Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Forging the Tetracyclic Core Framework of Rhodomolleins XIV and XLII: A Ring-Distortion Approach.

A ring distortion approach for the synthesis of an advanced intermediate en route to rhodomolleins XIV and XLII was described, which led to successful construction of the 5/8/5/5 tetracyclic core framework of the kalmane diterpenoids. Key steps of the strategy include an oxidative dearomatization-induced (ODI)-Diels-Alder cycloaddition, a Dowd-Beckwith rearrangement, and a bioinspired Wagner-Meerwein rearrangement.

Performance of dual-layer spectrum CT virtual monoenergetic images to assess early rectal adenocarcinoma T-stage: comparison with MR.

OBJECTIVES: To evaluate the image quality and utility of virtual monoenergetic images (VMI) of dual-layer spectrum computed tomography (DLSCT) in assessing preoperative T-stage for early rectal adenocarcinoma (ERA). METHODS: This retrospective study included 67 ERA patients (mean age 62 ± 11.1 years) who underwent DLSCT and MR examination. VMI 40-200 keV and poly energetic image (PEI) were reconstructed. The image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor contrast of different energy levels were calculated and compared, respectively. Two radiologists independently assess the image quality of the VMIs and PEI using 5-point scales. The diagnostic accuracies of DLSCT and HR-MRI for ERA T-staging were evaluated and compared. RESULTS: The maximum noise was observed at VMI 40 keV, and noise at VMI 40-200 keV in the arterial and venous phases showed no significant difference (all p > 0.05). The highest SNR and CNR were obtained at VMI 40 keV, significantly greater than other energy levels and PEI (all p < 0.05). Tumor contrast was more evident than PEI at 40-100 keV in the arterial phase and at 40 keV in the venous phase (all p < 0.05). When compared with PEI, VMI 40 keV yielded the highest scores for overall image quality, tumor visibility, and tumor margin delineation, especially in the venous phase (p < 0.05). The overall diagnostic accuracy of DLSCT and HR-MRI for T-stage was 65.67 and 71.64% and showed no significant difference (p > 0.05). CONCLUSIONS: VMI 40 keV improves image quality and accuracy in identifying lesions, providing better diagnostic information for ERA staging. CRITICAL RELEVANCE STATEMENT: Low-keV VMI from DLSCT can improve tumor staging accuracy for early rectal carcinoma, helping guide surgical intervention decisions, and has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC. KEYPOINTS: • Compared with PEI, low-keV VIM derived from DLSCT, particularly at the 40 keV, significantly enhanced the objective and subjective image quality of ERA. • Using VMI 40 keV helped increase lesion detectability, leading to improved diagnostic accuracy for ERA. • Low-keV VMI from DLSCT has shed new light on the potential breakthroughs of assessing preoperative T-stage in RC.

Biomarkers and experimental models for cancer immunology investigation.

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Adjuvant crizotinib treatment selected by patient-derived organoids in a patient with stage IIIA adenocarcinoma with novel LRRTM4-ALK fusion: a case report.

Background: Over 90 different anaplastic lymphoma kinase (ALK) fusions have been reported, and patients with different ALK fusion partners exhibit different responses to targeted therapy. Patient-derived organoid (PDO), a kind of 3-dimensional culture, is a promising model for drug-sensitivity testing for personalized treatment decision-making. It further has the potential to provide treatment strategy for patients with novel mutations, rare mutations, and concomitant mutations, serving as a supplement to evidence-based medicine. Case Description: We report a case in which a man with stage IIIA adenocarcinoma had pleural effusion 1 month after surgery. A novel leucine-rich repeat transmembrane neuronal protein 4 (LRRTM4)-ALK fusion was unveiled by next-generation sequencing (NGS), and PDOs were used in drug-sensitivity testing to select a proper adjuvant therapy for this patient. We chose crizotinib based on result of the test and drugs' availability in China and helped the patient achieve a more than 3-year-long disease-free survival (DFS). Higher variant allele frequencies (VAFs) of the driver mutation were also found in PDOs and their waste culture medium, indicating that the PDO model could filter out cells with driver genes or stemness and help us to identify the critical cancer cell colony in treatment decision-making. Conclusions: For the first time, we report the case of a LRRTM4-ALK fusion. The patient achieved a more than 3-year long-term DFS under crizotinib treatment, which was selected by an emerging PDO drug-sensitivity test model. We also discovered the enrichment of a low-abundance driver mutation in PDO and its waste culture medium, providing a new direction for future research.

Occult breast cancer patients with mastectomy have better prognosis than those with breast-conserving therapy.

Background: This single-center retrospective study compared the efficacy of breast-conserving therapy along with axillary lymph node dissection (ALND) with mastectomy and ALND with regard to survival of Chinese patients with occult breast cancer. Materials & methods: Univariate Kaplan-Meier analysis and multivariate Cox proportional hazards model were used to compare treatments and prognosis. Results: A total of 111 patients with a median follow-up of 72.9 months were included. 39 patients with mastectomy + ALND had better disease-free survival than 72 patients with breast-conserving therapy + ALND (HR = 0.31; p = 0.012). Patients with radiotherapy demonstrated inferior survival for both overall survival (HR = 2.67; p = 0.071) and disease-free survival (HR = 5.35; p = 0.002). Surgical strategies and radiotherapy remained significantly predictive of better disease-free survival in multivariate analyses. Conclusion: Mastectomy and ALND demonstrate superior disease-free prognosis compared with breast-conserving therapy and ALND in occult breast cancer.

Covalent Organic Frameworks for Neuromorphic Devices.

Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices. Covalent organic frameworks (COFs), as crystalline porous polymers, have tailorable skeletons and pores, providing unique platforms for the interplay with photons, excitons, electrons, holes, ions, spins, and molecules. Such features encourage the rising research interest in COF materials in neuromorphic electronics. To develop high-performance COF-based neuromorphic memory devices, it is necessary to comprehensively understand materials, devices, and applications. Therefore, this Perspective focuses on discussing the use of COF materials for neuromorphic memory devices in terms of molecular design, thin-film processing, and neuromorphic applications. Finally, we provide an outlook for future directions and potential applications of COF-based neuromorphic electronics.

Co Single Atoms Anchored in N and P Co-doped Porous Carbon Fibers for Efficient Water Splitting.

Single atom catalysts (SACs) show potential application for highly efficient water splitting. Herein, we designed Co single atoms (SAs) dispersed on N and P co-doped porous carbon nanofibers as electrocatalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The configuration of Co SAs is proved to coordinate with 4 N/O atoms. The long-range interactions between doped P atoms and Co-N4 (O) sites could modulate the electronic structures of M-N4 (O) sites, which greatly reduce the adsorption energies of HER and OER intermediates at metal sites. Density Functional Theory calculations reveal that CoSA /CNFs exhibits optimized HER and OER kinetics when P coordinates with two N atoms. The atomically dispersed Co electrocatalyst exhibits the low overpotentials of 61, 89 and 390 mV for acidic HER, alkaline HER and OER at 10 mA cm-2 current density, along with the Tafel slope of 54, 143 and 74 mV dec-1 , respectively. This work demonstrates the prospect of utilizing di-heteroatom-doping transition metal SACs, and provides a novel and general strategy for the preparation of SACs.

Single nucleotide polymorphisms associated with female breast cancer susceptibility in Chinese population.

Breast cancer is a complex disease influenced by both external and internal factors, among which genetic factors play a critical role. Single-nucleotide polymorphisms (SNPs) are major contributors to the heritability of breast cancer, and their frequencies vary across ethnic groups. In this study, we aimed to investigate the association between 34 SNPs identified in previous genome-wide association studies (GWAS) and overall breast cancer risk, as well as breast cancer subtypes, in the Chinese female population. To accomplish this, we conducted an extensive association analysis using the high-throughput Sequenom MassARRAY® platform in a case-control study comprising 1848 breast cancer patients and 709 healthy controls. Our analysis, which utilized the SNPassoc package in R based on chi-squared (χ2) test and genetic model analysis, identified significant associations between breast cancer risk and SNP rs12493607 (TGFBR2, risk allele C, OR = 1.28 [1.11-1.47], P = 0.0005), as well as a less conservatively significant association with rs4784227 (CASC16, risk allele T, OR = 1.24 [1.08-1.42], P = 0.0017) and rs2046210 (ESR1, risk allele A, OR = 1.50 [1.16-1.95], P = 0.0016). Furthermore, our stratified analyses revealed that rs12493607 was significantly associated with invasive carcinoma, estrogen receptor (ER)-positive, progesterone receptor (PR)-positive, HER2-negative, and young (aged younger than 45) breast cancer. SNP rs4784227 and rs3803662 (CASC16) were associated with invasive carcinoma and ER-positive breast cancer, while rs2046210 was linked to ductal carcinoma in situ, ER-negative, PR-negative, HER2-positive, and elder (aged more than 45) breast cancers. SNPs rs10484919 (ESR1) and rs1038304 (CCDC170) showed links to HER2-positive breast cancer, and rs616488 (PEX14) with premenopausal breast cancer. In summary, our study shed light on the relationship between SNPs and breast cancer susceptibility within a vast Chinese cohort, supporting the development of polygenetic risk scores for the Chinese population. These findings provide valuable insights into the genetic basis of breast cancer and have important implications for risk prediction, early detection, and personalized treatment of this disease.

A novel non-invasive exhaled breath biopsy for the diagnosis and screening of breast cancer.

BACKGROUND: Early detection is critical for improving the survival of breast cancer (BC) patients. Exhaled breath testing as a non-invasive technique might help to improve BC detection. However, the breath test accuracy for BC diagnosis is unclear. METHODS: This multi-center cohort study consecutively recruited 5047 women from four areas of China who underwent BC screening. Breath samples were collected through standardized breath collection procedures. Volatile organic compound (VOC) markers were identified from a high-throughput breathomics analysis by the high-pressure photon ionization-time-of-flight mass spectrometry (HPPI-TOFMS). Diagnostic models were constructed using the random forest algorithm in the discovery cohort and tested in three external validation cohorts. RESULTS: A total of 465 (9.21%) participants were identified with BC. Ten optimal VOC markers were identified to distinguish the breath samples of BC patients from those of non-cancer women. A diagnostic model (BreathBC) consisting of 10 optimal VOC markers showed an area under the curve (AUC) of 0.87 in external validation cohorts. BreathBC-Plus, which combined 10 VOC markers with risk factors, achieved better performance (AUC = 0.94 in the external validation cohorts), superior to that of mammography and ultrasound. Overall, the BreathBC-Plus detection rates were 96.97% for ductal carcinoma in situ, 85.06%, 90.00%, 88.24%, and 100% for stages I, II, III, and IV BC, respectively, with a specificity of 87.70% in the external validation cohorts. CONCLUSIONS: This is the largest study on breath tests to date. Considering the easy-to-perform procedure and high accuracy, these findings exemplify the potential applicability of breath tests in BC screening.

Preoperative MR radiomics based on high-resolution T2-weighted images and amide proton transfer-weighted imaging for predicting lymph node metastasis in rectal adenocarcinoma.

OBJECTIVES: Lymph node (LN) metastasis is an important prognostic factor in rectal cancer (RC). However, accurate identification of LN metastasis can be challenged for radiologists. The aim of our study was to assess the utility of MRI radiomics based on T2-weighted images (T2WI) and amide proton transfer-weighted (APTw) images for predicting LN metastasis in RC preoperatively. METHODS: A total of 125 patients with pathologically confirmed rectal adenocarcinoma (RA) from January 2019 to June 2021 who underwent preoperative MR were enrolled in this retrospective study. Radiomics features were extracted from high-resolution T2WI and APTw images of primary tumor. The most relevant radiomics and clinical features were selected using correlation and multivariate logistic analysis. Radiomics models were built using five machine learning algorithms including support vector machine (SVM), logical regression (LR), k- nearest neighbor (KNN), naive bayes (NB), and random forest (RF). The best algorithm was selected for further establish the clinical- radiomics model. The receiver operating characteristic curve (ROC) analysis was used to assess the performance of radiomics and clinical-radiomics model for predicting LN metastasis. RESULTS: The LR classifier had the best prediction performance, with AUCs of 0.983 (95% CI 0.957-1.000), 0.864 (95% CI 0.729-0.972), 0.851 (95% CI 0.713-0.940) on the training set, validation, and test sets, respectively. In terms of prediction, the clinical-radiomics combined model outperformed the radiomics model. The AUCs of the clinical-radiomics combined model in the validation and test sets were 0.900 (95% CI 0.785-0.986), and 0.929 (95% CI 0.721-0.943), respectively. CONCLUSION: The radiomics model based on high-resolution T2WI and APTw images can predict LN metastasis accurately in patients with RA.

A review of studies on omitting surgery after neoadjuvant chemotherapy in breast cancer.

The advancement in systemic neoadjuvant therapy has significantly increased the pathological complete response (pCR) rate in breast cancer. As surgeries inevitably affect patients physically and psychologically and the accuracy of pCR prediction and diagnosis by minimal invasive biopsy is improving, the necessity of surgery in neoadjuvant chemotherapy (NAC) patients who achieve pCR is under debate. Thus, we conducted a literature review of studies on the selective omission of breast surgery after NAC for breast cancer patients. We summarized the existing predictive models and technologies to predict and diagnose pCR after NAC. Our research indicates that, for nearly half a century, the extent of surgery on both breast and axillary lymph nodes is decreasing, while more precise systematic treatments are increasing. NAC has advanced significantly and its pCR rates have improved, so surgery may be omitted in certain patients. However, accurately predicting pCR after NAC is still a challenge. We also described the design for a randomized clinical trial and the potential problems of omitting surgical treatment after NAC. In summary, the decrease in breast cancer surgery is an unavoidable trend, and more high-quality clinical trials need to be conducted.

Construction of immunotherapy-related prognostic gene signature and small molecule drug prediction for cutaneous melanoma.

Background: Cutaneous melanoma (CM), a kind of skin cancer with a high rate of advanced mortality, exhibits a wide variety of driver and transmitter gene alterations in the immunological tumor microenvironment (TME) associated with tumor cell survival and proliferation. Methods: We analyzed the immunological infiltration of TME cells in normal and malignant tissues using 469 CM and 556 normal skin samples. We used a single sample gene set enrichment assay (ssGSEA) to quantify the relative abundance of 28 cells, then used the LASSO COX regression model to develop a riskScore prognostic model, followed by a small molecule drug screening and molecular docking validation, which was then validated using qRT-PCR and IHC. Results: We developed a prognosis model around seven essential protective genes for the first time, dramatically elevated in tumor tissues, as did immune cell infiltration. Multivariate Cox regression results indicated that riskScore is an independent and robust prognostic indicator, and its predictive value in immunotherapy was verified. Additionally, we identified Gabapentin as a possible small molecule therapeutic for CM. Conclusions: A riskScore model was developed in this work to analyze patient prognosis, TME cell infiltration features, and treatment responsiveness. The development of this model not only aids in predicting patient response to immunotherapy but also has significant implications for the development of novel immunotherapeutic agents and the promotion of tailored treatment regimens.

The Multi-Omics Landscape and Clinical Relevance of the Immunological Signature of Phagocytosis Regulators: Implications for Risk Classification and Frontline Therapies in Skin Cutaneous Melanoma.

Tumor-associated macrophages (TAMs) have gained considerable attention as therapeutic targets. Monoclonal antibody treatments directed against tumor antigens contribute significantly to cancer cell clearance by activating macrophages to phagocytose tumor cells. Due to its complicated genetic and molecular pathways, skin cutaneous melanoma (SKCM) has not yet attained the expected clinical efficacy and prognosis when compared to other skin cancers. Therefore, we chose TAMs as an entrance point. This study aimed to thoroughly assess the dysregulation and regulatory role of phagocytosis regulators in SKCM, as well as to understand their regulatory patterns in SKCM. This study subtyped prognosis-related phagocytosis regulators to investigate prognostic differences between subtypes. Then, we screened prognostic factors and constructed phagocytosis-related scoring models for survival prediction using differentially expressed genes (DEGs) between subtypes. Additionally, we investigated alternative treatment options using chemotherapeutic drug response data and clinical cohort treatment data. We first characterized and generalized phagocytosis regulators in SKCM and extensively examined the tumor immune cell infiltration. We created two phagocytosis regulator-related system (PRRS) phenotypes and derived PRRS scores using a principal component analysis (PCA) technique. We discovered that subtypes with low PRRS scores had a poor prognosis and decreased immune checkpoint-associated gene expression levels. We observed significant therapeutic and clinical improvements in patients with higher PRRS scores. Our findings imply that the PRRS scoring system can be employed as an independent and robust prognostic biomarker, serving as a critical reference point for developing novel immunotherapeutic methods.

Mechanistic Insights Into Trehalose-Mediated Cold Stress Tolerance in Rapeseed (Brassica napus L.) Seedlings.

Cold stress (CS) severely affects several physiological, biochemical, and molecular mechanisms and limits the growth and production of rapeseed (Brassica napus L.). Trehalose (Tre) acts as a growth modulator, which is extensively used to improve the tolerance to multiple plant stresses. Further, Tre also serves as an external force in inducing plant signaling molecules, regulating the expression of stress-responsive genes, and enhancing the CS tolerance in plants. Nevertheless, the importance of exogenous Tre in improving the CS tolerance in rapeseed is still unclear. Therefore, the current study was designed to get mechanistic insights into Tre-mediated CS tolerance in rapeseed seedlings. To explore the Tre role, we designed four treatments [control (CK), CK + 20 mM L-1 Tre, Cold, and Cold + 20 mM L-1 Tre] and three CS conditions (4, 0, and -4°C). The results showed that Tre treatments significantly mitigated the adverse effects of CS on the seedlings and increased the survival rate of Tre-treated seedlings under CS conditions. The exogenous Tre dramatically increased the contents of osmoprotectants, including the soluble sugar (SS), soluble protein (SP), and proline (Pro), and the activities of antioxidant enzymes, such as catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), and ascorbate peroxidase (APX) were also increased under CS conditions. Additionally, Tre decreased the malondialdehyde (MDA) contents to protect the rapeseed seedlings. Moreover, Tre also remarkably augmented the expression levels of antioxidant genes (CAT12, POD34, and FSD7), CS-responsive marker genes (CBF1, CBF2, CBF4, COR6.6, COR15, COR25, COL1, and KIN1), and Tre-biosynthesis genes (TPS4, TPS8, and TPS9). Briefly, exogenous Tre not only regulates the antioxidant and osmotic balance, but it also significantly participates in Tre metabolism and signaling network to improve the CS tolerance in rapeseed. Thus, Tre-induced supervisory connections between physiological or/and biochemical attributes provide information to dissect the mechanisms of Tre-mediated CS tolerance.

A Bayesian Network Meta-Analysis of Complications Related to Breast Reconstruction Using Different Skin Flaps After Breast Cancer Surgery.

BACKGROUND AND OBJECTIVES: As the incidence of breast cancer rises, the number of mastectomy surgeries surges, so does the importance of postoperative breast reconstruction. The implementation of autologous flap restoration methods is becoming prevalent, although which is the best flap remains controversial. As a result, we performed a Bayesian network meta-analysis to compare the eight most common flap in the reconstruction processor of breast cancer surgery. Our findings may help surgeons decide which skin flaps to use for breast reconstruction. METHODS: We searched PubMed, Medline, Embase, and the Cochrane library for relevant literature. For our Bayesian network meta-analysis, we scrutinized 37 papers and evaluated the postoperative complications of eight commonly used breast reconstruction procedures. We also registered this study on PROSPERO, with the number CRD42021251989. RESULTS: A total of 21,184 patients were included in this Bayesian network meta-analysis from 37 different studies. The results demonstrate that TRAM flaps are more prone to complications such as hernias in the abdominal wall and blood flow problems. Hematoma and seroma are more likely to follow LDP flaps. Combining LDP flaps with a prosthetic or autologous adipose tissue does not enhance the risk of postoperative problems appreciably. Fat liquefaction are relatively common in DIEP. CONCLUSIONS: After breast reconstruction, several skin flaps can be employed as clinical choices. TRAM flaps are not recommended for patients with a weak abdominal wall structure, although LDP flaps or SIEA flaps can be considered instead. We do not advocate LDP flaps for patients who have had breast surgery because of the higher risk of hematoma or seroma, but DIEP flaps or LAP flaps can be utilized instead. We do not propose DIEP flaps for individuals who are at a higher risk of postoperative fat liquefaction, but LDP flaps or SIEA flaps can be used instead. However, this Bayesian network meta-analysis has limitations, and further randomized controlled trials are needed to confirm its findings. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.

BACKGROUND: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and risk prediction models for prioritizing genetic testing among breast cancer patients do not meet the demands of clinical practice due to insufficient accuracy. METHODS: The study population comprised 3041 breast cancer patients enrolled from seven hospitals between October 2017 and 11 August 2019, who underwent germline genetic testing of 50 cancer predisposition genes (CPGs). Associations among GPVs in different CPGs and endophenotypes were evaluated using a case-control analysis. A phenotype-based GPV risk prediction model named DNA-repair Associated Breast Cancer (DrABC) was developed based on hierarchical neural network architecture and validated in an independent multicenter cohort. The predictive performance of DrABC was compared with currently used models including BRCAPRO, BOADICEA, Myriad, PENN II, and the NCCN criteria. RESULTS: In total, 332 (11.3%) patients harbored GPVs in CPGs, including 134 (4.6%) in BRCA2, 131 (4.5%) in BRCA1, 33 (1.1%) in PALB2, and 37 (1.3%) in other CPGs. GPVs in CPGs were associated with distinct endophenotypes including the age at diagnosis, cancer history, family cancer history, and pathological characteristics. We developed a DrABC model to predict the risk of GPV carrier status in BRCA1/2 and other important CPGs. In predicting GPVs in BRCA1/2, the performance of DrABC (AUC = 0.79 [95% CI, 0.74-0.85], sensitivity = 82.1%, specificity = 63.1% in the independent validation cohort) was better than that of previous models (AUC range = 0.57-0.70). In predicting GPVs in any CPG, DrABC (AUC = 0.74 [95% CI, 0.69-0.79], sensitivity = 83.8%, specificity = 51.3% in the independent validation cohort) was also superior to previous models in their current versions (AUC range = 0.55-0.65). After training these previous models with the Chinese-specific dataset, DrABC still outperformed all other methods except for BOADICEA, which was the only previous model with the inclusion of pathological features. The DrABC model also showed higher sensitivity and specificity than the NCCN criteria in the multi-center validation cohort (83.8% and 51.3% vs. 78.8% and 31.2%, respectively, in predicting GPVs in any CPG). The DrABC model implementation is available online at http://gifts.bio-data.cn/ . CONCLUSIONS: By considering the distinct endophenotypes associated with different CPGs in breast cancer patients, a phenotype-driven prediction model based on hierarchical neural network architecture was created for identification of hereditary breast cancer. The model achieved superior performance in identifying GPV carriers among Chinese breast cancer patients.

Theoretical insights into volatile iodine adsorption onto COF-DL229.

COF-DL229 is one of the promising sorbents for the capture of volatile radioiodine due to its large adsorption capacity. However, the interaction mechanism between them remains unclear. In the present work, the adsorption of volatile iodine onto COF-DL229 was systematically investigated using periodic density functional theory and crystal orbital Hamilton population calculations. The "soft" characters of COF-DL229 have been theoretically demonstrated. Furthermore, the adsorption energies are extremely large (-8.38 to -9.26 eV), which mainly originate from the framework deformation energies, accounting for 90% at least. The I2 interacts with the skeleton mainly through the N atoms of the imine linkers or the C atoms of the phenyl rings. And, the I-N bond is the strongest bond among all the potential secondary bonds formed between the skeleton and I2. The electrons could be transferred from the skeletons to the iodine atoms and from the near iodine atom to the far one. It is also found that the energy gap becomes narrow after iodine adsorption and the skeletons mainly interact with the bonding orbital σp of I2. The present work could provide reasonable theoretical explanations to the corresponding experimental investigations and contribute to the design and screening of better sorbents for the capture of volatile radioiodine.