A rapid aureochrome opto-switch enables diatom acclimation to dynamic light.

Diatoms often outnumber other eukaryotic algae in the oceans, especially in coastal environments characterized by frequent fluctuations in light intensity. The identities and operational mechanisms of regulatory factors governing diatom acclimation to high light stress remain largely elusive. Here, we identified the AUREO1c protein from the coastal diatom Phaeodactylum tricornutum as a crucial regulator of non-photochemical quenching (NPQ), a photoprotective mechanism that dissipates excess energy as heat. AUREO1c detects light stress using a light-oxygen-voltage (LOV) domain and directly activates the expression of target genes, including LI818 genes that encode NPQ effector proteins, via its bZIP DNA-binding domain. In comparison to a kinase-mediated pathway reported in the freshwater green alga Chlamydomonas reinhardtii, the AUREO1c pathway exhibits a faster response and enables accumulation of LI818 transcript and protein levels to comparable degrees between continuous high-light and fluctuating-light treatments. We propose that the AUREO1c-LI818 pathway contributes to the resilience of diatoms under dynamic light conditions.

Dissecting the association between gut microbiota, body mass index and specific depressive symptoms: a mediation Mendelian randomisation study.

Background: Observational studies highlight the association between gut microbiota (GM) composition and depression; however, evidence for the causal relationship between GM and specific depressive symptoms remains lacking. Aims: We aimed to evaluate the causal relationship between GM and specific depressive symptoms as well as the mediating role of body mass index (BMI). Methods: We performed a two-sample Mendelian randomisation (MR) analysis using genetic variants associated with GM and specific depressive symptoms from genome-wide association studies. The mediating role of BMI was subsequently explored using mediation analysis via two-step MR. Results: MR evidence suggested the Bifidobacterium genus (ß=-0.03; 95% CI -0.05 to -0.02; p<0.001 and ß=-0.03; 95% CI -0.05 to -0.02; p<0.001) and Actinobacteria phylum (ß=-0.04; 95% CI -0.06 to -0.02; p<0.001 and ß=-0.03; 95% CI -0.05 to -0.03; p=0.001) had protective effects on both anhedonia and depressed mood. The Actinobacteria phylum also had protective effects on appetite changes (ß=-0.04; 95% CI -0.06 to -0.01; p=0.005), while the Family XI had an antiprotective effect (ß=0.03; 95% CI 0.01 to 0.04; p<0.001). The Bifidobacteriaceae family (ß=-0.01; 95% CI -0.02 to -0.01; p=0.001) and Actinobacteria phylum (ß=-0.02; 95% CI -0.03 to -0.01; p=0.001) showed protective effects against suicidality. The two-step MR analysis revealed that BMI also acted as a mediating moderator between the Actinobacteria phylum and appetite changes (mediated proportion, 34.42%) and that BMI partially mediated the effect of the Bifidobacterium genus (14.14% and 8.05%) and Actinobacteria phylum (13.10% and 8.31%) on both anhedonia and depressed mood. Conclusions: These findings suggest a potential therapeutic effect of Actinobacteria and Bifidobacterium on both depression and obesity. Further studies are required to translate these findings into clinical practice.

An insulin-like signalling pathway model for Fasciola gigantica.

BACKGROUND: The insulin/insulin-like signalling (IIS) pathway is common in mammals and invertebrates, and the IIS pathway is unknown in Fasciola gigantica. In the present study, the IIS pathway was reconstructed in F. gigantica. We defined the components involved in the IIS pathway and investigated the transcription profiles of these genes for all developmental stages of F. gigantica. In addition, the presence of these components in excretory and secretory products (ESPs) was predicted via signal peptide annotation. RESULTS: The core components of the IIS pathway were detected in F. gigantica. Among these proteins, one ligand (FgILP) and one insulin-like molecule binding protein (FgIGFBP) were analysed. Interestingly, three receptors (FgIR-1/FgIR-2/FgIR-3) were detected, and a novel receptor, FgIR-3, was screened, suggesting novel functions. Fg14-3-3ζ, Fgirs, and Fgpp2a exhibited increased transcription in 42-day-old juveniles and 70-day-old juveniles, while Fgilp, Fgigfb, Fgsgk-1, Fgakt-1, Fgir-3, Fgpten, and Fgaap-1 exhibited increased transcription in metacercariae. FgILP, FgIGFBP, FgIR-2, FgIR-3, and two transcription factors (FgHSF-1 and FgSKN-1) were predicted to be present in FgESPs, indicating their exogenous roles. CONCLUSIONS: This study helps to elucidate the signal transduction pathway of IIS in F. gigantica, which will aid in understanding the interaction between flukes and hosts, as well as in understanding fluke developmental regulation, and will also lay a foundation for further characterisation of the IIS pathways of trematodes.

A thermosensitive luminescence halloysite-based nanocomposite enabling encryptable thermal printing.

In situ formation of carbon dots on halloysite nanotubes is demonstrated by treating polyacrylamide-grafted halloysite nanotubes with polycarboxylic acid without the recourse to extremely high temperatures or solvents. Thermosensitive luminescence and phosphorescence properties are carefully investigated. The polyacrylamide-grafted halloysite nanotubes are further processed as composite films for encryptable thermal printing.

Does wearing a mask promote consumer uniqueness seeking?

As a motivational factor, uniqueness drives individuals to seek and choose unique goods or experiences. The act of wearing masks obscures individuals' facial features and influences their desire for uniqueness. This study aims to explore how wearing masks promotes individual uniqueness- seeking behavior. Three experiments were performed using various product categories (Starbucks coffee cups, sweatshirts, suitcases, and baseball caps) and sample types (college student and adult samples). Experiment results show that wearing masks obscures individuals' facial features and weakens their self- perceived uniqueness, thereby increasing their willingness to actively purchase unique products. This study is the first to examine the effect of wearing masks on individuals' choice of unique products. Practically, the results suggest that customized products can compensate for the lack of self-perceived uniqueness brought about by facial occlusion, thus providing valuable guidance for companies and retailers that offer customized services in formulating and designing marketing strategies.

Deep-learning-based sampling position selection on color Doppler sonography images during renal artery ultrasound scanning.

Accurate selection of sampling positions is critical in renal artery ultrasound examinations, and the potential of utilizing deep learning (DL) for assisting in this selection has not been previously evaluated. This study aimed to evaluate the effectiveness of DL object detection technology applied to color Doppler sonography (CDS) images in assisting sampling position selection. A total of 2004 patients who underwent renal artery ultrasound examinations were included in the study. CDS images from these patients were categorized into four groups based on the scanning position: abdominal aorta (AO), normal renal artery (NRA), renal artery stenosis (RAS), and intrarenal interlobular artery (IRA). Seven object detection models, including three two-stage models (Faster R-CNN, Cascade R-CNN, and Double Head R-CNN) and four one-stage models (RetinaNet, YOLOv3, FoveaBox, and Deformable DETR), were trained to predict the sampling position, and their predictive accuracies were compared. The Double Head R-CNN model exhibited significantly higher average accuracies on both parameter optimization and validation datasets (89.3 ± 0.6% and 88.5 ± 0.3%, respectively) compared to other methods. On clinical validation data, the predictive accuracies of the Double Head R-CNN model for all four types of images were significantly higher than those of the other methods. The DL object detection model shows promise in assisting inexperienced physicians in improving the accuracy of sampling position selection during renal artery ultrasound examinations.

Federated-learning-based prognosis assessment model for acute pulmonary thromboembolism.

BACKGROUND: Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing low prognosis risk patients with PTE accurately is significant for clinical treatment. This study evaluated the value of federated learning (FL) technology in PTE prognosis risk assessment while ensuring the security of clinical data. METHODS: A retrospective dataset consisted of PTE patients from 12 hospitals were collected, and 19 physical indicators of patients were included to train the FL-based prognosis assessment model to predict the 30-day death event. Firstly, multiple machine learning methods based on FL were compared to choose the superior model. And then performance of models trained on the independent (IID) and non-independent identical distributed(Non-IID) datasets was calculated and they were tested further on Real-world data. Besides, the optimal model was compared with pulmonary embolism severity index (PESI), simplified PESI (sPESI), Peking Union Medical College Hospital (PUMCH). RESULTS: The area under the receiver operating characteristic curve (AUC) of logistic regression(0.842) outperformed convolutional neural network (0.819) and multi layer perceptron (0.784). Under IID, AUC of model trained using FL(Fed) on the training, validation and test sets was 0.852 ± 0.002, 0.867 ± 0.012 and 0.829 ± 0.004. Under Real-world, AUC of Fed was 0.855 ± 0.005, 0.882 ± 0.003 and 0.835 ± 0.005. Under IID and Real-world, AUC of Fed surpassed centralization model(NonFed) (0.847 ± 0.001, 0.841 ± 0.001 and 0.811 ± 0.001). Under Non-IID, although AUC of Fed (0.846 ± 0.047) outperformed NonFed (0.841 ± 0.001) on validation set, it (0.821 ± 0.016 and 0.799 ± 0.031) slightly lagged behind NonFed (0.847 ± 0.001 and 0.811 ± 0.001) on the training and test sets. In practice, AUC of Fed (0.853, 0.884 and 0.842) outshone PESI (0.812, 0.789 and 0.791), sPESI (0.817, 0.770 and 0.786) and PUMCH(0.848, 0.814 and 0.832) on the training, validation and test sets. Additionally, Fed (0.842) exhibited higher AUC values across test sets compared to those trained directly on the clients (0.758, 0.801, 0.783, 0.741, 0.788). CONCLUSIONS: In this study, the FL based machine learning model demonstrated commendable efficacy on PTE prognostic risk prediction, rendering it well-suited for deployment in hospitals.

LncRNA TUG1 and its Molecular Mechanisms in Human Cancer.

As lncRNAs have increasingly been investigated, they are no longer simply defined as RNAs with no transcription capability. Studies have identified significant associations between the abnormal expression of lncRNAs and human diseases, particularly the mechanisms by which lncRNAs play a part in cancers, which are of considerable attention to researchers. As a result of the complex spatial structure, the mechanisms of interaction of lncRNAs in cancer cells are also complicated and diversified. Among a series of lncRNAs, TUG1, which is now considered to be a very high-value lncRNA, has recently been identified to express abnormally in some malignancies, leading to different alterations in cancer cells proliferation, migration, invasion, apoptosis, and drug resistance, and hence promoting or inhibiting cancer progression. Current studies have implicitly indicated that TUG1 can be used as a therapeutic target for human cancers. However, the biological functions of TUG1 have been studied for a short period of time, and the complete molecular mechanism still needs to be clarified. Accordingly, this review focuses on the principal molecular mechanisms of TUG1 in human cancers and the specific mechanisms of action in different cancer development processes based on existing studies.

PIPET: predicting relevant subpopulations in single-cell data using phenotypic information from bulk data.

Single-cell RNA sequencing has revealed cellular heterogeneity in complex tissues, notably benefiting research on diseases such as cancer. However, the integration of single-cell data from small samples with extensive clinical features in bulk data remains underexplored. In this study, we introduce PIPET, an algorithmic method for predicting relevant subpopulations in single-cell data based on multivariate phenotypic information from bulk data. PIPET generates feature vectors for each phenotype from differentially expressed genes in bulk data and then identifies relevant cellular subpopulations by assessing the similarity between single-cell data and these vectors. Subsequently, phenotype-related cell states can be analyzed based on these subpopulations. In simulated datasets, PIPET showed robust performance in predicting multiclassification cellular subpopulations. Application of PIPET to lung adenocarcinoma single-cell RNA sequencing data revealed cellular subpopulations with poor survival and associations with TP53 mutations. Similarly, in breast cancer single-cell data, PIPET identified cellular subpopulations associated with the PAM50 clinical subtypes and triple-negative breast cancer subtypes. Overall, PIPET effectively identified relevant cellular subpopulations in single-cell data, guided by phenotypic information from bulk data. This approach comprehensively delineates the molecular characteristics of each cellular subpopulation, offering insights into disease-related subpopulations and guiding personalized treatment strategies.

The Relationship between Live Sports Learning and Exercise Behavior in College Students: A Serial Mediation Model.

Physical exercise is crucial to the development of students' physical and mental health. This study explored the relationship between live sports learning and college students' exercise behaviors, and the mediating roles of exercise motivation and exercise commitment, aiming to provide theoretical bases for the future that explain the mechanism of live sports learning in exercise behaviors, as well as practical guidance for the promotion of positive physical exercise behaviors in college students. In total, 1189 college students from China volunteered to complete questionnaires. The results showed that live sports learning positively predicted college students' exercise behavior and that live sports learning was able to affect exercise behavior through the mediating roles of exercise motivation and exercise commitment, with specific mediating paths including the two independent mediating paths and a serial mediating path of exercise motivation and exercise commitment. This study confirmed, for the first time, on live sports learning in the process of promoting exercise behavior. It is suggested that educators instruct college students to regulate their participation in live sports learning and to cultivate healthy exercise motivation and exercise commitment, which is an effective way to facilitate college students' practice of physical activity.

Genetically Encoded Sensors for the In Vivo Detection of Neurochemical Dynamics.

The ability to measure dynamic changes in neurochemicals with high spatiotemporal resolution is essential for understanding the diverse range of functions mediated by the brain. We review recent advances in genetically encoded sensors for detecting neurochemicals and discuss their in vivo applications. For example, notable progress has been made with respect to sensors for second messengers such as cyclic adenosine monophosphate, enabling in vivo real-time monitoring of these messengers at single-cell and even subcellular resolution. Moreover, the emergence of highly sensitive sensors for neurotransmitters and neuromodulators has greatly accelerated the study of these signaling molecules in a wide variety of behavioral models using an array of powerful imaging techniques. Finally, we discuss the future direction of neurochemical sensors, including their ability to measure neurochemical concentrations and the potential for multiplex imaging.

The histone acetyltransferase KAT6B is required for hematopoietic stem cell development and function.

The histone lysine acetyltransferase KAT6B (MYST4, MORF, QKF) is the target of recurrent chromosomal translocations causing hematological malignancies with poor prognosis. Using Kat6b germline deletion and overexpression in mice, we determined the role of KAT6B in the hematopoietic system. We found that KAT6B sustained the fetal hematopoietic stem cell pool but did not affect viability or differentiation. KAT6B was essential for normal levels of histone H3 lysine 9 (H3K9) acetylation but not for a previously proposed target, H3K23. Compound heterozygosity of Kat6b and the closely related gene, Kat6a, abolished hematopoietic reconstitution after transplantation. KAT6B and KAT6A cooperatively promoted transcription of genes regulating hematopoiesis, including the Hoxa cluster, Pbx1, Meis1, Gata family, Erg, and Flt3. In conclusion, we identified the hematopoietic processes requiring Kat6b and showed that KAT6B and KAT6A synergistically promoted HSC development, function, and transcription. Our findings are pertinent to current clinical trials testing KAT6A/B inhibitors as cancer therapeutics.

Triterpenoid ursolic acid regulates the environmental carcinogen benzo[a]pyrene-driven epigenetic and metabolic alterations in SKH-1 hairless mice for skin cancer interception.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental carcinogens accountable to developing skin cancers. Recently, we reported that exposure to benzo[a]pyrene (B[a]P), a common PAH, causes epigenetic and metabolic alterations in the initiation, promotion and progression of non-melanoma skin cancer (NMSC). As a follow-up investigation, this study examines how dietary triterpenoid ursolic acid (UA) regulates B[a]P-driven epigenetic and metabolic pathways in SKH-1 hairless mice. Our results show UA intercepts against B[a]P-induced tumorigenesis at different stages of NMSC. Epigenomic cytosines followed by guanine residues (CpG) methyl-seq data showed UA diminished B[a]P-mediated differentially methylated regions (DMRs) profiles. Transcriptomic RNA-seq revealed UA revoked B[a]P-induced differentially expressed genes (DEGs) of skin cancer-related genes, such as leucine-rich repeat LGI family member 2 (Lgi2) and kallikrein-related peptidase 13 (Klk13), indicating UA plays a vital role in B[a]P-mediated gene regulation and its potential consequences in NMSC interception. Association analysis of DEGs and DMRs found that the mRNA expression of KLK13 gene was correlated with the promoter CpG methylation status in the early-stage comparison group, indicating UA could regulate the KLK13 by modulating its promoter methylation at an early stage of NMSC. The metabolomic study showed UA alters B[a]P-regulated cancer-associated metabolisms like thiamin metabolism, ascorbate and aldarate metabolism during the initiation phase; pyruvate, citrate and thiamin metabolism during the promotion phase; and beta-alanine and pathothenate coenzyme A (CoA) biosynthesis during the late progression phase. Taken together, UA reverses B[a]P-driven epigenetic, transcriptomic and metabolic reprogramming, potentially contributing to the overall cancer interception against B[a]P-mediated NMSC.

Critical Conditions Regulating the Gelation in Macroionic Cluster Solutions.

The critical gelation conditions observed in dilute aqueous solutions of multiple nanoscale uranyl peroxide molecular clusters are reported, in the presence of multivalent cations. This gelation is dominantly driven by counterion-mediated attraction. The gelation areas in the corresponding phase diagrams all appear in similar locations, with a characteristic triangle shape outlining three critical boundary conditions, corresponding to the critical cluster concentration, cation/cluster ratio, and the degree of counterion association with increasing cluster concentration. These interesting phrasal observations reveal general conditions for gelation driven by electrostatic interactions in hydrophilic macroionic solutions.

Online Streaming Video Super-Resolution With Convolutional Look-Up Table.

Online video streaming has fundamental limitations on the transmission bandwidth and computational capacity and super-resolution is a promising potential solution. However, applying existing video super-resolution methods to online streaming is non-trivial. Existing video codecs and streaming protocols (e.g., WebRTC) dynamically change the video quality both spatially and temporally, which leads to diverse and dynamic degradations. Furthermore, online streaming has a strict requirement for latency that most existing methods are less applicable. As a result, this paper focuses on the rarely exploited problem setting of online streaming video super resolution. To facilitate the research on this problem, a new benchmark dataset named LDV-WebRTC is constructed based on a real-world online streaming system. Leveraging the new benchmark dataset, we propose a novel method specifically for online video streaming, which contains a convolution and Look-Up Table (LUT) hybrid model to achieve better performance-latency trade-off. To tackle the changing degradations, we propose a mixture-of-expert-LUT module, where a set of LUT specialized in different degradations are built and adaptively combined to handle different degradations. Experiments show our method achieves 720P video SR around 100 FPS, while significantly outperforms existing LUT-based methods and offers competitive performance compared to efficient CNN-based methods. Code is available at https://github.com/quzefan/ConvLUT.

Electronic structure and optical properties of In- and Vacancy-doped 6H-SiC: a first-principles study.

PURPOSES: The paper aims to investigative the cacuses and impacts of In- and Vacancy-doped to 6H-SiC, expecting that improving optical properties of materials. Design-Using the first-principles calculations, we discuss the electronic structure and optical properties of different doped 6H-SiC systems. FINDINGS: The results show that In-doped 6H-SiC becomes a direct bandgap p-type semiconductor and the energy bandgap is reduced from the intrinsic 2.059 to 1.515 eV. We demonstrate the stability of the systems through the formation energy analysis, meanwhile identify their physical origins and discuss applications of all structures in electronic devices within optical analysis. Find the energy beginning values of the VSi-doped and VC-doped systems' optical absorption spectrums and extend to 0.4 2 eV and 0.11 eV respectively compared with the original 3.23 eV. In the visible light region, the reflectivity images of the VC/VSi and (In, VSi)-codoped systems rise obviously. CONCLUSIONS: The optical properties of all doping systems were analyzed to be improved compared with the intrinsic, all above mentioned provide a theoretical basis for the fabrication of spintronic and optical devices.

Deep-learning-based renal artery stenosis diagnosis via multimodal fusion.

PURPOSE: Diagnosing Renal artery stenosis (RAS) presents challenges. This research aimed to develop a deep learning model for the computer-aided diagnosis of RAS, utilizing multimodal fusion technology based on ultrasound scanning images, spectral waveforms, and clinical information. METHODS: A total of 1485 patients received renal artery ultrasonography from Peking Union Medical College Hospital were included and their color doppler sonography (CDS) images were classified according to anatomical site and left-right orientation. The RAS diagnosis was modeled as a process involving feature extraction and multimodal fusion. Three deep learning (DL) models (ResNeSt, ResNet, and XCiT) were trained on a multimodal dataset consisted of CDS images, spectrum waveform images, and individual basic information. Predicted performance of different models were compared with senior physician and evaluated on a test dataset (N = 117 patients) with renal artery angiography results. RESULTS: Sample sizes of training and validation datasets were 3292 and 169 respectively. On test data (N = 676 samples), predicted accuracies of three DL models were more than 80% and the ResNeSt achieved the accuracy 83.49% ± 0.45%, precision 81.89% ± 3.00%, and recall 76.97% ± 3.7%. There was no significant difference between the accuracy of ResNeSt and ResNet (82.84% ± 1.52%), and the ResNeSt was higher than the XCiT (80.71% ± 2.23%, p < 0.05). Compared to the gold standard, renal artery angiography, the accuracy of ResNest model was 78.25% ± 1.62%, which was inferior to the senior physician (90.09%). Besides, compared to the multimodal fusion model, the performance of single-modal model on spectrum waveform images was relatively lower. CONCLUSION: The DL multimodal fusion model shows promising results in assisting RAS diagnosis.

A Novel Air-Cooled Nd:YAG Laser for the Treatment of the Venous Lakes of the Lips.

Objective: To evaluate the therapeutic effect of a novel air-cooled Nd:YAG laser in the venous lakes of the lips (VLL). Background: The thermal injury is one of the most important issues during laser therapy for venous lakes. Methods: Six pieces of fresh pork livers were used to provide 30 regions with a diameter of 6 mm for experiment in vitro, among which 15 regions were treated by Nd:YAG laser with air cooling until the tissue turned gray-white, whereas the rest were treated without air cooling as control. The operation time of laser irradiation, the degree of temperature increase, and the depth of coagulation tissue were compared between two groups. Then, 60 VLL patients were selected for Nd:YAG laser treatment with or without air cooling. The operation time of laser irradiation, the degree of temperature increase, the postoperative pain visual analog scale (VAS) score, and the percentage of lesions removed within 1 month were compared. Results: In tissue studies, the treated group showed a longer operation time of laser irradiation (p < 0.01), a lower degree of temperature increase (p < 0.01), and there was no significant statistical difference in the depth of coagulation tissue (p = 0.624). In clinical studies, the treated group showed a longer operation time of laser irradiation (p < 0.01), a lower degree of temperature increase (p < 0.01), and a lower VAS score on the 1st and 2nd day, compared with the control group (p < 0.01). Conclusions: Air cooling during Nd:YAG laser for the treatment of VLL can prolong the surgical time, but lowered tissue temperature and reduced patient pain within 2 days under the premise of ensuring the treatment effect.

MicroRNA-145-5p Regulates the Epithelial-Mesenchymal Transition in Nasal Polyps by Targeting Smad3.

OBJECTIVES: The annual prevalence of chronic rhinosinusitis (CRS) is increasing, and the lack of effective treatments imposes a substantial burden on both patients and society. The formation of nasal polyps in patients with CRS is closely related to tissue remodeling, which is largely driven by the epithelial-mesenchymal transition (EMT). MicroRNA (miRNA) plays a pivotal role in the pathogenesis of numerous diseases through the miRNA-mRNA regulatory network; however, the specific mechanism of the miRNAs involved in the formation of nasal polyps remains unclear. METHODS: The expression of EMT markers and Smad3 were detected using western blots, quantitative real-time polymerase chain reaction, and immunohistochemical and immunofluorescence staining. Differentially expressed genes in nasal polyps and normal tissues were screened through the Gene Expression Omnibus database. To predict the target genes of miR-145-5p, three different miRNA target prediction databases were used. The migratory ability of cells was evaluated using cell migration assay and wound healing assays. RESULTS: miR-145-5p was associated with the EMT process and was significantly downregulated in nasal polyp tissues. In vitro experiments revealed that the downregulation of miR-145-5p promoted EMT. Conversely, increasing miR-145-5p levels reversed the EMT induced by transforming growth factor-ß1. Bioinformatics analysis suggested that miR-145-5p targets Smad3. Subsequent experiments confirmed that miR-145-5p inhibits Smad3 expression. CONCLUSION: Overall, miR-145-5p is a promising target to inhibit nasal polyp formation, and the findings of this study provide a theoretical basis for nanoparticle-mediated miR-145-5p delivery for the treatment of nasal polyps.

A historical controlled study of domestic trastuzumab and pertuzumab in combination with docetaxel for the neoadjuvant treatment of early HER2-positive breast cancer.

Background: HER2-positive molecular breast cancer subtypes are characterized by high aggressiveness and malignancy, and their metastasis and mortality rates are among the highest of all types of breast cancer. The use of anti-HER2-targeted agents in neoadjuvant therapy has significantly improved the prognosis of patients with HER2-positive breast cancer. In this study, we investigated the efficacy and safety of a neoadjuvant Chinese THP regimen (docetaxel, trastuzumab biosimilar TQB211 plus the pertuzumab biosimilar TQB2440 or pertuzumab) for ER/PR-negative and HER2-positive breast cancer in China. Method: All enrolled patients received the THP regimen (T: docetaxel 75 mg/m2 per cycle; H: trastuzumab biosimilar TQB211 8 mg/kg in the first cycle and 6 mg/kg maintenance dose in cycles 2 to 4; P: pertuzumab biosimilar TQB2440 or pertuzumab 840 mg in the first cycle, maintenance dose 420 mg in cycles 2 to 4) every 3 weeks for 4 cycles. The biosimilar TQB2440 pertuzumab and pertuzumab were randomly assigned to patients. Docetaxel, TQB211, and TQB2440 were all developed by Chiatai Tianqing. The primary endpoint was the complete pathological response (pCR) in the breast, and the secondary endpoint was cardiac safety. Results: Of the 28 eligible patients, 19 (67.9%) achieved tpCR. The tpCR rate was higher than in the NeoSphere trial (pCR63.2%) and the PEONY study (tpCR52.5%). The adverse events that occurred most frequently were leukopenia and neutropenia, with incidence rates of 82.1% and 75.0%, respectively. Of these, grade 3 leukopenia and neutropenia occupied 46.4% and 35.7%. Other grade 3 or higher adverse events were bone marrow suppression (7.1%), lymphopenia (3.6%), and anemia (3.6%). There were no events of heart failure in patients and no patient died during the neoadjuvant phase. Conclusion: Domestic dual-target HP has a more satisfactory efficacy and safety in the neoadjuvant phase of treatment. Clinical trial registration: https://clinicaltrials.gov/study/NCT05985187, NCT05985187.