Association between dietary intake of saturated fatty acid subgroups and breast cancer risk.

The impact of dietary saturated fatty acids (SFAs) on breast cancer risk may vary depending on their carbon chain lengths, attributable to the discrepancy in their dietary sources and biological activities. The associations between SFA subgroups classified by chain length and breast cancer risk remain controversial. In this case-control study, we aimed to investigate the association between the dietary intake of SFA subgroups, classified by chain lengths, and odds of breast cancer in China. This study included 1661 cases of breast cancer (confirmed as primary and histologically) and 1674 frequency-matched controls. Face-to-face interviews were used to collect basic information, while dietary intake information was obtained by a food frequency questionnaire. The unconditional logistic regression model was used to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs). All SFA subgroups were inversely associated with odds of breast cancer. The adjusted ORs (95% CIs) were 0.78 (0.61-0.99) for medium-chain SFAs, 0.50 (0.31-0.83) for long even-chain SFAs, 0.69 (0.54-0.88) for long odd-chain, and 0.67 (0.48-0.95) for very long-chain SFAs, respectively. In the restricted cubic spline (RCS) models, a non-linear M-shaped association was observed between long odd-chain SFAs and odds of breast cancer (Pnon-linearity = 0.007). However, the associations of medium-chain SFAs, long even-chain SFAs, and very long-chain SFAs did not reach statistical significance (Pnon-linearity > 0.05). No significant interactions were observed between all these four subgroups of SFAs and menopausal status or BMI. Our findings emphasize the significance of elucidating the associations of dietary SFAs according to chain lengths, providing insights into the etiology as well as the potential benefits of SFA-rich food intake in reducing the risk of breast cancer. Further prospective cohort studies and intervention studies are warranted to confirm these findings and identify the underlying mechanisms of the association between dietary SFAs and breast cancer.

Heritable transcriptional defects from aberrations of nuclear architecture.

Transcriptional heterogeneity due to plasticity of the epigenetic state of chromatin contributes to tumour evolution, metastasis and drug resistance1-3. However, the mechanisms that cause this epigenetic variation are incompletely understood. Here we identify micronuclei and chromosome bridges, aberrations in the nucleus common in cancer4,5, as sources of heritable transcriptional suppression. Using a combination of approaches, including long-term live-cell imaging and same-cell single-cell RNA sequencing (Look-Seq2), we identified reductions in gene expression in chromosomes from micronuclei. With heterogeneous penetrance, these changes in gene expression can be heritable even after the chromosome from the micronucleus has been re-incorporated into a normal daughter cell nucleus. Concomitantly, micronuclear chromosomes acquire aberrant epigenetic chromatin marks. These defects may persist as variably reduced chromatin accessibility and reduced gene expression after clonal expansion from single cells. Persistent transcriptional repression is strongly associated with, and may be explained by, markedly long-lived DNA damage. Epigenetic alterations in transcription may therefore be inherently coupled to chromosomal instability and aberrations in nuclear architecture.

Clinical efficacy of combination therapy of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs in the treatment of novel coronavirus pneumonia: A prospective interventional study.

Introduction: The National Administration of Traditional Chinese Medicine of the People's Republic of China (NATCM) and the State Administration of Traditional Chinese medicine (TCM) advocated a combination therapy of TCM and anti-viral drugs for novel coronavirus pneumonia (NCP) to improve the efficacy of clinical treatment. Methods: Forty-six patients diagnosed with NCP were sequentially divided into intent-to-treat population: the experimental group (combination of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs; n = 23) and the control group (anti-viral drugs only) (n = 23). The two groups were compared in terms of duration of fever, cough symptom score, fatigue, appetite, dyspnea, out-of-bed activities, chest computer tomography (CT) recovery, virological clearance, average length of hospital stay, and clinical effective rate of drug. After 6 days of observation, patients from the control group were divided into as-treated population: experimental subgroup (n = 14) to obtain clinical benefit and control subgroup (n = 9). Results: There was a significant improvement in the duration of fever (1.087 ± 0.288 vs 4.304 ± 2.490), cough (0.437 ± 0.589 vs 2.435 ± 0.662; P < 0.05), chest CT evaluation (82.6% vs 43.4%; P < 0.05), and virological clearance (60.8% vs 8.7%; P < 0.05) in patients of the experimental group compared with patients in the control group. Further observation in as-treated population reported that cough (0.742 ± 0.463 vs 1.862 ± 0.347; P < 0.05) and fatigue (78.5% vs 33.3%; P < 0.05) were significantly relieved after adding FuXi-Tiandi-Wuxing Decoction to the existing treatment. Conclusion: An early treatment with combination therapy of FuXi-Tiandi-Wuxing Decoction and anti-viral drugs significantly relieves the clinical symptoms of NCP, shows improvement in chest CT scan, improves virological clearance, shortens average length of hospital stay, and reduces the risk of severe illness. The effect of FuXi-Tiandi-Wuxing Decoction in NCP may be clinically important and require further consideration.

Exploring interpretable graph convolutional networks for autism spectrum disorder diagnosis.

PURPOSE: Finding the biomarkers associated with autism spectrum disorder (ASD) is helpful for understanding the underlying roots of the disorder and can lead to earlier diagnosis and more targeted treatments. In essence, we are faced with two challenges (i) how to learn a node representation and a clean graph structure from original graph data with high dimensionality and (ii) how to jointly model the procedure of node representation learning, structure learning and graph classification. METHODS: We propose FSL-BrainNet, an interpretable graph convolution network (GCN) model for jointly Learning of node Features and clean Structures in brain networks for automatic brain network classification and interpretation. We formulate an end-to-end trainable and interpretable framework for graph classification and biomarkers (salient brain regions and potential subnetworks) identification. RESULTS: The experimental results on the ABIDE dataset show that our proposed methods not only achieve improved prediction performance compared with the state-of-the-art methods, but also find a compact set of highly suggestive biomarkers including relevant brain regions and subnetworks to ASD. CONCLUSION: Through node feature learning and structure learning, our model can simultaneously select important brain regions and identify subnetworks.

Efficient exosome subpopulation isolation and proteomic profiling using a Sub-ExoProfile chip towards cancer diagnosis and treatment.

Exosomes have been extensively studied as liquid biopsy biomarkers in the past decade. However, the origin and molecular heterogeneity of exosomes hinder the research development moving from proof-of-concept to clinical applications. Herein, we report an integrated microfluidic platform termed Sub-ExoProfile chip, to achieve the selective isolation and subsequent proteomic profiling of multiplex exosome subpopulations simultaneously. The Sub-ExoProfile chip comprises three cylindrical self-assembled nanopillars, on which specific exosome capture antibodies (CD81, EpCAM, HER2) were immobilized to capture and sort different exosome subpopulations. It is worth noting that the 3D porous nanopillars afford enhanced interface binding efficiency; thus, a tumor-specific exosome subpopulation with lowly-expressed surface marker was still isolated with satisfactory capture efficiency. Moreover, the amphiphilic mesoporous silica nanoparticle self-assembled nanopillars also served as a nanoreactor for the enrichment and in situ digestion of exosomal proteins, providing improved performance for the mass-spectrometry based molecular characterization of exosome subpopulations. The Sub-ExoProfile chip was investigated on standard exosome samples from different breast cancer cell lines. The isolation and quantitative detection of exosome subpopulations were in line with the molecular subtype of breast cancer cell lines, and the molecular makeup was confirmed using classic microplate ELISA. Clinical samples from HER2-positive and triple-negative breast cancer patients were also examined using the Sub-ExoProfile chip. The quantitative results of three exosome subpopulations distinguished the three subtypes of breast cancer significantly. Most importantly, the molecular characterization of three exosome subpopulations revealed that the distinct exosome subpopulation participated in a different signaling pathway and performed distinct biological functions. It is envisioned that the analysis of the exosome subpopulation on the Sub-ExoProfile chip will facilitate the screening of tumor-specific exosomal biomarkers and open a new avenue for exosome-based liquid biopsy.

Factors predicting the occurrence of net adverse clinical and cerebral events in patients with acute coronary syndrome treated with clopidogrel or ticagrelor in combination with aspirin: a real-world study.

Background: This study aimed to establish the factors influencing the clinical benefits of ticagrelor and clopidogrel for acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) surgery. Methods: A multicenter, retrospective, real-world study was conducted on patients with ACS whose data were sourced from 3 databases, namely the BRIC-ACS(I) study, COSTIC study, and 301 Hospital PCI patient database from January 2014 to October 2017. The primary endpoint was net adverse clinical and cerebral events (NACCE). Results: A total of 7,236 ACS patients were included, of which 4,444 patients (61.4%) and 2,792 patients (38.6%) were in the clopidogrel dual antiplatelet therapy (DAPT) group and ticagrelor DAPT group, respectively. The hazard ratio (HR) for NACCE was significantly higher in patients aged ≥65 years than those aged ≤65 years in the clopidogrel DAPT group (HR: 2.15, 95% CI: 1.68-2.76) and ticagrelor DAPT group (HR: 1.75, 95% CI: 1.34-2.29). In patients treated with clopidogrel DAPT, patients with unstable angina had a significantly lower HR for NACCE than patients with ST-elevation myocardial infarction. Use of beta blockers (HR: 0.77, 95% CI: 0.60-0.99) was an influencing factor in patients treated with clopidogrel DAPT, whereas in patients treated with ticagrelor DAPT, only smoking status (HR: 0.75, 95% CI: 0.57-0.99) was a significant influencing factor. Conclusions: Age, hypertension status, and presence or absence of unstable angina were factors influencing the composite outcome of NACCE. The selection of patients to be treated with either clopidogrel DAPT or ticagrelor DAPT depending on the presence or absence of factors influencing treatment outcome may improve therapeutic management.

Modelled Economic Analysis for Dacomitinib-A Cost Effectiveness Analysis in Treating Patients With EGFR-Mutation-Positive Non-Small Cell Lung Cancer in China.

OBJECTIVES: To establish the cost-effectiveness of dacomitinib compared to gefitinib from the Chinese healthcare system perspective. PATIENTS: Advanced non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. METHODS: Partitioned survival analysis was undertaken to examine the cost-effectiveness of dacomitinib utilising individual patient data (IPD) from the pivotal randomised controlled trial (RCT) (ARCHER 1050). The three health states modelled were progression-free, post-progression, and death. Parametric survival distributions were fitted to IPD against the Kaplan-Meier survival curves corresponding to progression-free survival (PFS) and overall survival (OS) outcomes by randomised groups. Costs included drug acquisition and administration, outpatient management (outpatient consultation and examinations), and best supportive care costs. Utility weights were sourced from the pivotal trial and other published literature. The incremental cost-effectiveness ratio (ICER) was calculated with costs and quality-adjusted life years (QALYs) discounted at an annual rate of 5%. Both deterministic and probabilistic sensitivity analyses were undertaken. RESULTS: In the base case, dacomitinib (CNY 265,512 and 1.95 QALY) was associated with higher costs and QALY gains compared to gefitinib (CNY 247,048 and 1.61 QALYs), resulting in an ICER of CNY 58,947/QALY. Using the empirical WTP/QALY threshold, dacomitinib is a cost-effective treatment strategy for patients with EGFR-mutation-positive advanced NSCLC. The probabilistic sensitivity analysis suggested that dacomitinib had a 97% probability of being cost-effective. CONCLUSIONS: Dacomitinib is a cost-effective treatment strategy in treating patients with EGFR-mutation-positive NSCLC from the Chinese healthcare system perspective. The uncertainty around the cost-effectiveness of dacomitinib could be reduced if long-term survival data become available. CLINICAL TRIAL REGISTRATION: NCT01024413.

MSDS-UNet: A multi-scale deeply supervised 3D U-Net for automatic segmentation of lung tumor in CT.

Lung cancer is one of the most common and deadly malignant cancers. Accurate lung tumor segmentation from CT is therefore very important for correct diagnosis and treatment planning. The automated lung tumor segmentation is challenging due to the high variance in appearance and shape of the targeting tumors. To overcome the challenge, we present an effective 3D U-Net equipped with ResNet architecture and a two-pathway deep supervision mechanism to increase the network's capacity for learning richer representations of lung tumors from global and local perspectives. Extensive experiments on two real medical datasets: the lung CT dataset from Liaoning Cancer Hospital in China with 220 cases and the public dataset of TCIA with 422 cases. Our experiments demonstrate that our model achieves an average dice score (0.675), sensitivity (0.731) and F1-score (0.682) on the dataset from Liaoning Cancer Hospital, and an average dice score (0.691), sensitivity (0.746) and F1-score (0.724) on the TCIA dataset, respectively. The results demonstrate that the proposed 3D MSDS-UNet outperforms the state-of-the-art segmentation models for segmenting all scales of tumors, especially for small tumors. Moreover, we evaluated our proposed MSDS-UNet on another challenging volumetric medical image segmentation task: COVID-19 lung infection segmentation, which shows consistent improvement in the segmentation performance.

Crizotinib versus chemotherapy: a real-world cost-effectiveness study in China.

Aim: To assess the cost-effectiveness of crizotinib verses platinum-based doublet chemotherapy as the first-line treatment for anaplastic lymphoma kinase (ALK)-positive non-small-cell lung cancer (NSCLC) in the real-world setting. Methods: Data from 163 advanced ALK positive NSCLC patients were collected from West China Hospital, Sichuan University (Chengdu, China). They were categorized into two groups as treated with crizotinib (n = 83) or chemotherapy (n = 80) as a first-line therapy. The progression-free survival (PFS) as the primary clinical outcome, and the direct medical costs were collected from hospital information systems. Incremental cost-effectiveness ratio (ICER) was calculated with costs, quality-adjusted life-years, as well as the costs discounted at 3% annually. Additionally, two different kinds of medical insurance (MI) for pharma-economic assessment were considered. Results: Crizotinib improved PFS versus chemotherapy in ALK positive patients (median PFS 19.67 m vs 5.47 m; p < 0.001). Moreover, crizotinib obtained an ICER of US$36,285.39 before the end of 2016, when crizotinib, pemetrexed and anti-angiogenesis drugs were not MI covered. This is more than the willingness to pay threshold (three-times of gross domestic product per capita in mainland China or Sichuan Province). However, ICER was US$7321.16, which is less than willingness to pay, when crizotinib and all chemotherapy drugs were covered by MI from the end of 2016. Sensitivity analysis demonstrated a 99.7% probability for crizotinib to be more cost-effective than chemotherapy, when crizotinib and all anticancer drugs were MI covered. One-way sensitivity analysis for the reimbursement ratio of crizotinib indicated that cost-effective tendency for crizotinib increased as reimbursement ratio increased. Conclusion: Crizotinib could be an effective, and cost-effective first-line treatment for ALK positive advanced NSCLC with the MI coverage currently available in Chengdu, Sichuan Province, China.

A rapid and efficient method for N-termini analysis in short-lived proteins.

A rapid and efficient method to isolate global N-termini is presented. Utilizing laser-assisted proteolysis and Fe3O4 microsphere, protein N-termini could be isolated in 4 h. The amino-blocked protein was digested by trypsin assisted by laser radiation, shortening the digest time from overnight to 40 s. Non-N-terminal peptides were characterized by a tryptic free amino in their N-term, which could be derived with sulfhydryl by traut' s reagent efficiently and then coupled with Fe3O4 microspheres nearly completely in less than 4 h. The rapid method was beneficial for the identification of unstable N-termini in short-lived proteins. Human serum albumin was studied as a model. The N-terminus was successfully isolated from the digest within 4 h. Also, 2011 N-terminal peptides out of 936 proteins in mouse liver proteome sample were identified using liquid chromatography-tandem mass spectrometer (LC-MS/MS). This method was demonstrated as a facile and efficient N-termini enrichment method for targeted protein N-termini analysis, especially those with short half-life.

Highly efficient and selective enrichment of glycopeptides using easily synthesized magG/PDA/Au/l-Cys composites.

Highly selective and efficient enrichment of glycopeptides from complex biological samples is necessary. In this study, novel zwitterionic hydrophilic polydopamine-coated magnetic graphene composites (magG/PDA/Au/l-Cys) were synthesized and applied to the enrichment of glycopeptides. The size, morphology, and composition of magG/PDA/Au/l-Cys composites were investigated by transmission electron microscopy, scanning electron microscopy, FT-infrared spectroscopy, and X-ray diffraction. The composites possessed a number of desirable characteristics, including good biocompatibility easy separation property and excellent hydrophilicity. By virtue of the features contributed by different ingredients, the prepared composites demonstrated superior performance for glycopeptide enrichment with high sensitivity (0.1 fmol), efficiency, selectivity (1:100), and repeatability (at least ten times). In addition, the composites were successfully applied to the enrichment of glycopeptides from human serum and 40 unique N-glycosylation peptides from 31 different N-linked glycoproteins were identified. The superior hydrophilic material is of great potential for the analysis of glycoproteins.

A novel method to isolate protein N-terminal peptides from proteome samples using sulfydryl tagging and gold-nanoparticle-based depletion.

A novel method to isolate global N-termini using sulfydryl tagging and gold-nanoparticle-based depletion (STagAu method) is presented. The N-terminal and lysine amino groups were first completely dimethylated at the protein level, after which the proteins were digested. The newly generated internal peptides were tagged with sulfydryl by Traut's reagent through digested N-terminal amines in yields of 96%. The resulting sulfydryl peptides were depleted through binding onto nano gold composite materials. The Au-S bond is stable and widely used in materials science. Nano gold composite materials showed nearly complete depletion of sulfydryl peptides. A set of the acetylated and dimethylated N-terminal peptides were analyzed by liquid chromatography-tandem mass spectrometry. This method was demonstrated to be an efficient N-terminus enrichment method because of the use of an effective derivatization reaction, in combination with robust and relative easy to implement Au-S coupling. We identified 632 N-terminal peptides from 386 proteins in a mouse liver sample. The STagAu approach presented is therefore a facile and efficient method for mass-spectrometry-based analysis of proteome N-termini or protease-generated cleavage products.

Isolation of acetylated and free N-terminal peptides from proteomic samples based on tresyl-functionalized microspheres.

Analysis of protein N-termini is of great importance in helping to figure out important posttranslational modifications (PTMs) occurred in N-termini. Those PTMs include initial methionine removal, proteolytic cleavage, peptide signal processing, or N-terminal acetylation, which are usually neglected by conventional shotgun proteomics strategies. Herein, we develop a protein N-terminal peptides enrichment method based on commercial tresyl-functionalized microspheres (TFM). TFM could specifically immobilize the non-N-terminal peptides (internal peptides) from the supernatant. We demonstrated the isolation by TFM was more fast and efficient than formyl or epoxy-functionalized microspheres. Furthermore, this method could simultaneously isolate not only naturally free but acetylated blocked N-terminus. That facilitates a more comprehensive acquisition of N-terminus. After being verified by three standard proteins, cytochrome C, ribonuclease B and bovine serum albumin, this method was applied to mouse liver protein sample. We identified 122 naturally acetylated N-terminus and 107 free N-terminus in the sample. With the good performance of TFM, this method is efficient and useful for N-termini recovery.