工程技术最新文献

{"title":"An effective encryption approach using a combination of a non-chain ring and a four-dimensional chaotic map.","authors":"Muhammad Umair Safdar, Tariq Shah, Asif Ali","doi":"10.1007/s11571-025-10217-1","DOIUrl":"10.1007/s11571-025-10217-1","url":null,"abstract":"<p><p>Algebraic structures are highly effective in designing symmetric key cryptosystems; however, if the key space is not sufficiently large, such systems become vulnerable to brute-force attacks. To address this challenge, our research focuses on enlarging the key space in symmetric key schemes by integrating the non-chain ring with a four-dimensional chaotic system. While chaotic maps offer significant potential for data processing, relying solely on them does not fully leverage their operational advantages. Therefore, it is essential to incorporate algebraic structures that enhance the complexity of the scheme. In the proposed technique, four-dimensional chaotic sequences are employed for image pixel permutation, diffusion, and exclusive-or operations. The scheme is further strengthened against chosen and known plaintext attacks by incorporating pixel values during the exclusive-or operation, where images are XORed with hashed images and keys generated from chaotic sequences. The effectiveness of the technique, its resilience to various forms of attack, and its feasibility for practical implementation are demonstrated through extensive testing and a comprehensive security analysis.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"27"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11735708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-view domain adaption based multi-scale convolutional conditional invertible discriminator for cross-subject electroencephalogram emotion recognition.","authors":"Sivasaravana Babu S, Prabhu Venkatesan, Parthasarathy Velusamy, Saravana Kumar Ganesan","doi":"10.1007/s11571-024-10193-y","DOIUrl":"10.1007/s11571-024-10193-y","url":null,"abstract":"<p><p>Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people. Accurately predicting emotions poses challenges due to dynamic traits. Models struggle with feature extraction, convergence, and negative transfer issues, hindering cross subject emotion recognition. The proposed model employs thorough signal preprocessing, Short-Time Geodesic Flow Kernel Fourier Transform (STGFKFT) for feature extraction, enhancing classifiers' accuracy. Multi-view sheaf attention improves feature discrimination, while the Multi-Scale Convolutional Conditional Invertible Puma Discriminator Neural Network (MSCCIPDNN) framework ensures generalization. Efficient computational techniques and the puma optimization algorithm enhance model robustness and convergence. The suggested framework demonstrates extraordinary success with high accuracy, of 99.5%, 99% and 99.50% for SEED, SEED-IV, and DEAP dataset sequentially. By incorporating these techniques, the proposed method aims to precisely recognition emotions, and accurately captures the features, thereby overcoming the limitations of existing methodologies.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"23"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729617/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3T dilated inception network for enhanced autism spectrum disorder diagnosis using resting-state fMRI data.","authors":"V Kavitha, R Siva","doi":"10.1007/s11571-024-10202-0","DOIUrl":"10.1007/s11571-024-10202-0","url":null,"abstract":"<p><p>Autism spectrum disorder (ASD) is one of the complicated neurodevelopmental disorders that impacts the daily functioning and social interactions of individuals. It includes diverse symptoms and severity levels, making it challenging to diagnose and treat efficiently. Various deep learning (DL) based methods have been developed for diagnosing ASD, which rely heavily on behavioral assessment. However, existing techniques have suffered from poor diagnostic outcomes, higher computational complexity, and overfitting issues. To address these challenges, this research work introduces an innovative framework called 3T Dilated Inception Network (3T-DINet) for effective ASD diagnosis using resting-state functional Magnetic Resonance Imaging (rs-fMRI) images. The proposed 3T-DINet technique designs a 3T dilated inception module that incorporates dilated convolutions along with the inception module, allowing it to extract multi-scale features from brain connectivity patterns. The 3T dilated inception module uses three distinct dilation rates (low, medium, and high) in parallel to determine local, mid-level, and global features from the brain. In addition, the proposed approach implements Residual networks (ResNet) to avoid the vanishing gradient problem and enhance the feature extraction ability. The model is further optimized using a Crossover-based Black Widow Optimization (CBWO) algorithm that fine-tunes the hyperparameters thereby enhancing the overall performance of the model. Further, the performance of the 3T-DINet model is evaluated using the five ASD datasets with distinct evaluation parameters. The proposed 3T-DINet technique achieved superior diagnosis results compared to recent previous works. From this simulation validation, it's clear that the 3T-DINet provides an excellent contribution to early ASD diagnosis and enhances patient treatment outcomes.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"22"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143001551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of memristive emotion associative learning circuit.","authors":"Zhangzhi Zhou, Mi Lin, Xuanxuan Zhou, Chong Zhang","doi":"10.1007/s11571-024-10211-z","DOIUrl":"10.1007/s11571-024-10211-z","url":null,"abstract":"<p><p>Psychological studies have demonstrated that the music can affect memory by triggering different emotions. Building on the relationships among music, emotion, and memory, a memristor-based emotion associative learning circuit is designed by utilizing the nonlinear and non-volatile characteristics of memristors, which includes a music judgment module, three emotion generation modules, three emotional homeostasis modules, and a memory module to implement functions such as learning, second learning, forgetting, emotion generation, and emotional homeostasis. The experimental results indicate that the proposed circuit can simulate the learning and forgetting processes of human under different music circumstances, demonstrate the feasibility of memristors in biomimetic circuits, verify the impact of music on memory, and provide a foundation for in-depth research and application development of the interaction mechanism between emotion and memory.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"13"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal time-frequency localized wavelet filters for identification of Alzheimer's disease from EEG signals.","authors":"Digambar V Puri, Jayanand P Gawande, Pramod H Kachare, Ibrahim Al-Shourbaji","doi":"10.1007/s11571-024-10198-7","DOIUrl":"10.1007/s11571-024-10198-7","url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a chronic disability that occurs due to the loss of neurons. The traditional methods to detect AD involve questionnaires and expensive neuro-imaging tests, which are time-consuming, subjective, and inconvenient to the target population. To overcome these limitations, Electroencephalogram (EEG) based methods have been developed to classify AD patients from normal controlled (NC) and mild cognitive impairment (MCI) subjects. Most of the EEG-based methods involved entropy-based feature extraction and discrete wavelet transform. However, the existing AD classification methods failed to provide promising classification accuracy. Here, we proposed a wavelet-machine learning (ML) framework to detect AD using a newly designed biorthogonal filter bank by optimization of frequency and time localization of triplet halfband filter banks (OTFL-THFB). The OTFL-THFB decomposes EEG signals into various EEG sub- bands. Hjorth Parameters (HP) and Higuchi's Fractal Dimension (HFD) have been investigated to extract features from each EEG subband. Subsequently, ML models are trained and tested using different features such as OTFL-THFB with HFD, OTFL-THFB with HP, and OTFL-THFB with HFD and HP used for detecting AD with 10-fold cross-validation. This method was applied to two publicly available datasets. Our model achieved an accuracy of <math><mrow><mn>98.91</mn> <mo>%</mo></mrow> </math> for AD versus NC and <math><mrow><mn>98.65</mn> <mo>%</mo></mrow> </math> for AD versus MCI versus NC using the least square support vector machine. Results indicate that this framework surpassed existing state-of-the-art techniques for classifying AD from NC.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"12"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The phonation test can distinguish the patient with Parkinson's disease via Bayes inference.","authors":"Yifeng Liu, Hongjie Gong, Meimei Mouse, Fan Xu, Xianwei Zou, Jingsheng Yang, Qingping Xue, Min Huang","doi":"10.1007/s11571-024-10194-x","DOIUrl":"10.1007/s11571-024-10194-x","url":null,"abstract":"<p><p>Parkinson's disease (PD) is a neurodegenerative disease with various clinical manifestations caused by multiple risk factors. However, the effect of different factors and relationships between different features related to PD and the extent of those factors leading to the incidence of PD remains unclear. we employed Bayesian network to construct a prediction model. The prediction system was trained on the data of 35 patients and 26 controls. The structure learning and parameter learning of Bayesian Network was completed through the tree-augmented network (TAN) and Netica software, respectively. We employed four Bayesian Networks in terms of the syllable, including monosyllables, disyllables, multisyllables and unsegmented syllables. The area under the curve (AUC) of monosyllabic, disyllabic, multisyllabic, and unsegmented-syllable models were 0.95, 0.83, 0.80 and 0.84, respectively. In the monosyllabic tests, the best predictor of PD was duration, the posterior probability of which was 92.70%. Meanwhile, minimum f0 (61.60%) predicted best in the disyllabic tests and the variables that predicted best in multisyllables and unsegmented syllables were end f0 (59.40%) and maximum f0 (58.40%). In the cross-sectional comparison, the prediction effect of each variable in the monosyllabic tests was generally higher than that of other test groups. The monosyllabic models had the highest predicted performance of PD. Among acoustic parameters, duration was the strongest feature in predicting the prevalence of PD in monosyllabic tests. We believe that this network methodology will be a useful tool for the clinical prediction of Parkinson's disease.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11571-024-10194-x.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"18"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11717751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142969961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuroenhancement by repetitive transcranial magnetic stimulation (rTMS) on DLPFC in healthy adults.","authors":"Elias Ebrahimzadeh, Seyyed Mostafa Sadjadi, Mostafa Asgarinejad, Amin Dehghani, Lila Rajabion, Hamid Soltanian-Zadeh","doi":"10.1007/s11571-024-10195-w","DOIUrl":"10.1007/s11571-024-10195-w","url":null,"abstract":"<p><p>The term \"neuroenhancement\" describes the enhancement of cognitive function associated with deficiencies resulting from a specific condition. Nevertheless, there is currently no agreed-upon definition for the term \"neuroenhancement\", and its meaning can change based on the specific research being discussed. As humans, our continual pursuit of expanding our capabilities, encompassing both cognitive and motor skills, has led us to explore various tools. Among these, repetitive Transcranial Magnetic Stimulation (rTMS) stands out, yet its potential remains underestimated. Historically, rTMS was predominantly employed in studies focused on rehabilitation objectives. A small amount of research has examined its use on healthy subjects with the goal of improving cognitive abilities like risk-seeking, working memory, attention, cognitive control, learning, computing speed, and decision-making. It appears that the insights gained in this domain largely stem from indirect outcomes of rehabilitation research. This review aims to scrutinize these studies, assessing the effectiveness of rTMS in enhancing cognitive skills in healthy subjects. Given that the dorsolateral prefrontal cortex (DLPFC) has become a popular focus for rTMS in treating psychiatric disorders, corresponding anatomically to Brodmann areas 9 and 46, and considering the documented success of rTMS stimulation on the DLPFC for cognitive improvement, our focus in this review article centers on the DLPFC as the focal point and region of interest. Additionally, recognizing the significance of theta burst magnetic stimulation protocols (TBS) in mimicking the natural firing patterns of the brain to modulate excitability in specific cortical areas with precision, we have incorporated Theta Burst Stimulation (TBS) wave patterns. This inclusion, mirroring brain patterns, is intended to enhance the efficacy of the rTMS method. To ascertain if brain magnetic stimulation consistently improves cognition, a thorough meta-analysis of the existing literature has been conducted. The findings indicate that, after excluding outlier studies, rTMS may improve cognition when compared to appropriate control circumstances. However, there is also a considerable degree of variation among the researches. The navigation strategy used to reach the stimulation site and the stimulation location are important factors that contribute to the variation between studies. The results of this study can provide professional athletes, firefighters, bodyguards, and therapists-among others in high-risk professions-with insightful information that can help them perform better on the job.</p>","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":"19 1","pages":"34"},"PeriodicalIF":3.1,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11759757/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143045801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiplex CRISPR/Cas9-mediated genome editing to address drought tolerance in wheat.","authors":"Naglaa A Abdallah, Hany Elsharawy, Hamiss A Abulela, Roger Thilmony, Abdelhadi A Abdelhadi, Nagwa I Elarabi","doi":"10.1080/21645698.2022.2120313","DOIUrl":"10.1080/21645698.2022.2120313","url":null,"abstract":"<p><p>Genome editing tools have rapidly been adopted by plant scientists for crop improvement. Genome editing using a multiplex sgRNA-CRISPR/Cas9 genome editing system is a useful technique for crop improvement in monocot species. In this study, we utilized precise gene editing techniques to generate wheat 3'(2'), 5'-bisphosphate nucleotidase (<i>TaSal1</i>) mutants using a multiplex sgRNA-CRISPR/Cas9 genome editing system. Five active <i>TaSal1</i> homologous genes were found in the genome of Giza168 in addition to another apparently inactive gene on chromosome 4A. Three gRNAs were designed and used to target exons 4, 5 and 7 of the five wheat <i>TaSal1</i> genes. Among the 120 Giza168 transgenic plants, 41 lines exhibited mutations and produced heritable <i>TaSal1</i> mutations in the M₁ progeny and 5 lines were full 5 gene knock-outs. These mutant plants exhibit a rolled-leaf phenotype in young leaves and bended stems, but there were no significant changes in the internode length and width, leaf morphology, and stem shape. Anatomical and scanning electron microscope studies of the young leaves of mutated <i>TaSal1</i> lines showed closed stomata, increased stomata width and increase in the size of the bulliform cells. <i>Sal1</i> mutant seedlings germinated and grew better on media containing polyethylene glycol than wildtype seedlings. Our results indicate that the application of the multiplex sgRNA-CRISPR/Cas9 genome editing is efficient tool for mutating more multiple TaSal1 loci in hexaploid wheat.</p>","PeriodicalId":54282,"journal":{"name":"Gm Crops & Food-Biotechnology in Agriculture and the Food Chain","volume":" ","pages":"1-17"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33490173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Antimicrobial capping agents on silver nanoparticles made via green method using natural products from banana plant waste.","authors":"Jimmy K Kabeya, Nadège K Ngombe, Paulin K Mutwale, Justin B Safari, Gauta Gold Matlou, Rui W M Krause, Christian I Nkanga","doi":"10.1080/21691401.2025.2462335","DOIUrl":"10.1080/21691401.2025.2462335","url":null,"abstract":"<p><p>Herein, we investigated the phytochemical composition and antibacterial activities of the organic layers from biosynthesized silver nanoparticles (AgNPs). AgNPs were synthesized using <i>Musa paradisiaca</i> and <i>Musa sapientum</i> extracts. UV-vis absorption in the 400-450 nm range indicated surface plasmonic resonance peak of AgNPs. Samples analyses using dynamic light scattering and transmission electron microscopy revealed the presence of particles within nanometric ranges, with sizes of 30-140 nm and 8-40 nm, respectively. Fourier transform infrared (FTIR) unveiled the presence of several organic functional groups on the surface of AgNPs, indicating the presence of phytochemicals from plant extracts. Thin layer chromatography (TLC) of the phytochemicals (capping agents) from AgNPs identified multiple groups of secondary metabolites. These phytochemical capping agents exhibited antibacterial activities against <i>Staphylococcus aureus</i>, <i>Escherichia coli</i>, and <i>Pseudomonas aeruginosa</i>, with minimum inhibitory concentrations ranging from 62.5 to 1000 µg/mL. Regardless of the bacterial species or plant parts (leaves or pseudo-stems), capping agents from <i>M. sapientum</i> nanoparticles displayed significantly enhanced antibacterial effectiveness compared to all other samples, including the raw plant extracts and biosynthesized capped and uncapped AgNPs. These results suggest the presence of antimicrobial phytochemicals on biosynthesized AgNPs, highlighting the promise of green nanoparticle synthesis as a valuable approach in bioprospecting antimicrobial agents.</p>","PeriodicalId":8736,"journal":{"name":"Artificial Cells, Nanomedicine, and Biotechnology","volume":"53 1","pages":"29-42"},"PeriodicalIF":4.5,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143370356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correlation of MicroRNA-31 with Endometrial Receptivity in Patients with Repeated Implantation Failure of <i>In Vitro</i> Fertilization and Embryo Transfer.","authors":"Yan Tan, Bijun Du, Xixi Chen, Minhong Chen","doi":"10.1080/15476278.2025.2460263","DOIUrl":"10.1080/15476278.2025.2460263","url":null,"abstract":"<p><strong>Objective: </strong>This trial probed the correlation between miR-31 expression and endometrial receptivity (ER) in patients with repeated implantation failure (RIF) of in vitro fertilization and embryo transfer (IVF-ET).</p><p><strong>Methods: </strong>A retrospective study of 80 infertility patients who underwent IVF-ET assisted conception treatment were divided into RIF group and normal pregnancy group (control group) according to the pregnancy outcome after embryo transfer. General information of both groups was collected. Endometrial tissues were collected in the middle luteal phase of the menstrual cycle before IVF-ET. miR-31 levels in endometrial tissues were measured, and endometrial tolerance indicator pulsatility index (PI), resistance index (RI), and endometrial thickness (Em) were detected. The correlation between endometrial miR-31 levels and ER indices was evaluated by Pearson method. ROC curves were utilized to analyze the efficacy of miR-31 in predicting RIF occurrence. The influencing factors of RIF were analyzed by binary Logistic regression.</p><p><strong>Results: </strong>RIF patients had increased miR-31 expression level and endometrial tolerance indicator PI, and RI while decreased Em (<i>p</i> < 0.05). miR-31 in RIF patients was positively correlated with PI and RI, and negatively correlated with Em (<i>p</i> < 0.05). The area under the curve for miR-31 to predict the occurrence of RIF was 0.899, with a sensitivity of 0.750 and a specificity of 0.950. PI, RI, and miR-31 were risk factors for developing RIF in IVF-ET women, and Em was a protective factor (<i>p</i> < 0.05).</p><p><strong>Conclusion: </strong>miR-31 in RIF patients is positively correlated with PI and RI, and negatively correlated with Em.</p>","PeriodicalId":19596,"journal":{"name":"Organogenesis","volume":"21 1","pages":"2460263"},"PeriodicalIF":1.6,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11853553/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143483502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}