (MD), and the confidence interval of both is 95%.ResultsAfter completing this meta-analysis, the results will be available.ConclusionThe results will provide reliable data basis for the value of Yasmin combined with antibiotics and Motherwort in postoperative induced abortion.PROSPERO Registration NumberCRD42021246764.

ObjectivePatients with endometrial cancer (EC) combined with metabolic syndrome (MetS) have a worse prognosis than those without MetS. This study aimed to investigate whether partial metabolic disorder significantly influenced early-stage endometrioid EC (EEC) survival and searched for a more efficient method to evaluate metabolic status.MethodsThis is a nationwide, multicenter cohort study that included 998 patients with primary early-stage EEC from 2001 to 2018. Patients were divided into different metabolic groups based on the diagnostic criteria of the Chinese Medical Association (CDC). The progression-free survival (PFS) time was compared between various metabolic status. Meanwhile, we established an EC Prognostic-Related Metabolic Score (ECPRM Score) to explore the association of the severity of metabolic status and early-stage EEC PFS. A nomogram was established for predicting PFS, which was externally validated in a testing set that includes 296 patients.ResultsA partial metabolic disorder, as well as MetS, was an independent risk factor of poor survival of patients with early-stage EEC [hazard ratio (HR) = 7.6, 95% CI = 1.01–57.5, p < 0.05]. A high ECPRM Score was associated with lower PFS (HR = 2.1, 95% CI = 1.05–4.0, p < 0.001). The nomogram, in which the ECPRM Score contributed most to the prognosis, exhibited excellent discrimination of survival supported by the internal and external validations. In addition, the calibration curve supports its robust predicting ability.ConclusionEven though they do not meet the criteria of MetS, partial metabolic disorders were also associated with adverse outcomes in early-stage EEC. The ECPRM Score is beneficial for clinicians to evaluate the severity of metabolic abnormalities and guide patients to ameliorate the poor prognosis of metabolic disorders.

This study aimed to assess the effects of the antidiabetic drug Exendin-4 (Exe-4), a GLP-1 receptor agonist, on the response of human endometrial cancer cells to chemotherapy under high glucose (HG) conditions. Cell viability was detected using a cell counting kit (CCK)-8. Cell apoptosis and reactive oxygen species (ROS) levels were measured by flow cytometry. Gene expression was evaluated by real-time PCR and immunoblotting. The chemotherapeutic drug cisplatin (DDP) dose-dependently inhibited both human endometrial adenocarcinoma Ishikawa and HEC1B cells, a response reversed by HG. Meanwhile, Exe-4 attenuated hyperglycemia’s effect by elevating intracellular lactate dehydrogenase (LDH) and ROS production. Similarly, DDP-induced elevation of intracellular rhodamine123 was attenuated by HG, and Exe-4 reversed HG’s impact. The chemoresistance genes multidrug resistance-associated protein 1 (MRP1) and P-glycoprotein (Pgp) were upregulated. At the same time, topoisomerase II (TOPO II) was downregulated under HG conditions, suggesting HG-induced chemoresistance. Exe-4 did not significantly influence the above genes. DDP downregulated Bcl-2 and Bcl-XL and upregulated Bax, cytosolic cytochrome c, and PARP under normal glucose (NG) versus HG conditions, and Exe-4 attenuated these effects. Upstream of Bax/Bcl, acetylated P53 was upregulated by DDP and downregulated by HG, whose effect was reversed by Exe-4. DPP treatment significantly induced apoptosis and cell cycle arrest in the S phase under NG, and HG reduced these effects. Prolonged exposure to HG induces DDP chemoresistance in human endometrial cancer cells but is alleviated by Exe-4.

Objective: To systematically evaluate lymph node metastasis (LNM) patterns in patients with endometrial cancer (EC) who underwent complete surgical staging, which included systematic pelvic and para-aortic lymphadenectomy.Methods: Four thousand and one patients who underwent complete surgical staging including systematic pelvic and para-aortic lymphadenectomy for EC were enrolled from 30 centers in China from 2001 to 2019. We systematically displayed the clinical and prognostic characteristics of patients with various LNM patterns, especially the PLN-PAN+ [para-aortic lymph node (PAN) metastasis without pelvic lymph node (PLN) metastasis]. The efficacy of PAN+ (para-aortic lymph node metastasis) prediction with clinical and pathological features was evaluated.Results: Overall, 431 of the 4,001 patients (10.8%) showed definite LNM according to pathological diagnosis. The PAN+ showed the highest frequency (6.6%) among all metastatic sites. One hundred fourteen cases (26.5%) were PLN-PAN+ (PAN metastasis without PLN metastasis), 167 cases (38.7%) showed PLN+PAN-(PLN metastasis without PAN metastasis), and 150 cases (34.8%) showed metastasis to both regions (PLN+PAN+). There was also 1.9% (51/2,660) of low-risk patients who had PLN-PAN+. There are no statistical differences in relapse-free survival (RFS) and disease-specific survival (DSS) among PLN+PAN-, PLN-PAN+, and PLN+PAN+. The sensitivity of gross PLNs, gross PANs, and lymphovascular space involvement (LVSI) to predict PAN+ was 53.8 [95% confidence interval (CI): 47.6–59.9], 74.2 95% CI: 65.6–81.4), and 45.8% (95% CI: 38.7–53.2), respectively.Conclusion: Over one-fourth of EC patients with LMN metastases were PLN-PAN+. PLN-PAN+ shares approximate survival outcomes (RFS and DSS) with other LNM patterns. No effective clinical methods were achieved for predicting PAN+. Thus, PLN-PAN+ is a non-negligible LNM pattern that cannot be underestimated in EC, even in low-risk patients.

A transparent, conductive, smooth, and temperature sensitive thin films was fabricated and characterized in this paper. Silk fibroin could be processed into transparent thin films, which can act as ideal opto-electronic substrates. As pure silk fibroin film is nonconductive, ultra-long silver nanowires coating and platinum sputtering were used to strengthen its conductivity. Ultra-long nanowires were used to reduce the junctions between wires, and platinum was to improve the conductivity of the film. The new nanowire-metal-organic composite film possesses excellent conductivity and good transmittance. The composite films containing different silver nanowires exhibit conductivities of as low as 6.9 Ω/sq, and transmittance of 60–80% in the visible light range. The films also showed potentials in practical applications as their resistance is almost linearly temperature-dependent. It also can transfer power to electrical devices. The new composite films could be expected to function in wearable electronics or implantable devices and sensors.

Water segmentation is essential for the autonomous driving system of unmanned surface vehicles (USVs), which provides reliable navigation for making safety decisions. However, existing methods have only used monocular images as input, which often suffer from the changes in illumination and weather. Compared with monocular images, LiDAR point clouds can be collected independently of ambient light and provide sufficient 3D information but lack the color and texture that images own. Thus, in this paper, we propose a novel camera-LiDAR cross-modality fusion water segmentation method, which combines the data characteristics of the 2D image and 3D LiDAR point cloud in water segmentation for the first time. Specifically, the 3D point clouds are first supplemented with 2D color and texture information from the images and then distinguished into water surface points and non-water points by the early 3D cross-modality segmentation module. Subsequently, the 3D segmentation results and features are fed into the late 2D cross-modality segmentation module to perform 2D water segmentation. Finally, the 2D and 3D water segmentation results are fused for the refinement by an uncertainty-aware cross-modality fusion module. We further collect, annotate and present a novel Cross-modality Water Segmentation (CMWS) dataset to validate our proposed method. To the best of our knowledge, this is the first water segmentation dataset for USVs in inland waterways consisting of images and corresponding point clouds. Extensive experiments on the CMWS dataset demonstrate that our proposed method can significantly improve image-only-based methods, achieving improvements in accuracy and MaxF of approximately 2% for all the image-only-based methods.

BackgroundAlternative splicing (AS) is one of the critical post-transcriptional regulatory mechanisms of various cancers and also plays a crucial role in the development of cancers, including endometrial cancer (EC).MethodsThe splicing data and gene expression profiles of EC were obtained from The Cancer Genome Atlas. The corresponding clinical data were extracted from TCGA-CDR. With univariate Cox regression analysis, least absolute shrinkage and selection operator model, and multivariate Cox regression analysis, the survival-related AS events were selected. Functional enrichment analysis was also performed to investigate the functions of these AS events. Splicing factors and AS regulation network were constructed to understand the correlation among these AS events.ResultA total of 1826 AS events were identified as survival-related events. Functional enrichment analysis showed that these AS events were associated with several immune system-related processes. Then, the prognostic signatures were developed based on these survival-related events and acted as an independent prognostic factor for EC. Splicing factors and AS regulation network were also constructed to understand the regulatory mechanisms of AS events in EC.ConclusionThis study systematically analyzed the role of AS events in EC and developed the prognostic model for EC.

Deep classification tracking aims at classifying the candidate samples into target or background by a classifier generally trained with a binary label. However, the binary label merely distinguishes samples of different classes, while inadvertently ignoring the distinction among the samples belonging to the same class, which weakens the classification and locating ability. To cope with this problem, this article proposes a soft labeling with quasi-Gaussian structure instead of the binary labeling, which distinguishes the samples belonging to different classes and the same class simultaneously. Like as the binary label, the signs of labels for target and background samples are set to be plus and minus respectively to distinguish samples of different classes. Further, to exploit the difference among samples in the same class, the label values of samples in the same class are designed as a monotonically decreasing quasi-Gaussian function about Intersection over Union. Therefore, the corresponding response function is a two-piecewise monotonically increasing quasi-Gaussian combination function about Intersection over Union. Due to such response function, deep classification tracking trained with this proposed soft labeling achieves better classification and location performance. To validate this, the proposed soft labeling is integrated into the pipeline of the deep classification tracker SiamFC. Experimental results on OTB-2015 and VOT benchmark show that our variant achieves significant improvement to the baseline tracker while maintaining real-time tracking speed and acquires comparable accuracy as recent state-of-the-art trackers.

Unmanned surface vehicles (USVs) as unmanned intelligent devices can replace humans to perform missions more efficiently and safely in dangerous areas. However, due to the complex navigation environment and special mission requirements, USVs face many challenges in emergency response missions for marine oil spill accidents. To solve these challenges in the emergency response mission of the ‘Sanchi’ oil tanker collision and explosion accident, we designed and deployed an USV to perform the missions of real-time scanning and water sampling in the shipwreck waters. Compared with the previous USVs, our USV owned the following characteristics: Firstly, the improved navigation control algorithms (path following and collision avoidance) can provide high navigation accuracy while ensuring navigation safety; Secondly, an improved launch and recovery system (LARS) enabled the USV to be quickly deployed and recovered in the mission area; Thirdly, a new sampling system was specially designed for the USV. Our USV completed the missions successfully, not only providing a lot of information for rescuers but also offering a scientific basis for follow-up work.