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MOTIVATION: Complex diseases are often caused and characterized by misregulation of multiple biological pathways. Differential network analysis aims to detect significant rewiring of biological network structures under different conditions and has become an important tool for understanding the molecular etiology of disease progression and therapeutic response. With few exceptions, most existing differential network analysis tools perform differential tests on separately learned network structures that are computationally expensive and prone to collapse when grouped samples are limited or less consistent. RESULTS: We previously developed an accurate differential network analysis method-differential dependency networks (DDN), that enables joint learning of common and rewired network structures under different conditions. We now introduce the DDN3.0 tool that improves this framework with three new and highly efficient algorithms, namely, unbiased model estimation with a weighted error measure applicable to imbalance sample groups, multiple acceleration strategies to improve learning efficiency, and data-driven determination of proper hyperparameters. The comparative experimental results obtained from both realistic simulations and case studies show that DDN3.0 can help biologists more accurately identify, in a study-specific and often unknown conserved regulatory circuitry, a network of significantly rewired molecular players potentially responsible for phenotypic transitions. AVAILABILITY AND IMPLEMENTATION: The Python package of DDN3.0 is freely available at https://github.com/cbil-vt/DDN3. A user's guide and a vignette are provided at https://ddn-30.readthedocs.io/.
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Algoritmos , Programas Informáticos , Humanos , Redes Reguladoras de Genes , Biología Computacional/métodosRESUMEN
Combinatorial expression of postsynaptic proteins underlies synapse diversity within and between neuron types. Thus, characterization of neuron-type-specific postsynaptic proteomes is key to obtaining a deeper understanding of discrete synaptic properties and how selective dysfunction manifests in synaptopathies. To overcome the limitations associated with bulk measures of synaptic protein abundance, we developed a biotin proximity protein tagging probe to characterize neuron-type-specific postsynaptic proteomes in vivo. We found Shank3 protein isoforms are differentially expressed by direct and indirect pathway spiny projection neurons (dSPNs and iSPNs). Investigation of Shank3B-/- mice lacking exons 13-16 within the Shank3 gene, reveal distinct Shank3 protein isoform expression in iSPNs and dSPNs. In Shank3B-/- striatum, Shank3E and Shank3NT are expressed by dSPNs but are undetectable in iSPNs. Proteomic analysis indicates significant and selective alterations in the postsynaptic proteome of Shank3B-/- iSPNs. Correspondingly, the deletion of exons 13-16 diminishes dendritic spine density, reduces spine head diameter, and hampers corticostriatal synaptic transmission in iSPNs. Remarkably, reintroducing Shank3E in adult Shank3B-/- iSPNs significantly rectifies the observed dendritic spine morphological and corticostriatal synaptic transmission deficits. We report unexpected cell-type specific synaptic protein isoform expression which could play a key causal role in specifying synapse diversity and selective synapse dysfunction in synaptopathies.
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STUDY OBJECTIVE: To establish a prediction model to help doctors determine which patients with cesarean scar defect are more suitable for transvaginal repair. DESIGN: Retrospective analysis. SETTING: Xinhua Hospital and Shanghai First Maternity & Infant Hospital between June 2014 and May 2021. PATIENTS: 1015 women who underwent transvaginal repair of cesarean scar defect (CSD). INTERVENTIONS: All enrolled patients underwent CSD repair performed by the same gynecologist and his team. And followed up a clinic visit at 6 months to record their menstruation and measure multiple parameters of the CSD by Magnetic Resonance Imaging. MAIN OUTCOMES AND MEASURES: CSD patients are categorized as optimal healing group when the menstruation duration is no more than 7 days, meanwhile the thickness of residual myometrium is no less than 5.39 mm after vaginal repair. The final nomogram is constructed to predict surgical outcomes based on preoperative variables. RESULTS: The key factors that determine optimal healing are the timing of cesarean section (elective or emergency), menstrual cycle, CSD length, width, depth, and the thickness of the lower uterine segment. With the prediction model, scores are given to each parameter according to the statistics. Total scores range from 0 to 25 points, with a cutoff point of 16.5. When a score is greater than 16.5, the transvaginal repair can achieve optimal healing. Uterine position (anteflexion or retroflexion) and preoperative thickness of residual myometrium are the key factors affecting postoperative thickness of residual myometrium. The width of the CSD and the thickness of the lower uterine segment are the key factors affecting abnormal uterine bleeding symptoms (p < 0.01). CONCLUSIONS: For the first time, we established a prediction model system that may predict the repair effect of CSD and can potentially be useful in future clinical trials to determine which patients are more suitable for surgery or other treatment options.
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Cesárea , Cicatriz , Humanos , Femenino , Embarazo , Cicatriz/etiología , Cicatriz/cirugía , Estudios Retrospectivos , Cesárea/efectos adversos , Selección de Paciente , ChinaRESUMEN
STUDY OBJECTIVE: To prospectively investigate whether the application of vaginal repair (VR) of cesarean section scar defect (CSD) combined with a gonadotropin-releasing hormone agonist (GnRHa) achieve better clinical outcomes than VR alone. DESIGN: A randomized clinical trial. SETTING: University hospital. PATIENTS: A total of 124 women with CSD were undergoing expectant management from December 2016 to September 2021. 61 were randomised to VR+ GnRHa and 63 to VR alone. INTERVENTION: Vaginal repair combined with GnRHa and vaginal repair alone. MEASURES AND MAIN RESULTS: The primary outcome was the duration of menstruation and thickness of the remaining muscular layer (TRM) at 6 months after surgery. Secondary outcomes included the length, width and depth of the CSD; operation time; estimated blood loss; hospitalization time; and operative complications. Women were treated with either VR (nâ¯=â¯63) or VRâ¯+â¯GnRHa (nâ¯=â¯61). Menstruation and TRM in patients pre. vs. post comparisons either with VR or VRâ¯+â¯GnRHa are significant improved (P < .05). Significant differences in menstruation duration and TRM occurred in patients treated with VRâ¯+â¯GnRHa compared with those treated with VR (P < .05). Moreover, the rate of CSD after surgery in the VR group was significantly higher than that in the VRâ¯+â¯GnRHa group (Pâ¯=â¯.033), and CSD patients in the VRâ¯+â¯GnRHa group achieved better therapeutic effects than those in the VR group (Pâ¯=â¯.017). Patients who received VRâ¯+â¯GnRHa had a shorter menstruation duration and a greater increment of TRM postoperatively than did patients treated with VR alone (Pâ¯=â¯.021; Pâ¯=â¯.002, respectively). CONCLUSION: VRâ¯+â¯GnRHa therapy has a greater potential to improve scar healing and reduce the number of menstruation days than VR alone for symptomatic women with CSD. PRéCIS: Vaginal Repair Combined with GnRHa Creates Better Therapeutic Effects of CSD. TRIAL REGISTRATION: Date of registration: October 13, 2016, Date of initial participant enrollment: December 20, 2016, Clinical trial identification number: NCT02932761, URL of the registration site: ClinicalTrials.gov, Figshare DOI: 10.6084/m9.figshare.24117114 LINK TO THE CLINICAL TRIAL REGISTRATION: https://clinicaltrials.gov/study/NCT02932761.
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This research investigates the impact of climate challenges on financial markets by introducing an innovative approach to measure climate risk, specifically the aggregate climate change concern (ACCC) index. The study aims to assess and quantify the potential influence of climate change and risk-related factors on the performance and dynamics of financial markets. In this paper, concern is defined as the attention paid to the risk of climate change and the associated negative consequences. The findings demonstrate that the aggregate index exhibits robust predictability of market risk premiums, both within the sample and out-of-sample. By comparison, the index contains additional information beyond 14 economic predictors and 12 risk/uncertainty indexes in forecasting stock market return. In addition, the index proves valuable for mean-variance investors in asset allocation, leading to significant economic gains. The study identifies the index's ability to capture the reversal of temporary price crashes caused by overreactions to climate change risk. Furthermore, it exhibits stronger return forecasting capability for green stocks, non-state-owned enterprise (non-SOE) stocks, and stocks in regions with low air pollution. Particularly during periods of low air pollution and relaxed regulation, the index displays an enhanced ability to forecast returns. The study's findings provide valuable insights for policymakers and financial institutions as they address 21st-century environmental challenges. Moreover, these findings can inform the design of adaptive measures and interventions aimed at mitigating ecological risks and promoting sustainable economic growth.
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BACKGROUND: Bibliometric analysis of liver cancer research, particularly in immunotherapy, reveals crucial insights. The US leads in liver cancer mortality but ranks fifth globally. OBJECTIVE: Scopus database analysis identified 2,349 papers, with the top 100 ranging from 127 to 4,959 citations. Notably, "Microenvironmental Regulation of Tumours Progression and Metastasis" in the Journal of Nature Medicine garnered the highest citations. METHODS: Journals like the Journal of Hepatology, Hepatology, and Nature Reports Clinical Oncology contributed significantly. Understanding molecular mechanisms and prognostic indicators is paramount for advancing combination therapies. RESULTS: For better patient outcomes, research trends in liver cancer immunotherapy point to improved treatment protocols, knowledge of the tumor microenvironment, combining therapies, predicting disease course, international cooperation, sophisticated surgical techniques, early detection, oncolytic virotherapy, and patient-centered care. CONCLUSIONS: This research underscores immunotherapy's pivotal role and encourages further exploration, offering valuable insights into liver cancer treatment trends.
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BACKGROUND: Fibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated. METHODS: In this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan-Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored. RESULTS: The study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan-Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells. CONCLUSION: Despite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.
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Dominio de Fibronectina del Tipo III , Neoplasias Pancreáticas , Humanos , Células Dendríticas , Nomogramas , Neoplasias Pancreáticas/genética , PronósticoRESUMEN
BACKGROUND: The rarity yet high malignancy of gallbladder adenocarcinoma (GBA) endows it with a distinctive nature. Radical resection remains the foremost therapeutic approach for GBA, while the impact of early recurrence and metastasis on patient prognosis necessitates the utilization of adjuvant chemotherapy (AC). Despite numerous previous studies on this topic, a consensus regarding the authentic efficacy of AC has yet to be reached. METHODS: We conducted an updated retrospective cohort analysis utilizing data from the Surveillance, Epidemiology, and End Results (SEER) database spanning from 2010 to 2020 to explore the association between AC and survival outcomes in patients with resected GBA. RESULTS: Our study included 2782 patients from the SEER database, with further evaluation of 843 patients in each cohort following meticulous execution of a 1:1 propensity score matching. Remarkably, the AC cohort exhibited a significant survival advantage when juxtaposed against the non-AC cohort. Multivariable Cox regression analysis identified age at diagnosis, year at diagnosis, grade, AJCC T stage, AJCC N stage as well as AC as independent prognostic factors. Furthermore, our findings unveiled that poor/undifferentiated tumor histology, pathological T2 or higher category and pathological N1 category were significantly associated with improved survival when treated with AC while simultaneously observing improved survival across all age categories. CONCLUSION: These results provide additional evidence supporting the survival benefits of AC and offer guidance for personalized therapy in patients with resected GBA.
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Adenocarcinoma , Neoplasias de la Vesícula Biliar , Humanos , Estudios Retrospectivos , Quimioterapia Adyuvante/métodos , Estudios de Cohortes , Adenocarcinoma/tratamiento farmacológico , Adenocarcinoma/cirugía , Neoplasias de la Vesícula Biliar/tratamiento farmacológico , Neoplasias de la Vesícula Biliar/cirugía , Estadificación de NeoplasiasRESUMEN
Dendritic cells (DC) are professional antigen-presenting cells which link innate to adaptive immunity. DC play a central role in regulating antitumor T-cell responses in both tumor-draining lymph nodes (TDLN) and the tumor microenvironment (TME). They modulate effector T-cell responses via immune checkpoint proteins (ICPs) that can be either stimulatory or inhibitory. Functions of DC are often impaired by the suppressive TME leading to tumor immune escape. Therefore, better understanding of the mechanisms of action of ICPs expressed by (tumor-infiltrating) DC will lead to potential new treatment strategies. Genetic manipulation and high-dimensional analyses have provided insight in the interactions between DC and T-cells in TDLN and the TME upon ICP targeting. In this review, we discuss (tumor-infiltrating) DC lineage cells and tumor tissue specific "mature" DC states and their gene signatures in relation to anti-tumor immunity. We also review a number of ICPs expressed by DC regarding their functions in phagocytosis, DC activation, or inhibition and outline position in, or promise for clinical trials in cancer immunotherapy. Collectively, we highlight the critical role of DC and their exact status in the TME for the induction and propagation of T-cell immunity to cancer.
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Células Dendríticas , Neoplasias , Humanos , Neoplasias/patología , Linfocitos T , Inmunidad Adaptativa , Inmunoterapia/métodos , Microambiente TumoralRESUMEN
Photonic integrated circuits have been extensively explored for optical processing with the aim of breaking the speed and energy efficiency bottlenecks of digital electronics. However, the input/output (IO) bottleneck remains one of the key barriers. Here we report a photonic iterative processor (PIP) for matrix-inversion-intensive applications. The direct reuse of inputted data in the optical domain unlocks the potential to break the IO bottleneck. We demonstrate notable IO advantages with a lossless PIP for real-valued matrix inversion and integral-differential equation solving, as well as a coherent PIP with optical loops integrated on-chip, enabling complex-valued computation and a net inversion time of 1.2 ns. Furthermore, we estimate at least an order of magnitude enhancement in IO efficiency of a PIP over photonic single-pass processors and the state-of-the-art electronic processors for reservoir training tasks and multiple-input and multiple-output (MIMO) precoding tasks, indicating the huge potential of PIP technology in practical applications.
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Henckelia longisepala (H. W. Li) D. J. Middleton & Mich. Möller is a rare and endangered plant species found only in Southeastern Yunnan, China, and Northern Vietnam. It is listed as a threatened species in China and recognized as a plant species with extremely small populations (PSESP), while also having high ornamental value and utilization potential. This study used ddRAD-seq technology to quantify genetic diversity and structure for 32 samples from three extant populations of H. longisepala. The H. longisepala populations were found to have low levels of genetic diversity (Ho = 0.1216, He = 0.1302, Pi = 0.1731, FIS = 0.1456), with greater genetic differentiation observed among populations (FST = 0.3225). As indicated by genetic structure and phylogenetic analyses, samples clustered into three distinct genetic groups that corresponded to geographically separate populations. MaxEnt modeling was used to identify suitable areas for H. longisepala across three time periods and two climate scenarios (SSP1-2.6, SSP5-8.5). High-suitability areas were identified in Southeastern Yunnan Province, Northern Vietnam, and Eastern Laos. Future H. longisepala distribution was predicted to remain centered in these areas, but with a decrease in the total amount of suitable habitat. The present study provides key data on H. longisepala genetic diversity, as well as a theoretical basis for the conservation, development, and utilization of its germplasm resources.
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Extracellular vesicles (EVs) facilitate intercellular communication by transferring cargo between cells in a variety of tissues. However, how EVs achieve cell-type-specific intercellular communication is still largely unknown. We found that Notch1 and Notch2 proteins are expressed on the surface of neuronal EVs that have been generated in response to neuronal excitatory synaptic activity. Notch ligands bind these EVs on the neuronal plasma membrane, trigger their internalization, activate the Notch signaling pathway, and drive the expression of Notch target genes. The generation of these neuronal EVs requires the endosomal sorting complex required for transport-associated protein Alix. Adult Alix conditional knockout mice have reduced hippocampal Notch signaling activation and glutamatergic synaptic protein expression. Thus, EVs facilitate neuron-to-neuron communication via the Notch receptor-ligand system in the brain.
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Vesículas Extracelulares , Neuronas , Animales , Ratones , Ligandos , Transporte de Proteínas , Transducción de Señal , Ratones NoqueadosRESUMEN
In neurons, it is commonly assumed that mitochondrial replication only occurs in the cell body, after which the mitochondria must travel to the neuron's periphery. However, while mitochondrial DNA replication has been observed to occur away from the cell body, the specific mechanisms involved remain elusive. Using EdU-labelling in mouse primary neurons, we developed a tool to determine the mitochondrial replication rate. Taking of advantage of microfluidic devices, we confirmed that mitochondrial replication also occurs locally in the periphery of neurons. To achieve this, mitochondria require de novo nuclear-encoded, but not mitochondrial-encoded protein translation. Following a proteomic screen comparing synaptic with non-synaptic mitochondria, we identified two elongation factors - eEF1A1 and TUFM - that were upregulated in synaptic mitochondria. We found that mitochondrial replication is impaired upon the downregulation of eEF1A1, and this is particularly relevant in the periphery of neurons.
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Doxorubicin (Dox), a chemotherapeutic agent frequently used to treat cancer, elicits cardiotoxicity, a condition referred to as Dox-induced cardiotoxicity (DIC), and ferroptosis plays a contributory role in its pathophysiology. Fucoidan, a polysaccharide with various biological activities and safety profile, has potential therapeutic and pharmaceutical applications. This study aimed to investigate the protective effects and underlying mechanisms of fucoidan in DIC. Echocardiography, biomarkers of cardiomyocyte injury, serum creatine kinase, creatine kinase isoenzyme and lactate dehydrogenase, as well as histological staining results, revealed that fucoidan significantly reduced myocardial damage and improved cardiac function in DIC mice. Transmission electron microscopy; levels of lipid reactive oxygen species, glutathione, and malondialdehyde; ferroptosis-related markers; and regulatory factors such as glutathione peroxidase 4 (GPX4), transferrin receptor protein-1, ferritin heavy chain-1, heme oxygenase-1 in the heart tissue were measured to explore the effect of fucoidan on Dox-induced ferroptosis. These results suggested that fucoidan could inhibit cardiomyocyte ferroptosis caused by Dox. In vitro experiments revealed that silencing nuclear factor-erythroid 2-related factor 2 (Nrf2) in cardiomyocytes reduced the inhibitory effect of fucoidan on ferroptosis. Hence, fucoidan has the potential to ameliorate DIC by inhibiting ferroptosis via the Nrf2/GPX4 pathway.
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Cardiotoxicidad , Doxorrubicina , Ferroptosis , Miocitos Cardíacos , Factor 2 Relacionado con NF-E2 , Fosfolípido Hidroperóxido Glutatión Peroxidasa , Polisacáridos , Transducción de Señal , Animales , Polisacáridos/farmacología , Polisacáridos/química , Ferroptosis/efectos de los fármacos , Factor 2 Relacionado con NF-E2/metabolismo , Doxorrubicina/efectos adversos , Doxorrubicina/toxicidad , Ratones , Cardiotoxicidad/tratamiento farmacológico , Fosfolípido Hidroperóxido Glutatión Peroxidasa/metabolismo , Transducción de Señal/efectos de los fármacos , Miocitos Cardíacos/efectos de los fármacos , Miocitos Cardíacos/metabolismo , MasculinoRESUMEN
Bioinformatics software tools are essential to identify informative molecular features that define different phenotypic sample groups. Among the most fundamental and interrelated tasks are missing value imputation, signature gene detection, and differential pattern visualization. However, many commonly used analytics tools can be problematic when handling biologically diverse samples if either informative missingness possess high missing rates with mixed missing mechanisms, or multiple sample groups are compared and visualized in parallel. We developed the ABDS tool suite specifically for analyzing biologically diverse samples. Collectively, a mechanism-integrated group-wise pre-imputation scheme is proposed to retain informative missingness associated with signature genes, a cosine-based one-sample test is extended to detect group-silenced signature genes, and a unified heatmap is designed to display multiple sample groups. We describe the methodological principles and demonstrate the effectiveness of three analytics tools under targeted scenarios, supported by comparative evaluations and biomedical showcases. As an open-source R package, ABDS tool suite complements rather than replaces existing tools and will allow biologists to more accurately detect interpretable molecular signals among phenotypically diverse sample groups.
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The recently discovered HAPSTR1 protein broadly oversees cellular stress responses. This function requires HUWE1, a ubiquitin ligase that paradoxically marks HAPSTR1 for degradation, but much about this pathway remains unclear. Here, leveraging multiplexed proteomics, we find that HAPSTR1 enables nuclear localization of HUWE1 with implications for nuclear protein quality control. We show that HAPSTR1 is tightly regulated and identify ubiquitin ligase TRIP12 and deubiquitinase USP7 as upstream regulators titrating HAPSTR1 stability. Finally, we generate conditional Hapstr1 knockout mice, finding that Hapstr1-null mice are perinatal lethal, adult mice depleted of Hapstr1 have reduced fitness, and primary cells explanted from Hapstr1-null animals falter in culture coincident with HUWE1 mislocalization and broadly remodeled signaling. Notably, although HAPSTR1 potently suppresses p53, we find that Hapstr1 is essential for life even in mice lacking p53. Altogether, we identify novel components and functional insights into the conserved HAPSTR1-HUWE1 pathway and demonstrate its requirement for mammalian life.
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Proteína p53 Supresora de Tumor , Ubiquitina-Proteína Ligasas , Animales , Ratones , Mamíferos/metabolismo , Proteínas Nucleares/metabolismo , Transducción de Señal/genética , Proteína p53 Supresora de Tumor/genética , Proteína p53 Supresora de Tumor/metabolismo , Ubiquitina/metabolismo , Ubiquitina-Proteína Ligasas/genética , Ubiquitina-Proteína Ligasas/metabolismo , Ubiquitinación/genética , Proteínas Supresoras de Tumor/genética , Proteínas Supresoras de Tumor/metabolismo , Péptidos y Proteínas de Señalización Intracelular/genética , Péptidos y Proteínas de Señalización Intracelular/metabolismoRESUMEN
Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, and imaging modalities. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.
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AIMS: The automation of quantitative evaluation for breast immunohistochemistry (IHC) plays a crucial role in reducing the workload of pathologists and enhancing the objectivity of diagnoses. However, current methods face challenges in achieving fully automated immunohistochemistry quantification due to the complexity of segmenting the tumor area into distinct ductal carcinoma in situ (DCIS) and invasive carcinoma (IC) regions. Moreover, the quantitative analysis of immunohistochemistry requires a specific focus on invasive carcinoma regions. METHODS AND RESULTS: In this study, we propose an innovative approach to automatically identify invasive carcinoma regions in breast cancer immunohistochemistry whole-slide images (WSIs). Our method leverages a neural network that combines multi-scale morphological features with boundary features, enabling precise segmentation of invasive carcinoma regions without the need for additional H&E and P63 staining slides. In addition, we introduced an advanced semi-supervised learning algorithm, allowing efficient training of the model using unlabeled data. To evaluate the effectiveness of our approach, we constructed a dataset consisting of 618 IHC-stained WSIs from 170 cases, including four types of staining (ER, PR, HER2, and Ki-67). Notably, the model demonstrated an impressive intersection over union (IoU) score exceeding 80% on the test set. Furthermore, to ascertain the practical utility of our model in IHC quantitative evaluation, we constructed a fully automated Ki-67 scoring system based on the model's predictions. Comparative experiments convincingly demonstrated that our system exhibited high consistency with the scores given by experienced pathologists. CONCLUSIONS: Our developed model excels in accurately distinguishing between DCIS and invasive carcinoma regions in breast cancer immunohistochemistry WSIs. This method paves the way for a clinically available, fully automated immunohistochemistry quantitative scoring system.