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Abstract Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures. This paper proposes an efficacious methodology for identifying diverse apparent damages in hydraulic structures to address the limitations of existing technologies. The advanced features of apparent damage in hydraulic structures were elucidated by fine-tuning the top-level parameters of the lightweight pre-trained model, thereby mitigating the data dependency issue inherent in the model. Ensemble learning algorithms are employed to classify high-dimensional samples to enhance the accuracy and stability of the classification. However, ensemble learning algorithms are subject to time consuming issues when applied to high-dimensional datasets. To this end, we propose a robust discriminative feature selection model to identify the most salient features, thereby enhancing the performance of apparent damage recognition in hydraulic structures while concurrently reducing the inference time. The results demonstrated that the accuracies of this method in identifying crack, fracture, hole and normal structures were 87.65%, 87.82%, 96.99%, and 95.25%, respectively. This methodology exhibits significant applicability and practical value for the intelligent inspection of hydraulic structures.

Abstract Defective renal excretion and increased production of uric acid engender hyperuricemia that predisposes to gout. However, molecular mechanisms underlying defective uric acid excretion remain largely unknown. Here, we report a rare genetic variant of gout-unprecedented NUMB gene within a hereditary human gout family, which was identified by an unbiased genome-wide sequencing approach. This dysfunctional missense variant within the conserved region of the NUMB gene (NUMBR630H) underwent intracellular redistribution and degradation through an autophagy-dependent mechanism. Mechanistically, we identified the uric acid transporter, ATP Binding Cassette Subfamily G Member 2 (ABCG2), as a novel NUMB-binding protein through its intracellular YxNxxF motif. In polarized renal tubular epithelial cells (RTECs), NUMB promoted ABCG2 trafficking towards the apical plasma membrane. Genetic loss-of-function of NUMB resulted in redistribution of ABCG2 in the basolateral domain and ultimately defective excretion of uric acid. To recapitulate the clinical situation in human gout patients, we generated a NUMBR630H knock-in mouse strain, which showed marked increases of serum urate and decreased uric acid excretion. The NUMBR630H knock-in mice exhibited clinically relevant hyperuricemia. In summary, we have uncovered a novel NUMB-mediated mechanism of uric acid excretion and a functional missense variant of NUMB in humans, which causes hyperuricemia and gout.

Abstract This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. We retrospectively collected data from 717 hormone-sensitive prostate cancer (HSPC) patients at Yunnan Cancer Hospital. Of these, data from 526 patients were used for modeling. Seven auxiliary models were established using Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), Extreme gradient boosting tree (XGBoost), Adaptive Boosting (Adaboost), and artificial neural network (ANN) based on 21 clinical biochemical indicators and features. Evaluation metrics included accuracy (ACC), precision (PRE), specificity (SPE), sensitivity (SEN) or regression rate(Recall), and f1 score. Evaluation metrics for the models primarily included ACC, PRE, SPE, SEN or Recall, f1 score, and area under the curve(AUC). Evaluation metrics were visualized using confusion matrices and ROC curves. Among the ensemble learning methods, RF, XGBoost, and Adaboost performed the best. RF achieved a training dataset score of 0.769 (95% CI: 0.759—0.835) and a testing dataset score of 0.755 (95% CI: 0.660—0.760) (AUC: 0.786, 95%CI: 0.722—0.803), while XGBoost achieved a training dataset score of 0.755 (95% CI: 95%CI: 0.711—0.809) and a testing dataset score of 0.745 (95% CI: 0.660—0.764) (AUC: 0.777, 95% CI: 0.726—0.798). Adaboost scored 0.789 on the training dataset (95% CI: 0.782—0.857) and 0.774 on the testing dataset (95% CI: 0.651—0.774) (AUC: 0.799, 95% CI: 0.703—0.802). In terms of feature importance (FI) in ensemble learning, Bone metastases at first visit, prostatic volume, age, and T1-T2 have significant proportions in RF’s FI. fPSA, TPSA, and tumor burden have significant proportions in Adaboost’s FI, while f/TPSA, LDH, and testosterone have the highest proportions in XGBoost. Our findings indicate that ensemble learning methods demonstrate good performance in classifying HSPC patient data, with TNM staging and fPSA being important classification indicators. These discoveries provide valuable references for distinguishing different Gleason scores, facilitating more accurate patient assessments and personalized treatment plans.

Gastric cancer (GC), among the most prevalent malignant tumors globally, demonstrates a rapid metastasis rate leading to high mortality. While microRNAs (miRNAs) have been recognized as critical regulators of tumor progression, the specific role of miR-28–3p in GC remains unclear. In this study, we demonstrate that miR-28–3p acts as a tumor suppressor by inhibiting GC cell proliferation and EMT-driven migration in vitro, as well as tumor growth and metastasis in vivo. Mechanistically, miR-28–3p directly targets ADP ribosylation factor 6 (ARF6), a small GTPase identified as an oncogene in GC. We reveal that ARF6 is significantly upregulated in GC and activates the GLI1/2-dependent Hedgehog signaling pathway, promoting tumor growth and EMT. Notably, ARF6 knockdown mitigates the pro-tumor effects caused by miR-28–3p deficiency, while combined ARF6 inhibition and Hedgehog pathway suppression exhibit synergistic anti-tumor effects. This study establishes the miR-28-3p-ARF6-Hedgehog signaling axis as a critical regulatory pathway in GC progression. Our findings provide novel insights into GC pathogenesis and highlight the therapeutic potential of targeting this axis for innovative treatment strategies.

Background Prostate cancer (PCa) is among the three main types of cancer. Although prostate-specific antigen (PSA) is routinely tested, it has disadvantages, such as poor prognostic ability. Therefore, finding more PCa markers and therapeutic targets remains a subject of study. CircRNAs have been found to have regulatory roles in various diseases, such as diabetes, Central Nervous System (CNS) neuropathy, etc. where their application in cancer is even more valuable. Therefore, this paper aims to search for differentially expressed circRNAs in PCa and find downstream targeting pathways related to autophagy.Method By detecting the expression of circRNA in the samples, hsa_circ_0119816 was finally identified as the research target. The properties of circRNA were verified by RNase R, actinomycin D, and fluorescence in situ hybridization (FISH). The downstream target miRNAs and target proteins were predicted by an online database, and the targeting relationship was verified using dual luciferase and RNA Immunoprecipitation. The effects of circRNAs and their downstream signalling pathways on prostate cancer cell proliferation, migration, EMT and autophagy were examined by CCK-8, Transwell, immunofluorescence and Western blotting.Results CircBIRC6 is highly expressed in prostate cancer samples. Knockdown of its expression inhibits cell proliferation, invasion, EMT and autophagy and promotes apoptosis. CircBIRC6/miRNA-574-5p/DNAJB1 is a molecular axis that regulates prostate cancer cells.

Takayasu's arteritis is a primary systemic vasculitis that affects predominantly large vessels, affecting the aorta and its major branches. We report a case of adolescent female patient who initially experienced numbness and weakness in her limbs, subsequently developing severe hypertension. Physical examination revealed uneven blood pressure in the limbs and a murmur in the auscultation area of the abdominal aorta without decreased pulses. Auxiliary examinations revealed diffuse blood vessel stenosis, leading to the diagnosis of Takayasu's arteritis. One month later, the patient was diagnosed with multiple cerebral hemorrhages following sudden impairment of limb movement. Digital subtraction angiography did not reveal any evident vascular malformations or aneurysms. Following surgery and biologic intervention with tocilizumab, the patient's condition improved, with no new bleeding episodes and stable blood pressure control achieved. We also reviewed the literature that have been previously reported with hypertensive intracerebral hemorrhage complicated by Takayasu's arteritis. We recommend that Takayasu's arteritis be taken into account when considering the hypertension in young patients. Timely vascular imaging and standardized treatment are imperative for diagnosing and managing effectively.

Background: Chemotherapy is a primary treatment for breast cancer (BC), yet many patients develop resistance over time. This study aims to identify critical factors contributing to chemoresistance and their underlying molecular mechanisms, with a focus on reversing this resistance. Methods: We utilized samples from the Gene Expression Omnibus (GEO) and West China Hospital to identify and validate genes associated with chemoresistance. Functional studies were conducted using MDA-MB-231 and MCF-7 cell lines, involving gain-of-function and loss-of-function approaches. RNA sequencing (RNA-seq) identified potential mechanisms. We examined interactions between DNAJC12, HSP70, and AKT using co-immunoprecipitation (Co-IP) assays and established cell line-derived xenograft (CDX) models for in vivo validations. Results: Boruta analysis of four GEO datasets identified DNAJC12 as highly significant. Patients with high DNAJC12 expression showed an 8 % pathological complete response (pCR) rate, compared to 38 % in the low expression group. DNAJC12 inhibited doxorubicin (DOX)-induced cell death through both ferroptosis and apoptosis. Combining apoptosis and ferroptosis inhibitors completely reversed DOX resistance caused by DNAJC12 overexpression. RNA-seq suggested that DNAJC12 overexpression activated the PI3K-AKT pathway. Inhibition of AKT reversed the DOX resistance induced by DNAJC12, including reduced apoptosis and ferroptosis, restoration of cleaved caspase 3, and decreased GPX4 and SLC7A11 levels. Additionally, DNAJC12 was found to increase AKT phosphorylation in an HSP70-dependent manner, and inhibiting HSP70 also reversed the DOX resistance. In vivo studies confirmed that AKT inhibition reversed DNAJC12-induced DOX resistance in the CDX model. Conclusion: DNAJC12 expression is closely linked to chemoresistance in BC. The DNAJC12-HSP70-AKT signaling axis is crucial in mediating resistance to chemotherapy by suppressing DOX-induced ferroptosis and apoptosis. Our findings suggest that targeting AKT and HSP70 activities may offer new therapeutic strategies to overcome chemoresistance in BC.

In the present paper, we investigate a fractional magnetic system involving critical concave–convex nonlinearities with Laplace operators. Specifically, (−Δ)Asu1=λ1|u1|q−2u1 + 2α1α1+β1|u1|α1−2u1|u2|β1 in Ω, (−Δ)Asu2=λ2|u2|q−2u2+2β1α1+β1|u2|β1−2u2|u1|α1 in Ω, u1=u2=0 in Rn∖Ω, where Ω is a bounded set with Lipschitz boundary ∂Ω in Rn, 11,β1>1, α1+β1=2s∗=2nn−2s, 2s∗ is the fractional critical Sobolev exponent, and (−Δ)As is a fractional magnetic Laplace operator. By using Lusternik–Schnirelmann’s theory, we prove the existence result of infinitely many solutions for the magnetic fractional system.

Antiplatelet therapy is the foundational treatment for the prevention and treatment of coronary and cerebrovascular ischemic events in patients with coronary heart disease, ischemic stroke, and transient ischemic attack (TIA). However, with more and more studies reporting an increased risk of thrombosis in some patients due to poor response to therapeutic agents, the selection of appropriate P2Y12 inhibitors has become a major challenge that needs to be addressed urgently. Currently, commonly used oral P2Y12 inhibitors include clopidogrel, ticagrelor, and prasugrel. Assessing patients' risk factors before the development of treatment regimens by effectively predicting the risk of high platelet reactivity with specific P2Y12 inhibitors in advance to avert the occurrence of major adverse cardiovascular and cerebrovascular events (MACCE) is the key point to the problem. Up to now, methods available for predicting platelet reactivity include genetic testing, platelet function testing, and risk scores. This review provides a summarization of the existent available identification methods and analyzes the advantages and drawbacks of different methods in specific clinical settings, intending to guide the rational clinical application of P2Y12 receptor inhibitors.

In response to the issues of poor content correlation and insufficient intelligent decision support in emergency plans for water conservancy projects, a method for intelligent generation of emergency plans based on knowledge graphs is proposed. Utilizing pre-trained language models (PTM) based on entity masking, the accuracy of entity recognition tasks is enhanced by uncovering contextual features surrounding the masked entities. By employing translations, rotations, and superpositions within the vector space, a multiview convolutional neural network (MCNN) is constructed to enhance the accuracy of relation extraction through complementary and integrated feature representation. Integrating PTM with MCNN enables the construction of an emergency entity relationship extraction method based on PTM-MCNN. Neo4j is utilized for storing entity relationship triplets to construct an emergency knowledge graph. Through the utilization of the mutual information criterion, knowledge retrieval and matching are performed to accomplish the intelligent generation of emergency plans. The results indicate that PTM-MCNN achieves high recognition accuracy (F1 score of 92.2%), ensuring the reliability of the generated emergency plans. Related studies can effectively improve the intelligence of emergency management of water conservancy projects.

Background: Little is known about the benefits of adjuvant endocrine therapy (ET) in low ER-positive breast cancer (1%–10%) patients. We analyzed the association between ET and breast cancer-specific survival (BCSS) in these patients with respect to the regimen and the duration of ET. Methods: Patients were classified into three groups based on the regimen and duration of ET. The regimens included aromatase inhibitor (AI) monotherapy or sequential tamoxifen followed by an AI (AI/T + AI), or only tamoxifen and no ET. The duration of ET included 2–3 years and >3 years. Multivariate Cox regression analysis was employed to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs). Results: Of the 10,696 patients diagnosed with breast cancer between 2010 and 2020, 407 women were identified with ER-low positive disease and met the inclusion criteria. During a median follow-up of 5.2 years, patients who received ET improved BCSS. Of them, those with AI/T + AI had increased BCSS compared to patients without ET, after adjusting for demographics and tumor characteristics, especially in ER-low/HER-2-positive breast cancer. After additional adjustment for treatment mode, the association maintained a similar trend. Patients who received >3 years of ET was associated with a better DFS. There was no significant difference in BCSS between patients with 2–3 years and >3 years of ET. Conclusion: For ER-low patients, findings suggest that ET with AI/T + AI may be a reasonable treatment alternative. This effect should be assessed in randomized studies.

This paper presents a self-coherent optical feedback system that achieves resonance between the external cavity mode and the relaxation oscillation frequency of distributed feedback (DFB) laser and the repetition frequency of Fabry–Perot (FP) laser, all in an effort to achieve optical feedback self-locking. Results using this system show that for FP lasers, feedback is able to reduce the 3 dB radio frequency linewidth from 2 MHz to 600 kHz. In the case of DFB lasers, an electric frequency comb with an external cavity repetition rate of 17.25 MHz is achieved. This research presents a significant step toward the improvement of the performance of quantum dot lasers in optical communication systems.

Background: We aimed to analyse the discrepancy in clinical features and prognosis between molecular subtypes in primary ductal carcinoma in situ (DCIS) patients with lumpectomy. Methods: Primary DCIS patients were identified from the Surveillance, Epidemiology, and End Results registries database from 2010 to 2017. Based on immunohistochemistry markers of hormone receptor (HR) and human epidermal growth factor receptor-2 (HER2), enrolled DCIS cases were divided into four molecular subtypes, HR-HER2-, HR-HER2+, HR + HER2+, and HR + HER2-. Clinical features and prognosis were compared between molecular subtypes. Radiotherapy (RT) effects on prognosis were also analysed in each molecular subtype. Results: A total of 5,628 DCIS cases were retrospectively enrolled in this study. HR-HER2-, HR-HER2+, HR+HER2+, and HR+HER2- are 299 (5.3%), 498 (8.8%), 1,086 (19.3%), and 3,745 (66.5%), respectively. HR + HER2- cases have smaller tumor size (72.6%, P

Abstract Background Myocardial infarction (MI) represents a severe cardiovascular disease with limited therapeutic agents. This study was aimed to elucidate the role of the exosomes derived from human placental mesenchymal stem cells (PMSCs-Exos) in MI. Methods PMSCs were isolated and cultured in vitro, with identification by both transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). To further investigate the effects of PMSC-Exos on MI, C57BL/6 mice were randomly divided into Sham group, MI group, and PMSC-Exos group. After 4 weeks of the intervention, cardiac function was assessed by cardiac echocardiography, electrocardiogram and masson trichrome staining; lipid indicators were determined by automatic biochemical instrument; inflammatory cytokines were measured by cytometric bead array (CBA); gut microbiota, microbial metabolites short chain fatty acids (SCFAs) as well as lipopolysaccharide (LPS) were separately investigated by 16S rRNA high throughput sequencing, gas chromatography mass spectrometry (GC–MS) and tachypleus amebocyte lysate kit; transcriptome analysis was used to test the transcriptional components (mRNA\miRNA\cirRNA\lncRNA) of PMSC-Exos. Results We found that human PMSC-Exos were obtained and identified with high purity and uniformity. MI model was successfully established. Compared to MI group, PMSC-Exos treatment ameliorated myocardial fibrosis and left ventricular (LV) remodeling (P

Chronic low-grade inflammation is regarded to an important signature of atherosclerosis (AS). Macrophage (Mψ) and related polarization have been demonstrated to play a crucial role in the occurrence and development of AS inflammation. Butyrate, a bioactive molecule produced by the intestinal flora, has been increasingly demonstrated to exhibit a vital role for regulating the inflammation in chronic metabolic diseases. However, the effectiveness and multiple anti-inflammation mechanisms of butyrate on AS still need to be further understood. ApoE-/- mice fed with high-fat diet as AS model were administered with sodium butyrate (NaB) for 14 weeks of treatment. Our results showed that the atherosclerotic lesion in the AS group was dramatically reduced after NaB intervention. Moreover, deteriorated routine parameters of AS including body weights (BWs), low-density lipoprotein (LDL-C), triglyceride (TG), total cholesterol (TC) were significantly reversed by NaB administration. Abnormal elevated plasma and aorta pro-inflammatory indicators including interleukin (IL)-1β, IL-6, IL-17A, tumor necrosis factor (TNF)-α and lipopolysaccharide (LPS), as well as reduced anti-inflammatory IL-10 in plasma were respectively rectified after NaB administration. Consistently, accumulated Mψ and associated imbalance of polarization in the arota were attenuated with NaB treatment. Importantly, we demonstrated that the suppression of Mψ and associated polarization of NaB was dependent on binding G-protein coupled receptor (GPR) and inhibiting histone deacetylase HDAC3. Moreover, we found that intestinal butyrate-producing bacteria, anti-inflammatory bacteria and intestinal tight junction protein zonula occludens-1 (ZO)-1 may contribute to this effectiveness. Intriguingly, according to transcriptome sequencing of atherosclerotic aorta, 29 elevated and 24 reduced miRNAs were found after NaB treatment, especially miR-7a-5p, suggesting that non-coding RNA may possess a potential role in the protection of NaB against AS. Correlation analysis showed that there were close complicated interactions among gut microbiota, inflammation and differential miRNAs. Collectively, this study revealed that dietary NaB may ameliorate atherosclerotic inflammation by regulating Mψ polarization via GPR43/HDAC-miRNAs axis in ApoE-/- mice.

Green synthesis and metal oxide composites have attracted much attention from researchers of industry and academia. As a typical application of green synthesis and metal oxide composites, the protection of oil and gas reservoirs is related to various links such as exploration, drilling, completion, and development. It is a complex and systematic project, which directly affects whether the oil and gas fields can be discovered, evaluated, and efficiently developed in time, and it is also related to the development of oil and gas fields recovery rate. As the most critical part of oil and gas well construction, the cementing process mainly pays attention to the safe pumping of the cement slurry and the long-term effective interlayer isolation capability of the cement sheath. Less attention is paid to the reservoir protection during the cementing process. The high-pressure difference between the annulus and the formation, the high fluid loss, and the high solids content of the cementing slurry during the cementing process have also become major challenges. In order to solve this problem, this study takes a typical clastic rock block in an oilfield in western China as the research object and carries out a geological survey of fracture development, pressure deficit, and cement slurry permeability leakage in the reservoir. The reservoir physical properties, clay mineral characteristics, and formation water quality of rock reservoirs are analyzed. The influence of cement slurry filtrate and solid phase particles on reservoir clay expansion rate and permeability was tested by core porosity and permeability tester. XRD and SEM techniques were used to analyze the damage mechanism of cement slurry filtrate and solid phase particles to the reservoir. The research results show that the average porosity of the clastic rock reservoir in the study area is 15%, the permeability is high, the average pore size of the reservoir is between 37 and 56 μm, the microfractures are developed in the reservoir section, and the porosity and permeability conditions are good; high-valent cations and inorganic ions in the filtrate generate inorganic scales such as CaCO3 and Mg(OH)2 and cross-link with dissolved polymers to form flocculation substances, which cause the filtrate to damage the reservoir, and at the same time, the cement particles in the pore throats in the near wellbore zone are lost along with the leakage. Furthermore, hydration, tightly bonding the inert admixture and the clastic rock formation, forms a tight sealing layer, which reduces the permeability of the reservoir sharply; the expansive clay particles in the reservoir absorb the moisture of the cement slurry filtrate and expand. The volume of the particles increases, and the porous formation containing expansive clay minerals absorbs moisture and causes internal expansion, and the volume expansion rate can reach 9%, which eventually causes the porosity and permeability of the reservoir to decrease, resulting in reservoir damage and solid phase in the cement slurry. The damage of particles to the reservoir is mainly due to the blockage of the reservoir pore throats and the hydration and consolidation of cement particles inside the reservoir caused by the external admixtures in the cement slurry that do not participate in the hydration reaction. The solid phase particles form a filter cake on the surface of the reservoir core and cannot enter the reservoir, but under the condition of porous formation leakage, the solid phase particles with a particle size of 1–10 μm in the cement slurry will directly penetrate into the reservoir rock resulting in shallow plugging in the reservoir near the wellbore. The research results provide theoretical data support for the research on low-damage cementing slurry technology in clastic rock reservoirs. The work provides an important application guidance to green synthesis and metal oxide composites.

Summary: Fruit flies sense the features of food that are driven by particle size, including smoothness versus grittiness, by deflection of sensilla decorating the labellum, and md-L neurons. We describe adaptation of the Drosophila proboscis extension response assay, including steps to perform the taste tests and score behavioral responses, to determine preferences to foods with different sized particles. We also describe calcium imaging in GCaMP-expressing flies to assess the responses of md-L neurons to different levels of taste sensilla deflection.For complete details on the use and execution of this protocol, please refer to Li and Montell. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Maritime accidents, such as ship collisions and oil spills, directly affect maritime transportation, pollute the water environment, and indirectly threaten life and property safety. Predicting the maritime accident susceptibility and taking measures in advance can effectively avoid the accident probability and reduce the risk. Therefore, this study established dynamic multi-period (monthly, yearly, and five-yearly) maritime accident prediction models based on the random forest (RF) algorithm and Automatic Identification System (AIS) data for susceptibility assessment. First, based on historical maritime accidents and influencing factor data, we generated the feature matrixes and selected the conditioning factors using the Pearson correlation coefficient. Then, we constructed the accident susceptibility models using the RF method and evaluated the model performances based on the accuracy, recall, precision, F1-measure, ROC, and AUC values. Finally, we developed accident susceptibility maps for different period scales. The results show that the monthly, yearly, and five-yearly models performed well according to the validation values. And the three-period susceptibility maps show similar patterns. The high-susceptibility areas are close to the shore, especially from the Shanghai shore to the Guangxi shore. In addition, the ship density and bathymetry are the most critical factors among the ten influencing factors in the three models, contributing around 25% and 20% of the total information. These models and maps can provide technological support for maritime accident susceptibility assessment on a multi-period scale, which can be helpful for route planning and resource allocation in marine management.

Road extraction from high-resolution remote sensing images is a critical task in image understanding and analysis, yet it poses significant challenges because of road occlusions caused by vegetation, buildings, and shadows. Deep convolutional neural networks have emerged as the leading approach for road extraction because of their exceptional feature representation capabilities. However, existing methods often yield incomplete and disjointed road extraction results. To address this issue, we propose CR-HR-RoadNet, a novel high-resolution road extraction network that incorporates local and global context reasoning. In this work, we introduce a road-adapted high-resolution network as the feature encoder, effectively preserving intricate details of narrow roads and spatial information. To capture multi-scale local context information and model the interplay between roads and background environments, we integrate multi-scale features with residual learning in a specialized multi-scale feature representation module. Moreover, to enable efficient long-range dependencies between different dimensions and reason the correlation between various road segments, we employ a lightweight coordinate attention module as a global context-aware algorithm. Extensive quantitative and qualitative experiments on three datasets demonstrate that CR-HR-RoadNet achieves superior extraction accuracy across various road datasets, delivering road extraction results with enhanced completeness and continuity. The proposed method holds promise for advancing road extraction in challenging remote sensing scenarios and contributes to the broader field of deep-learning-based image analysis for geospatial applications.

This paper proposes a dual inductor-capacitor (LC) circuit integrated wireless and passive force and temperature sensor for the simultaneous measurement of force and temperature in high-temperature environments. The sensor is fabricated by a two-step process: the preparation of the Al2O3 substrate and the fabrication of the dual LC sensor with Ag paste using screen-printing technology and metallization. The variation in ambient force and temperature can be detected wirelessly by extracting the resonant frequencies of the antenna. The sensor can work in the force range of 0–10 N and temperature range of 25–500 °C with a maximum force sensitivity of 107 kHz/N at 500 °C and temperature sensitivity of 21.7 kHz/°C. To precisely measure the force, the temperature compensation method is proposed. The sensor has the advantages of low cost, simple fabrication and test, and high stability and repeatability, which are promising for the force and temperature application on the engine turbine blade in high-temperature environments.

To solve the problems of low prediction accuracy, poor stability, and low calculation efficiency in runoff forecasting, this study develops an extreme learning machine (ELM) model based on improved complete ensemble empirical mode decomposition adaptive noise (CEEMDAN). The model first uses orthogonal triangular decomposition (QR) to redefine the ELM hidden layer output to construct the orthogonal triangular ELM (QR-ELM). It then introduces the online sequence mechanism (OS) into the QR-ELM model to construct online sequence OR-ELM (OS-QR-ELM), which can effectively improve the efficiency of the ELM models. Then, it uses the correlation wave extension method to extend both ends of the original signal to solve the end effect of CEEMDAN. Finally, it integrates CEEMDAN and OS-QR-ELM combined with parallel computing ideas to construct a parallel CEEMDAN-OS-QR-ELM runoff prediction method. The experimental results show that compared with the support vector regression method combined with empirical mode decomposition, the accuracy and reliability of the parallel CEEMDAN-OS-QR-ELM model was 1.09% and 8% higher, respectively. Compared with the ELM model, the efficiency of OS-QR-ELM was 5%.

The bidding strategies of power suppliers to maximize their interests is of great importance. The proposed bi-level optimization model with coalitions of power suppliers takes restraint factors into consideration, such as operating cost reduction, potential cooperation, other competitors’ bidding behavior, and network constraints. The upper model describes the coalition relationship between suppliers, and the lower model represents the independent system operator’s optimization without network loss (WNL) or considering network loss (CNL). Then, a novel algorithm, the evolutionary game theory algorithm (EGA) based on a hybrid particle swarm optimization and improved firefly algorithm (HPSOIFA), is proposed to solve the bi-level optimization model. The bidding behavior of the power suppliers in equilibrium with a dynamic power market is encoded as one species, with the EGA automatically predicting a plausible adaptation process for the others. Individual behavior changes are employed by the HPSOIFA to enhance the ability of global exploration and local exploitation. A novel improved firefly algorithm (IFA) is combined with a chaotic sequence theory to escape from the local optimum. In addition, the Shapley value is applied to the profit distribution of power suppliers’ cooperation. The simulation, adopting the standard IEEE-30 bus system, demonstrates the effectiveness of the proposed method for solving the bi-level optimization problem

Abstract Background The scoring of Ki-67 is highly relevant for the diagnosis, classification, prognosis, and treatment in breast invasive ductal carcinoma (IDC). Traditional scoring method of Ki-67 staining followed by manual counting, is time-consumption and inter−/intra observer variability, which may limit its clinical value. Although more and more algorithms and individual platforms have been developed for the assessment of Ki-67 stained images to improve its accuracy level, most of them lack of accurate registration of immunohistochemical (IHC) images and their matched hematoxylin-eosin (HE) images, or did not accurately labelled each positive and negative cell with Ki-67 staining based on whole tissue sections (WTS). In view of this, we introduce an accurate image registration method and an automatic identification and counting software of Ki-67 based on WTS by deep learning. Methods We marked 1017 breast IDC whole slide imaging (WSI), established a research workflow based on the (i) identification of IDC area, (ii) registration of HE and IHC slides from the same anatomical region, and (iii) counting of positive Ki-67 staining. Results The accuracy, sensitivity, and specificity levels of identifying breast IDC regions were 89.44, 85.05, and 95.23%, respectively, and the contiguous HE and Ki-67 stained slides perfectly registered. We counted and labelled each cell of 10 Ki-67 slides as standard for testing on WTS, the accuracy by automatic calculation of Ki-67 positive rate in attained IDC was 90.2%. In the human-machine competition of Ki-67 scoring, the average time of 1 slide was 2.3 min with 1 GPU by using this software, and the accuracy was 99.4%, which was over 90% of the results provided by participating doctors. Conclusions Our study demonstrates the enormous potential of automated quantitative analysis of Ki-67 staining and HE images recognition and registration based on WTS, and the automated scoring of Ki67 can thus successfully address issues of consistency, reproducibility and accuracy. We will provide those labelled images as an open-free platform for researchers to assess the performance of computer algorithms for automated Ki-67 scoring on IHC stained slides.

Abstract Background Penile squamous cell carcinoma (PSCC) represents an important public health problem for developing countries. The major prognostic factors in PSCC are pathological subtype, perineural invasion, lymphovascular invasion, depth of invasion and grade, which are hard to obtain precisely before the operation. Besides, micro-metastases will be detected in about 30% of intermediate-risk patients with clinically non-palpable inguinal lymph nodes after inguinal lymph node dissection (ILND). It means approximately 70% of patients are unable to benefit from ILND who might suffered from the complications of surgery. We hope some biomarkers could be found which are able to predict the outcome before surgery and reflect the inguinal lymph nodes metastasis. Methods A total of 349 consecutive patients of penile cancer in Yunnan cancer hospital in China between October 2002 and December2017. Two hundred twenty-five was succeed to follow-up. The association between NLR, LMR, PLR, LDH and Overall survival (OS), progression free survival (PFS), inguinal lymph node (N stage) was analyzed with K-M analysis, univariable, multivariable logistic regression and Kendall’s tau-b correlation coefficient. Results Multivariable analysis reveal that only PLR was significant independent factor which is associated with inferior OS and PFS; Age and LDH was associated with inferior OS; Lymph node and metastatic status remained significant for OS and PFS as NCCN and EAU Guidelines indicated; the tumor type, initial treatment and NLR LMR were not significant in predicting both OS and PFS. NLR, LMR and PLR were corresponded to N stage, while LDH was not associated with the N stage based on logistic regression model analysis. NLR, LMR and PLR were found weakly related to N stage through an application of Kendall’s tau-b correlation coefficient. Conclusions PLR was significant independent factors for OS and PFS, Age and LDH was significant independent factors for OS. NLR, LMR, PLR was corresponded to N stage.

A passive substrate integrated waveguide (SIW) sensor based on the complementary split ring resonator (CSRR) is presented for pressure detection in high-temperature environments. The sensor pressure sensing mechanism is described through circuit analysis and the electromagnetic coupling principle. The pressure sensor is modeled in high frequency structure simulator (HFSS), designed through parameter optimization. According to the optimized parameters, the sensor was customized and fabricated on a high temperature co-fired ceramic (HTCC) substrate using the three-dimensional co-fired technology and screen-printing technology. The pressure sensor was tested in the high-temperature pressure furnace and can work stably in the ambient environment of 25−500 °C and 10−300 kPa. The pressure sensitivity is 139.77 kHz/kPa at 25 °C, and with increasing temperature, the sensitivity increases to 191.97 kHz/kPa at 500 °C. The temperature compensation algorithm is proposed to achieve accurate acquisition of pressure signals in a high-temperature environment.

Atherosclerosis (AS) is closely associated with abnormally chronic low-grade inflammation and gut dysbiosis. Flaxseed oil (FO) rich in omega-3 polyunsaturated fatty acids (PUFAs), which are mainly composed of alpha-linolenic acid (ALA, 18:3 omega-3), has been demonstrated to exhibit pleiotropic benefits in chronic metabolic diseases. However, the impact of dietary ALA-rich FO on AS and its associated underlying mechanisms remain poorly understood. Thus, the present study was designed as two phases to investigate the effects in atherosclerotic Apolipoprotein E (ApoE)−/− mice. In the initial portion, the ApoE−/− mice were randomly allocated to three groups: control group (CON), model group (MOD), and FO-fed model group (MOD/FO) and were treated for 12 weeks. The second phase used antibiotic (AB)-treated ApoE−/− mice were divided into two groups: AB-treated model group (AB/MOD) and FO-fed AB-treated model group (AB/FO). In the results, the dietary ALA-rich FO administration ameliorated atherosclerotic lesion, as well as the parameters of AS (body weights (BWs) and the total bile acids (TBA). Chronic systemic/vascular inflammatory cytokines and in situ macrophages (Mψs) were reduced with FO intervention. In addition, the FO improved the gut integrity and permeability by decreasing the plasma lipopolysaccharide (LPS). Moreover, gut dysbiosis and metabolites [short-chain fatty acids (SCFAs) and bile acids (BAs)] in AS were modulated after FO treatment. Intriguingly, during an AB-treated condition, a significantly weakened amelioration of FO-treated on AS proposed that the intestinal microbiota contributed to the FO effects. A correlation analysis showed close relationships among gut bacteria, metabolites, and inflammation. Collectively, these results suggested that the dietary ALA-rich FO ameliorated the AS in ApoE−/− mice via the gut microbiota-inflammation-artery axis.

Feature selection and feature transformation are the two main approaches to reduce dimensionality, and they are often presented separately. In this study, a novel robust and efficient feature selection method, called FS-VLDA-L2,1 (feature selection based on variant of linear discriminant analysis and L2,1-norm), is proposed by combining a new variant of linear discriminant analysis and L2,1 sparsity regularization. Here, feature transformation and feature selection are integrated into a unified optimization objective. To obtain significant discriminative power between classes, all the data in the same class are expected to be regressed to a single vector, and the important task is to explore a transformation matrix such that the squared regression error is minimized. Therefore, we derive a new discriminant analysis from a novel view of least squares regression. In addition, we impose row sparsity on the transformation matrix through L2,1-norm regularized term to achieve feature selection. Consequently, the most discriminative features are selected, simultaneously eliminating the redundant ones. To address the L2,1-norm based optimization problem, we design a new efficient iterative re-weighted algorithm and prove its convergence. Extensive experimental results on four well-known datasets demonstrate the performance of our feature selection method.

Abstract In this paper we investigate the existence of infinitely many solutions for nonlocal Schrödinger equation involving a magnetic potential ( − △ ) A s u + V ( x ) u = f ( x , | u | ) u , in R N , $$ (-\triangle )_{A}^{s}u+V(x)u=f\bigl(x, \vert u \vert \bigr)u, \quad\text{in } {\mathbb {R}}^{N}, $$ where s ∈ ( 0 , 1 ) $s\in (0,1)$ is fixed, N > 2 s $N>2s$ , V : R N → R + $V:{\mathbb {R}}^{N}\rightarrow {\mathbb {R}}^{+}$ is an electric potential, the magnetic potential A : R N → R N $A:{\mathbb {R}}^{N}\rightarrow {\mathbb {R}}^{N}$ is a continuous function, and ( − △ ) A s $(-\triangle )_{A}^{s}$ is the fractional magnetic operator. Under suitable assumptions for the potential function V and nonlinearity f, we obtain the existence of infinitely many nontrivial high energy solutions by using the variant fountain theorem.

BackgroundBladder cancer (BC) is a molecular heterogeneous malignant tumor; the treatment strategies for advanced-stage patients were limited. Therefore, it is vital for improving the clinical outcome of BC patients to identify key biomarkers affecting prognosis. Ferroptosis is a newly discovered programmed cell death and plays a crucial role in the occurrence and progression of tumors. Ferroptosis-related genes (FRGs) can be promising candidate biomarkers in BC. The objective of our study was to construct a prognostic model to improve the prognosis prediction of BC.MethodsThe mRNA expression profiles and corresponding clinical data of bladder urothelial carcinoma (BLCA) patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. FRGs were identified by downloading data from FerrDb. Differential analysis was performed to identify differentially expressed genes (DEGs) related to ferroptosis. Univariate and multivariate Cox regression analyses were conducted to establish a prognostic model in the TCGA cohort. BLCA patients from the GEO cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were used to explore underlying mechanisms.ResultsNine genes (ALB, BID, FADS2, FANCD2, IFNG, MIOX, PLIN4, SCD, and SLC2A3) were identified to construct a prognostic model. Patients were classified into high-risk and low-risk groups according to the signature-based risk score. Receiver operating characteristic (ROC) and Kaplan–Meier (K–M) survival analysis confirmed the superior predictive performance of the novel survival model based on the nine-FRG signature. Multivariate Cox regression analyses showed that risk score was an independent risk factor associated with overall survival (OS). GO and KEGG enrichment analysis indicated that apart from ferroptosis-related pathways, immune-related pathways were significantly enriched. ssGSEA analysis indicated that the immune status was different between the two risk groups.ConclusionThe results of our study indicated that a novel prognostic model based on the nine-FRG signature can be used for prognostic prediction in BC patients. FRGs are potential prognostic biomarkers and therapeutic targets.

In this paper, a new hybrid method for controlling a wheeled robot is introduced. Model predictive control (MPC) is the main controller and a fuzzy controller is used as a compensator. The wheeled robot is a nonlinear, multi-input–multi-output system that requires new and combined methods for precise control. In order to stabilize the system the appropriate control input is set, and at the same time, attention is paid to the reference signal tracking. In the simulation section, several different scenarios are applied and parameter uncertainties and their effects on the controller’s performance are evaluated. The simulation results show the success and efficiency of the proposed method.

Atherosclerosis (AS) is closely associated with chronic low-grade inflammation and gut dysbiosis. Metformin (MET) presents pleiotropic benefits in the control of chronic metabolic diseases, but the impacts of MET intervention on gut microbiota and inflammation in AS remain largely unclear. In this study, ApoE-/- mice with a high-fat diet (HFD) were adopted to assess the MET treatment. After 12 weeks of MET intervention (100mg·kg-1·d-1), relevant indications were investigated. As indicated by the pathological measurements, the atherosclerotic lesion was alleviated with MET intervention. Moreover, parameters in AS including body weights (BWs), low-density lipoprotein (LDL), triglyceride (TG), total cholesterol (TC) and malondialdehyde (MDA) were elevated; whereas high-density lipoprotein (HDL) and total superoxide dismutase (T-SOD) levels were decreased, which could be reversed by MET intervention. Elevated pro-inflammatory interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α and lipopolysaccaride (LPS) in AS were decreased after MET administration. However, anti-inflammatory IL-10 showed no significant difference between AS group and AS+MET group. Consistently, accumulated macrophages in the aorta of AS were conversely lowered with MET treatment. The results of 16S rRNA sequencing and analysis displayed that the overall community of gut microbiota in AS was notably changed with MET treatment mainly through decreasing Firmicutes, Proteobacteria, Romboutsia, Firmicutes/Bacteroidetes, as well as increasing Akkermansia, Bacteroidetes, Bifidobacterium. Additionally, we found that microbiota-derived short-chain fatty acids (SCFAs) including acetic acid, propionic acid, butyric acid and valeric acid in AS were decreased, which were significantly up-regulated with MET intervention. Consistent with the attenuation of MET on gut dysbiosis, decreased intestinal tight junction protein zonula occludens-1 (ZO)-1 in AS was restored after MET supplementation. Correlation analysis showed close relationships among gut bacteria, microbial metabolites SCFAs and inflammation. Collectively, MET intervention ameliorates AS in ApoE-/- mice through restoring gut dysbiosis and anti-inflammation, thus can potentially serve as an inexpensive and effective intervention for the control of the atherosclerotic cardiovascular disease.

This paper is concerned with an elliptic system of Kirchhoff type, driven by the variable-order fractional px-operator. With the help of the direct variational method and Ekeland variational principle, we show the existence of a weak solution. This is our first attempt to study this kind of system, in the case of variable-order fractional variable exponents. Our main theorem extends in several directions previous results.

In this study, we investigate the existence and multiplicity of solutions for a fractional discrete p−Laplacian equation on Z. Under suitable hypotheses on the potential function V and the nonlinearity f, with the aid of Ekeland’s variational principle, via mountain pass lemma, we obtain that this equation exists at least two nonnegative and nontrivial homoclinic solutions when the real parameter λ>0 is large enough.

A novel, wireless, passive substrate-integrated waveguide (SIW) temperature sensor based on a complementary split-ring resonator (CSRR) is presented for ultra-high-temperature applications. The temperature sensor model was established by using the software of HFSS (ANSYS, Canonsburg, PA, USA) to optimize the performance. This sensor can monitor temperature wirelessly using the microwave backscatter principle, which uses a robust high-temperature co-fired ceramic (HTCC) as the substrate for harsh environments. The results are experimentally verified by measuring the S (1,1) parameter of the interrogator antenna without contact. The resonant frequency of the sensor decreases with the increasing temperature using the dielectric perturbation method, which changes from 2.5808 to 2.35941 GHz as the temperature increases from 25 to 1200 °C. The sensitivity of the sensor is 126.74 kHz/°C in the range of 25–400 °C and 217.33 kHz/°C in the range of 400–1200 °C. The sensor described in this study has the advantages of simple structure, higher quality and sensitivity, and lower environmental interference, and has the potential for utilization in multi-site temperature testing or multi-parameter testing (temperature, pressure, gas) in high-temperature environments.

In this paper, a mixed sources dimension reduction Multiple Signal Classification (MUSIC) localization algorithm suitable for Micro-Electro-Mechanical System (MEMS) vector hydrophone linear arrays is proposed, which reduces the two-dimensional search to one-dimensional local search. Firstly, the Lagrangian function is constructed by quadratic optimization idea to obtain the estimates of azimuth angles. Secondly, the least square method is utilized for optimal match to obtain the direction-of-arrivals (DOAs) and ranges, and the range parameters are judged in Fresnel zone to obtain the azimuth information of all near-field sources. Finally, find the common DOAs and achieve high-resolution separation of far-field and near-field sources. Simulation and field experiments prove that the proposed algorithm only needs a small number of elements can solve the problem of port and starboard ambiguity, does not need to construct high-order cumulants or multi-dimensional search while the parameters are automatically matched with low computational complexity. This study provides an idea of the engineering application of vector hydrophone.

Abstract Background Neoadjuvant chemotherapy (NAC) is widely used in advanced breast cancer patients. However, there is little known about conversion frequency of estrogen receptor (ER) and/or progesterone receptor (PR) status for hormone receptor positive-breast cancer patients after NAC and their correlation with prognosis. Methods In this study, 231 breast cancer patients with residual disease after NAC were enrolled and divided into receptor stable group (having no conversion in both ER and PR status pre- and post-NAC) and any receptor conversion group (having any conversion in either ER or PR status). Univariate and multivariate survival analyses were used to compare survival differences between the two groups. Results Fifty-five patients (23.8%) had ER and/or PR conversion after NAC. Younger patients (≤ 50 years) were more likely to have receptor conversion (P = 0.014). For 213 patients (92.2%) who received adjuvant endocrinotherapy after surgery, the 5-year disease free survival (DFS) estimates for patients in the any receptor conversion group (55.2%) was worse than patients in the receptor stable group (73.7%, Log-rank test, P = 0.015). While the 5-year overall survival estimates for patients with or without receptor conversion were not statistically different (86.0 vs. 82.4%, Log-rank test, P = 0.587). In multivariate Cox proportional hazard analyses, patients with any receptor conversion had worse DFS (hazard ratio, 1.995; 95% confidence interval, 1.130–3.521, P = 0.031). Conclusions It is necessary to recommend patients to test biomarkers in residual disease and pay more attention to patients who have any receptor conversion. These patients may need more individual therapy after surgery.

This study aims to investigate the impact of the urban undersea tunnel longitudinal slope on the visual characteristics of drivers. 20 drivers were enrolled to conduct the real vehicle test of the urban undersea tunnel. First, the data of average fixation time and visual lobe were collected by an eye tracker. The differential significance was tested using the one-way repeated measures analysis of variance (ANOVA). Then, the difference between the up-and-down slope (direction) factor and the longitudinal slope (percent) factor on the two indexes were analyzed using the two-way repeated measures ANOVA. Second, by constructing a Lorentz model, the impact of the longitudinal slope on the average fixation time and the visual lobe were analyzed. Besides, a three-dimensional model of the longitudinal slope, average fixation time, and visual lobe was quantified. The results showed that the average fixation time and visual lobe under different longitudinal slopes markedly differed when driving on the uphill and downhill sections. The average fixation time and visual lobe under two factors were markedly different. Moreover, with an increase in the longitudinal slope, the average fixation time exhibited a trend of increasing first then decreasing; the visual lobe exhibited a trend of decreasing first and then increasing. The average fixation time reached the minimum and maximum value when the slope was 2.15% and 4.0%, whereas the visual lobe reached the maximum and minimum value when the slope was 2.88% and 4.0%. Overall, the longitudinal slope exerted a great impact on the visual load of the driver.

Oxidized HDL (ox-HDL), unlike native HDL that exerts antiatherogenic effects, plays a proatherogenic role. However, the underlying mechanisms are not completely understood. This study was designed to explore the inductive effect of ox-HDL on endoplasmic reticulum (ER) stress-CCAAT-enhancer-binding protein homologous protein (CHOP)-mediated macrophage apoptosis and its upstream mechanisms. Our results showed that ox-HDL could be ingested by macrophages, causing intracellular lipid accumulation. As with tunicamycin (an ER stress inducer), ox-HDL induced macrophage apoptosis with concomitant activation of ER stress pathway, including nuclear translocation of activating transcription factor 6, phosphorylation of protein kinase-like ER kinase and eukaryotic translation initiation factor 2α, and upregulation of glucose-regulated protein 78 and CHOP, which were inhibited by 4-phenylbutyric acid (PBA, an ER stress inhibitor) and CHOP gene silencing. Additionally, diphenyleneiodonium (DPI, an oxidative stress inhibitor), probucol (a reactive oxygen species scavenger), and toll-like receptor 4 (TLR4) silencing reduced ox-HDL-induced macrophage apoptosis, oxidative stress, and CHOP upregulation. Moreover, HDL isolated from patients with metabolic syndrome induced macrophage apoptosis, oxidative stress, and CHOP upregulation, which were blocked by PBA and DPI. These data indicate that ox-HDL may activate ER stress-CHOP-induced apoptotic pathway in macrophages via enhanced oxidative stress and that this pathway may be mediated by TLR4.

In this paper, we are concerned with the following fractional p-Kirchhoff system with sign-changing nonlinearities: M(∫R2nux-uyp/x-yn+psdxdy)-Δpsu=λa(x)uq-2u+α/(α+β)f(x)uα-2uvβ, in Ω, M(∫R2n|v(x)-v(y)|p/|x-y|n+psdxdy)-Δpsv=μb(x)vq-2v+(β/α+β)f(x)uαvβ-2v, in Ω, and u=v=0, in Rn∖Ω, where Ω is a smooth bounded domain in Rn, n>ps, s∈(0,1), λ, μ are two real parameters, 10, l>0, h≥1,a(x),b(x)∈L(α+β)/(α+β-q)(Ω) are sign changing and either a±=max⁡{±a,0}≢0 or b±=max⁡{±b,0}≢0, f∈L(Ω¯) with f∞=1, and f≥0. Using Nehari manifold method, we prove that the system has at least two solutions with respect to the pair of parameters (λ,μ).

BACKGROUND: Asymmetric zygotic division in higher plants results in the formation of an apical cell and a basal cell. These two embryonic cells possess distinct morphologies and cell developmental fates. It has been proposed that unevenly distributed cell fate determinants and/or distinct cell transcript profiles may be the underlying reason for their distinct fates. However, neither of these hypotheses has convincing support due to technical limitations. METHODOLOGY/PRINCIPAL FINDINGS: Using laser-controlled microdissection, we isolated apical and basal cells and constructed cell type-specific cDNA libraries. Transcript profile analysis revealed difference in transcript composition. PCR and qPCR analysis confirmed that transcripts of selected embryogenesis-related genes were cell-type preferentially distributed. Some of the transcripts that existed in zygotes were found distinctly existed in apical or basal cells. The cell type specific de novo transcription was also found after zygotic cell division. CONCLUSIONS/SIGNIFICANCE: Thus, we found that the transcript diversity occurs between apical and basal cells. Asymmetric zygotic division results in the uneven distribution of some embryogenesis related transcripts in the two-celled proembryos, suggesting that a differential distribution of some specific transcripts in the apical or basal cells may involve in guiding the two cell types to different developmental destinies.