Prediction of lymphovascular invasion of gastric cancer based on contrast-enhanced computed tomography radiomics.

Background: Lymphovascular invasion (LVI) is a significant risk factor for lymph node metastasis in gastric cancer (GC) and is closely related to the prognosis and recurrence of GC. This study aimed to establish clinical models, radiomics models and combination models for the diagnosis of GC vascular invasion. Methods: This study enrolled 146 patients with GC proved by pathology and who underwent radical resection of GC. The patients were assigned to the training and validation cohorts. A total of 1,702 radiomic features were extracted from contrast-enhanced computed tomography images of GC. Logistic regression analyses were performed to establish a clinical model, a radiomics model and a combined model. The performance of the predictive models was measured by the receiver operating characteristic (ROC) curve. Results: In the training cohort, the age of LVI negative (-) patients and LVI positive (+) patients were 62.41 ± 8.41 and 63.76 ± 10.08 years, respectively, and there were more male (n = 63) than female (n = 19) patients in the LVI (+) group. Diameter and differentiation were the independent risk factors for determining LVI (-) and (+). A combined model was found to be relatively highly discriminative based on the area under the ROC curve for both the training (0.853, 95% CI: 0.784-0.920, sensitivity: 0.650 and specificity: 0.907) and the validation cohorts (0.742, 95% CI: 0.559-0.925, sensitivity: 0.736 and specificity: 0.700). Conclusions: The combined model had the highest diagnostic effectiveness, and the nomogram established by this model had good performance. It can provide a reliable prediction method for individual treatment of LVI in GC before surgery.

Asymmetric 1,4-Reduction of Pyrano[2,3-b]indoles with Hantzsch Ester by Chiral Phosphoric Acid.

A highly regioselective and enantioselective transfer hydrogenation of pyrano[2,3-b]indoles with Hantzsch ester has been successfully realized using spiro-chiral phosphoric acid, affording a series of optically active 1,4-reductive adducts, 4,9-dihydropyrano[2,3-b]indoles, in 34-99% yields with 61-99% ee.

Camouflaging endovascular stents with an endothelial coat using CD31 domain 1 and 2 mimetic peptides.

Objective: Implantation of an endovascular device disrupts the homeostatic CD31:CD31 interactions among quiescent endothelial cells (ECs), platelets, and circulating leukocytes. The aim of this study was to design an endothelial-mimetic coating of nitinol and cobalt-chromium (CoCr) surfaces and stents using synthetic CD31 peptides, to promote device endothelialization and pacific integration within the arterial wall. Methods: Peptides mimicking the domains 1 (D1) and 2 (D2) of CD31 were synthetized and immobilized onto experimental nitinol and CoCr surfaces using a three-step, dip-coating, mussel-inspired protocol using copper-free click chemistry. Human aortic EC phenotype and endothelialization assessment using parallel scratch tests were carried out using five synthetic CD31 peptides coated on 4.8-mm nitinol and CoCr flat disks and were compared with control disks. The CD31 peptide exhibiting the best results in vitro was then immobilized on clinical-grade 3 × 40-mm self-expanding nitinol and 2.5 × 20.0-mm balloon-expandable CoCr stents. Such devices were implanted in native arteries of White New Zealand rabbits, and compared with control uncoated bare metal stents (BMS) and drug-eluting stents 7 and 30 days after implantation using resin cross-sections and scanning electron microscopy (n = 2-3 per group at each time point). Results: Membrane-distal CD31 D1 and D2 peptides exhibited a distinct capability to foster a healthy endothelial phenotype and to promote endothelialization in vitro. By day 7 after implantation, CD31 nitinol and CoCr stents were evenly covered by wholesome ECs, devoid of thromboinflammatory signs, in contrast with both BMS and drug-eluting stents. Such results were consistent until day 30. Conclusions: Membrane-distal CD31 biomimetic peptides seem to camouflage the device surface effectively, preventing local reactions and promoting rapid and seamless endovascular integration.

Switchable Chemoselectivity in [3 + 3] Annulation of ß,γ-Unsaturated α-Ketoesters and 1H-Pyrazol-5-amines by Cooperative Acid Catalysis with NiII and InI.

The exchange of the metal ion from Ni(II) to In(I) leads to a switch in the chemoselectivity of the [3 + 3] annulation of ß,γ-unsaturated α-ketoesters and 1H-pyrazol-5-amines in the presence of phosphoric acid 1, affording functionalized 1H-pyrazolo[3,4-b]pyridines 4 in up to 97% yields and highly enantioselective 4,5-dihydro-1H-pyrazolo[3,4-b]pyridines 5 in up to 92% yield and 99% ee.

Learning Common Semantics via Optimal Transport for Contrastive Multi-View Clustering.

Multi-view clustering aims to learn discriminative representations from multi-view data. Although existing methods show impressive performance by leveraging contrastive learning to tackle the representation gap between every two views, they share the common limitation of not performing semantic alignment from a global perspective, resulting in the undermining of semantic patterns in multi-view data. This paper presents CSOT, namely Common Semantics via Optimal Transport, to boost contrastive multi-view clustering via semantic learning in a common space that integrates all views. Through optimal transport, the samples in multiple views are mapped to the joint clusters which represent the multi-view semantic patterns in the common space. With the semantic assignment derived from the optimal transport plan, we design a semantic learning module where the soft assignment vector works as a global supervision to enforce the model to learn consistent semantics among all views. Moreover, we propose a semantic-aware re-weighting strategy to treat samples differently according to their semantic significance, which improves the effectiveness of cross-view contrastive representation learning. Extensive experimental results demonstrate that CSOT achieves the state-of-the-art clustering performance.

Disruption of the ZFP574-THAP12 complex suppresses B cell malignancies in mice.

Despite the availability of life-extending treatments for B cell leukemias and lymphomas, many of these cancers remain incurable. Thus, the development of new molecular targets and therapeutics is needed to expand treatment options. To identify new molecular targets, we used a forward genetic screen in mice to identify genes required for development or survival of lymphocytes. Here, we describe Zfp574, an essential gene encoding a zinc finger protein necessary for normal and malignant lymphocyte survival. We show that ZFP574 interacts with zinc finger protein THAP12 and promotes the G1-to-S-phase transition during cell cycle progression. Mutation of ZFP574 impairs nuclear localization of the ZFP574-THAP12 complex. ZFP574 or THAP12 deficiency results in cell cycle arrest and impaired lymphoproliferation. Germline mutation, acute gene deletion, or targeted degradation of ZFP574 suppressed Myc-driven B cell leukemia in mice, but normal B cells were largely spared, permitting long-term survival, whereas complete lethality was observed in control animals. Our findings support the identification of drugs targeting ZFP574-THAP12 as a unique strategy to treat B cell malignancies.

High vegetable consumption and regular exercise are associated with better quality of life in patients with gout.

BACKGROUND/AIMS: The Gout Impact Scale (GIS), a part of the Gout Assessment Questionnaire 2.0, is used to measure gout-specific health-related quality of life (HRQOL). Although several studies have been conducted on the factors affecting the HRQOL of patients with gout, few have focused on lifestyle factors. This study aimed to investigate the correlation between lifestyle habits and HRQOL using the GIS in patients with gout. METHODS: We used data from the Urate-Lowering TheRApy in Gout (ULTRA) registry, a prospective cohort of Korean patients with gout treated at multiple centers nationwide. The patients were aged ≥18 years and met the 2015 American College of Rheumatology/European League Against Rheumatism gout classification criteria. They were asked to complete a GIS and questions regarding their lifestyle habits at enrollment. RESULTS: The study included 232 patients. 'Gout concern overall' scores in the GIS were significantly lower in patients who exercised more frequently and consumed soft drinks and meat less, and 'well-being during attack' scores were significantly lower in patients who consumed vegetables and exercised more frequently. The frequency of vegetable consumption had a negative linear relationship with the 'well-being during attack' and 'gout concern during attack' scores (p = 0.01, p = 0.001, respectively). The frequency of exercise had a negative linear relationship with the 'gout concern overall' and 'gout concern during attack' scores (p = 0.04 and p = 0.002, respectively). CONCLUSION: Patients with gout who frequently consumed vegetables and exercised regularly experienced less impact of gout, exhibiting a better GIS that represented HRQOL.

From Intercalation to External Binding: Ru(II) Complexes with a Spiro Ligand for TAR RNA Selective Binding and HIV-1 Reverse Transcriptase Inhibition.

As a typical RNA virus, the genetic information on HIV-1 is entirely stored in RNA. The reverse transcription activity of HIV-1 reverse transcriptase (RT) plays a crucial role in the replication and transmission of the virus. Non-nucleoside RT inhibitors (NNRTIs) block the function of RT by binding to the RNA binding site on RT, with very few targeting viral RNA. In this study, by transforming planar conjugated ligands into a spiro structure, we convert classical Ru(II) DNA intercalators into a nonintercalator. This enables selective binding to HIV-1 transactivation response (TAR) RNA on the outer side of nucleic acids through dual interactions involving hydrogen bonds and electrostatic attraction, effectively inhibiting HIV-1 RT and serving as a selective fluorescence probe for TAR RNA.

Induction-concurrent chemoradiotherapy with or without sintilimab in patients with locoregionally advanced nasopharyngeal carcinoma in China (CONTINUUM): a multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial.

BACKGROUND: Anti-PD-1 therapy and chemotherapy is a recommended first-line treatment for recurrent or metastatic nasopharyngeal carcinoma, but the role of PD-1 blockade remains unknown in patients with locoregionally advanced nasopharyngeal carcinoma. We assessed the addition of sintilimab, a PD-1 inhibitor, to standard chemoradiotherapy in this patient population. METHODS: This multicentre, open-label, parallel-group, randomised, controlled, phase 3 trial was conducted at nine hospitals in China. Adults aged 18-65 years with newly diagnosed high-risk non-metastatic stage III-IVa locoregionally advanced nasopharyngeal carcinoma (excluding T3-4N0 and T3N1) were eligible. Patients were randomly assigned (1:1) using blocks of four to receive gemcitabine and cisplatin induction chemotherapy followed by concurrent cisplatin radiotherapy (standard therapy group) or standard therapy with 200 mg sintilimab intravenously once every 3 weeks for 12 cycles (comprising three induction, three concurrent, and six adjuvant cycles to radiotherapy; sintilimab group). The primary endpoint was event-free survival from randomisation to disease recurrence (locoregional or distant) or death from any cause in the intention-to-treat population. Secondary endpoints included adverse events. This trial is registered with ClinicalTrials.gov (NCT03700476) and is now completed; follow-up is ongoing. FINDINGS: Between Dec 21, 2018, and March 31, 2020, 425 patients were enrolled and randomly assigned to the sintilimab (n=210) or standard therapy groups (n=215). At median follow-up of 41·9 months (IQR 38·0-44·8; 389 alive at primary data cutoff [Feb 28, 2023] and 366 [94%] had at least 36 months of follow-up), event-free survival was higher in the sintilimab group compared with the standard therapy group (36-month rates 86% [95% CI 81-90] vs 76% [70-81]; stratified hazard ratio 0·59 [0·38-0·92]; p=0·019). Grade 3-4 adverse events occurred in 155 (74%) in the sintilimab group versus 140 (65%) in the standard therapy group, with the most common being stomatitis (68 [33%] vs 64 [30%]), leukopenia (54 [26%] vs 48 [22%]), and neutropenia (50 [24%] vs 46 [21%]). Two (1%) patients died in the sintilimab group (both considered to be immune-related) and one (<1%) in the standard therapy group. Grade 3-4 immune-related adverse events occurred in 20 (10%) patients in the sintilimab group. INTERPRETATION: Addition of sintilimab to chemoradiotherapy improved event-free survival, albeit with higher but manageable adverse events. Longer follow-up is necessary to determine whether this regimen can be considered as the standard of care for patients with high-risk locoregionally advanced nasopharyngeal carcinoma. FUNDING: National Natural Science Foundation of China, Key-Area Research and Development Program of Guangdong Province, Natural Science Foundation of Guangdong Province, Overseas Expertise Introduction Project for Discipline Innovation, Guangzhou Municipal Health Commission, and Cancer Innovative Research Program of Sun Yat-sen University Cancer Center. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

PDZK1 confers sensitivity to sunitinib in clear cell renal cell carcinoma by suppressing the PDGFR-ß pathway.

BACKGROUND: Sunitinib has emerged as the primary treatment for advanced or metastatic clear cell renal cell carcinoma (ccRCC) due to its significant improvement in patients' average survival time. However, drug resistance and adverse effects of sunitinib pose challenges to its clinical benefits. METHODS: The differentially expressed genes (DEGs) associated with sunitinib sensitivity and resistance in ccRCC were investigated. Cell counting kit-8, plate colony formation, flow cytometry and subcutaneous xenograft tumor model assays were employed to explore the effects of PDZK1 on ccRCC. Further research on the molecular mechanism was conducted through western blot, co-immunoprecipitation, immunofluorescence co-localization and immunohistochemical staining. RESULTS: We elucidated that PDZK1 is significantly downregulated in sunitinib-resistant ccRCC specimens, and PDZK1 negatively regulates the phosphorylation of PDGFR-ß and the activation of its downstream pathways through interaction with PDGFR-ß. The dysregulated low levels of PDZK1 contribute to inadequate inhibition of cell proliferation, tumor growth, and insensitivity to sunitinib treatment. Notably, our preclinical investigations showed that miR-15b antagomirs enhance sunitinib cytotoxic effects against ccRCC cells by upregulating PDZK1 levels, suggesting their potential in overcoming sunitinib resistance. CONCLUSIONS: Our findings establish the miR-15b/PDZK1/PDGFR-ß axis as a promising therapeutic target and a novel predictor for ccRCC patients' response to sunitinib treatment.

DeTAL: Open-Vocabulary Temporal Action Localization with Decoupled Networks.

Pre-trained visual-language (ViL) models have demonstrated good zero-shot capability in video understanding tasks, where they were usually adapted through fine-tuning or temporal modeling. However, in the task of open-vocabulary temporal action localization (OV-TAL), such adaption reduces the robustness of ViL models against different data distributions, leading to a misalignment between visual representations and text descriptions of unseen action categories. As a result, existing methods often strike a trade-off between action detection and classification. Aiming at this issue, this paper proposes DeTAL, a simple but effective two-stage approach for OV-TAL. DeTAL decouples action detection from action classification to avoid the compromise between them, and the state-of-the-art methods for close-set action localization can be handily adapted to OV-TAL, which significantly improves the performance. Meanwhile, DeTAL can easily tackle the scenario where action category annotations are unavailable in the training dataset. In the experiments, we propose a new cross-dataset setting to evaluate the zero-shot capability of different methods. And the results demonstrate that DeTAL outperforms the state-of-the-art methods for OV-TAL on both THUMOS14 and ActivityNet1.3. Code and data are publicly available at https://github.com/vsislab/DeTAL.

IGCN: A Provably Informative GCN Embedding for Semi-Supervised Learning with Extremely Limited Labels.

Graph Neural Networks (GNNs) have gained much more attention in the representation learning for the graph-structured data. However, the labels are always limited in the graph, which easily leads to the overfitting problem and causes the poor performance. To solve this problem, we propose a new framework called IGCN, short for Informative Graph Convolutional Network, where the objective of IGCN is designed to obtain the informative embeddings via discarding the task-irrelevant information of the graph data based on the mutual information. As the mutual information for irregular data is intractable to compute, our framework is optimized via a surrogate objective, where two terms are derived to approximate the original objective. For the former term, it demonstrates that the mutual information between the learned embeddings and the ground truth should be high, where we utilize the semi-supervised classification loss and the prototype based supervised contrastive learning loss for optimizing it. For the latter term, it requires that the mutual information between the learned node embeddings and the initial embeddings should be high and we propose to minimize the reconstruction loss between them to achieve the goal of maximizing the latter term from the feature level and the layer level, which contains the graph encoder-decoder module and a novel architecture GCN Info. Moreover, we provably show that the designed GCN Info can better alleviate the information loss and preserve as much useful information of the initial embeddings as possible. Experimental results show that the IGCN outperforms the state-of-the-art methods on 7 popular datasets.

A machine learning based method for constructing group profiles of university students.

This study facilitates university student profiling by constructing a prediction model to forecast the classification of future students participating in a survey, thereby enhancing the utility and effectiveness of the questionnaire approach. In the context of the ongoing digital transformation of campuses, higher education institutions are increasingly prioritizing student educational development. This shift aligns with the maturation of big data technology, prompting scholars to focus on profiling university student education. While earlier research in this area, particularly foreign studies, focus on extracting data from specific learning contexts and often relied on single data sources, our study addresses these limitations. We employ a comprehensive approach, incorporating questionnaire surveys to capture a diverse array of student data. Considering various university student attributes, we create a holistic profile of the student population. Furthermore, we use clustering techniques to develop a categorical prediction model. In our clustering analysis, we employ the K-means algorithm to group student survey data. The results reveal four distinct student profiles: Diligent Learners, Earnest Individuals, Discerning Achievers, and Moral Advocates. These profiles are subsequently used to label student groups. For the classification task, we leverage these labels to establish a prediction model based on the Back Propagation neural network, with the goal of assigning students to their respective groups. Through meticulous model optimization, an impressive classification accuracy of 90.22% is achieved. Our research offers a novel perspective and serves as a valuable methodological reference for university student profiling.

Structural basis for Retriever-SNX17 assembly and endosomal sorting.

During endosomal recycling, Sorting Nexin 17 (SNX17) facilitates the transport of numerous membrane cargo proteins by tethering them to the Retriever complex. Despite its importance, the mechanisms underlying this interaction have remained elusive. Here, we report the structure of the Retriever-SNX17 complex determined using cryogenic electron microscopy (cryo-EM). Our structure reveals that the C-terminal tail of SNX17 engages with a highly conserved interface between the VPS35L and VPS26C subunits of Retriever. Through comprehensive biochemical, cellular, and proteomic analyses, we demonstrate that disrupting this interface impairs the Retriever-SNX17 interaction, subsequently affecting the recycling of SNX17-dependent cargos and altering the composition of the plasma membrane proteome. Intriguingly, we find that the SNX17-binding pocket on Retriever can be utilized by other ligands that share a consensus acidic C-terminal tail motif. By showing how SNX17 is linked to Retriever, our findings uncover a fundamental mechanism underlying endosomal trafficking of critical cargo proteins and reveal a mechanism by which Retriever can engage with other regulatory factors.

Switchable Enantioselectivity in Conjugate Alkyne Addition of ß,γ-Unsaturated α-Keto Esters by Asymmetric Binary Acid Catalysis.

Switchable enantioselectivity was uncovered in the enantioselective catalytic conjugate addition of ß,γ-unsaturated α-keto esters with terminal alkynes to the chiral Lewis acid complex of In(BF4)3 and chiral phosphoric acid.

A green aqueous binder to enhance the electrochemical performance of Li-rich disordered rock salt cathode material.

Li-rich disordered rock-salt oxides (DRX) are considered an attractive cathode material in the future battery field due to their excellent energy density and specific capacity. Nevertheless, anionic redox provides high capacity while causing O2 over-oxidation to O2, resulting in voltage hysteresis and capacity decay. Herein, the crystal structure of Li1.3Mn0.4Ti0.3O1.7F0.3 (LMTOF) cathode is stabilized by using sodium carboxymethylcellulose (CMC) binders replacing traditional polyvinylidene difluoride (PVDF) binders. The electrochemical impedance spectroscopy (EIS) and galvanostatic intermittent titration technique (GITT) reveal that the CMC-based LMTOF electrode has higher electronic conductivity and lithium-ion diffusion kinetics. Moreover, CMC has been demonstrated to improve the O2- reversibility, reduce the amounts of byproducts from electrolyte decomposition and suppress transition metal dissolution by Na+/Li+ exchange reaction. Furthermore, the CMC-based LMTOF electrode also exhibits less volume change upon lithiation/delithiation processes compared to the PVDF-based electrode, resulting in enhanced structural stability during cycling. Benefiting from these features, the CMC binders can effectively improve the cycling life and rate performance of the LMTOF cathode, and the CMC-based LMTOF electrode shows good capacity retention of 94.5 % after 30 cycles at 20 mA/g and 66.7 % after 100 cycles at 200 mA/g. This finding indicates that CMC as a binder can efficiently stabilize the structure and improve the electrochemical performance of Li-rich disordered rock-salt oxides cathode, making it possible for practical Li-ion battery applications.

PolypMixNet: Enhancing semi-supervised polyp segmentation with polyp-aware augmentation.

BACKGROUND: AI-assisted polyp segmentation in colonoscopy plays a crucial role in enabling prompt diagnosis and treatment of colorectal cancer. However, the lack of sufficient annotated data poses a significant challenge for supervised learning approaches. Existing semi-supervised learning methods also suffer from performance degradation, mainly due to task-specific characteristics, such as class imbalance in polyp segmentation. PURPOSE: The purpose of this work is to develop an effective semi-supervised learning framework for accurate polyp segmentation in colonoscopy, addressing limited annotated data and class imbalance challenges. METHODS: We proposed PolypMixNet, a semi-supervised framework, for colorectal polyp segmentation, utilizing novel augmentation techniques and a Mean Teacher architecture to improve model performance. PolypMixNet introduces the polyp-aware mixup (PolypMix) algorithm and incorporates dual-level consistency regularization. PolypMix addresses the class imbalance in colonoscopy datasets and enhances the diversity of training data. By performing a polyp-aware mixup on unlabeled samples, it generates mixed images with polyp context along with their artificial labels. A polyp-directed soft pseudo-labeling (PDSPL) mechanism was proposed to generate high-quality pseudo labels and eliminate the dilution of lesion features caused by mixup operations. To ensure consistency in the training phase, we introduce the PolypMix prediction consistency (PMPC) loss and PolypMix attention consistency (PMAC) loss, enforcing consistency at both image and feature levels. Code is available at https://github.com/YChienHung/PolypMix. RESULTS: PolypMixNet was evaluated on four public colonoscopy datasets, achieving 88.97% Dice and 88.85% mIoU on the benchmark dataset of Kvasir-SEG. In scenarios where the labeled training data is limited to 15%, PolypMixNet outperforms the state-of-the-art semi-supervised approaches with a 2.88-point improvement in Dice. It also shows the ability to reach performance comparable to the fully supervised counterpart. Additionally, we conducted extensive ablation studies to validate the effectiveness of each module and highlight the superiority of our proposed approach. CONCLUSION: PolypMixNet effectively addresses the challenges posed by limited annotated data and unbalanced class distributions in polyp segmentation. By leveraging unlabeled data and incorporating novel augmentation and consistency regularization techniques, our method achieves state-of-the-art performance. We believe that the insights and contributions presented in this work will pave the way for further advancements in semi-supervised polyp segmentation and inspire future research in the medical imaging domain.

Clinical Features of Li-Fraumeni Syndrome in Korea.

PURPOSE: Li-Fraumeni syndrome (LFS) is a hereditary disorder caused by germline mutation in TP53. Owing to the rarity of LFS, data on its clinical features are limited. This study aimed to evaluate the clinical characteristics and prognosis of Korean patients with LFS. MATERIALS AND METHODS: Patients who underwent genetic counseling and confirmed with germline TP53 mutation in the National Cancer Center in Korea between 2011 and 2022 were retrospectively reviewed. Data on family history with pedigree, types of mutation, clinical features, and prognosis were collected. RESULTS: Fourteen patients with LFS were included in this study. The median age at diagnosis of the first tumor was 32 years. Missense and nonsense mutations were observed in 13 and one patients, respectively. The repeated mutations were p.Arg273His, p.Ala138Val, and pPro190Leu. The sister with breast cancer harbored the same mutation of p.Ala138Val. Seven patients had multiple primary cancers. Breast cancer was most frequently observed, and other types of tumor included sarcoma, thyroid cancer, pancreatic cancer, brain tumor, adrenocortical carcinoma, ovarian cancer, endometrial cancer, colon cancer, vaginal cancer, skin cancer, and leukemia. The median follow-up period was 51.5 months. Two and four patients showed local recurrence and distant metastasis, respectively. Two patients died of leukemia and pancreatic cancer 3 and 23 months after diagnosis, respectively. CONCLUSION: This study provides information on different characteristics of patients with LFS, including types of mutation, types of cancer, and prognostic outcomes. For more appropriate management of these patients, proper genetic screening and multidisciplinary discussion are required.

Cu(OTf)2-Phosphoric Acid-Catalyzed Tandem Oxa-Nazarov Cyclization and Dibromination of Conjugated 1,2-Diketones.

A facile tandem oxa-Nazarov cyclization and dibromination has been developed. The combination of Cu(OTf)2 and diphenyl phosphate (DPP-H) was found to synergistically promote the coupling of conjugated 1,2-diketones and N-bromosuccinimide to form 2,4-dibromo-3(2H)-furanones in good yields.