Prioritizing prognostic-associated subpopulations and individualized recurrence risk signatures from single-cell transcriptomes of colorectal cancer.

Colorectal cancer (CRC) is one of the most common gastrointestinal malignancies. There are few recurrence risk signatures for CRC patients. Single-cell RNA-sequencing (scRNA-seq) provides a high-resolution platform for prognostic signature detection. However, scRNA-seq is not practical in large cohorts due to its high cost and most single-cell experiments lack clinical phenotype information. Few studies have been reported to use external bulk transcriptome with survival time to guide the detection of key cell subtypes in scRNA-seq data. We proposed scRankXMBD, a computational framework to prioritize prognostic-associated cell subpopulations based on within-cell relative expression orderings of gene pairs from single-cell transcriptomes. scRankXMBD achieves higher precision and concordance compared with five existing methods. Moreover, we developed single-cell gene pair signatures to predict recurrence risk for patients individually. Our work facilitates the application of the rank-based method in scRNA-seq data for prognostic biomarker discovery and precision oncology. scRankXMBD is available at https://github.com/xmuyulab/scRank-XMBD. (XMBD:Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.).

Union With Recursive Feature Elimination: A Feature Selection Framework to Improve the Classification Performance of Multicategory Causes of Death in Colorectal Cancer.

Despite the use of machine learning tools, it is challenging to properly model cause-specific deaths in colorectal cancer (CRC) patients and choose appropriate treatments. Here, we propose an interesting feature selection framework, namely union with recursive feature elimination (U-RFE), to select the union feature sets that are crucial in CRC progression-specific mortality using The Cancer Genome Atlas (TCGA) dataset. Based on the union feature sets, we compared the performance of 5 classification algorithms, including logistic regression (LR), support vector machines (SVM), random forest (RF), eXtreme gradient boosting (XGBoost), and Stacking, to identify the best model for classifying 4-category deaths. In the first stage of U-RFE, LR, SVM, and RF were used as base estimators to obtain subsets containing the same number of features but not exactly the same specific features. Union analysis of the subsets was then performed to determine the final union feature set, effectively combining the advantages of different algorithms. We found that the U-RFE framework could improve various models' performance. Stacking outperformed LR, SVM, RF, and XGBoost in most scenarios. When the target feature number of the RFE was set to 50 and the union feature set contained 298 deterministic features, the Stacking model achieved F1_weighted, Recall_weighted, Precision_weighted, Accuracy, and Matthews correlation coefficient of 0.851, 0.864, 0.854, 0.864, and 0.717, respectively. The performance of the minority categories was also significantly improved. Therefore, this recursive feature elimination-based approach of feature selection improves performances of classifying CRC deaths using clinical and omics data or those using other data with high feature redundancy and imbalance.

Clinical outcomes of coronavirus disease in patients with breast cancer treated with granulocyte colony-stimulating factor following chemotherapy: Triangulation of evidence using population-based cohort and Mendelian randomization analyses.

Recombinant human granulocyte colony-stimulating factor (G-CSF) administration in patients with cancer and coronavirus disease (COVID-19) remains controversial. Concerns exist that it may worsen COVID-19 outcomes by triggering an inflammatory cytokine storm, despite its common use for managing chemotherapy-induced neutropenia (CIN) or febrile neutropenia post-chemotherapy. Here, we determined whether prophylactic or therapeutic G-CSF administration following chemotherapy exacerbates COVID-19 progression to severe/critical conditions in breast cancer patients with COVID-19. Between December 2022 and February 2023, all 503 enrolled breast cancer patients had concurrent COVID-19 and received G-CSF post-chemotherapy, with most being vaccinated pre-chemotherapy. We prospectively observed COVID-19-related adverse outcomes, conducted association analyses, and subsequently performed Mendelian randomization (MR) analyses to validate the causal effect of genetically predicted G-CSF or its associated granulocyte traits on COVID-19 adverse outcomes. Only 0.99% (5/503) of breast cancer patients experienced COVID-19-related hospitalization following prophylactic or therapeutic G-CSF administration after chemotherapy. No mortality or progression to severe/critical COVID-19 occurred after G-CSF administration. Notably, no significant associations were observed between the application, dosage, or response to G-CSF and COVID-19-related hospitalization (all p >.05). Similarly, the MR analyses showed no evidence of causality of genetically predicted G-CSF or related granulocyte traits on COVID-19-related hospitalization or COVID-19 severity (all p >.05). There is insufficient evidence to substantiate the notion that the prophylactic or therapeutic administration of G-CSF after chemotherapy for managing CIN in patients with breast cancer and COVID-19 would worsen COVID-19 outcomes, leading to severe or critical conditions, or even death, especially considering the context of COVID-19 vaccination.

Comparative efficacy and safety of extended adjuvant endocrine therapy for hormone receptor-positive early breast cancer: a Bayesian network meta-analysis.

PURPOSE: Optimal extended adjuvant endocrine therapy (ET) duration and strategy for hormone receptor-positive (HR +) early breast cancer remain unclear. In this network meta-analysis (NMA), the efficacy and safety of all available extended adjuvant ETs were compared and ranked. METHODS: PubMed, Embase, and Cochrane Library and abstracts presented at ASCO, SABCS, and ESMO were searched on March 5, 2022. Fourteen randomized controlled trials (RCTs) comprising eight extended adjuvant ETs for HR + breast cancer and 38,070 patients were analyzed. Main outcomes were disease-free survival (DFS), overall survival (OS), grade ≥ 3 adverse events (AEs), and contralateral breast cancer (CBC). Direct and indirect comparisons were integrated via Bayesian NMA. Hierarchical cluster analysis was performed to jointly rank efficacy and safety outcomes. RESULTS: Compared with that of 5 year ET, extended 10 year aromatase inhibitor (AI) treatment provided the greatest DFS benefit (HR = 0.45, 95%CrI 0.23-0.83), whereas no strategy differed significantly in terms of the other main outcomes. Extended 10 year AI treatment was the preferred strategy for DFS improvement and CBC prevention (surface under the cumulative ranking curve: 93.51% and 91.29% probability, respectively). All strategies had comparable safeties (grade ≥ 3 AEs). Compared with that of 5 year ET, 10 year extended AI significantly increased arthralgia (OR = 1.65, 95%CrI 1.02-2.93) and osteoporosis (OR = 3.33, 95%CrI 1.19-9.68). CONCLUSION: Extended 10 year AI therapy may be optimal for HR + early breast cancer given its relatively high efficacy and safety.

Application of individualized differential expression analysis in human cancer proteome.

Liquid chromatography-mass spectrometry-based quantitative proteomics can measure the expression of thousands of proteins from biological samples and has been increasingly applied in cancer research. Identifying differentially expressed proteins (DEPs) between tumors and normal controls is commonly used to investigate carcinogenesis mechanisms. While differential expression analysis (DEA) at an individual level is desired to identify patient-specific molecular defects for better patient stratification, most statistical DEP analysis methods only identify deregulated proteins at the population level. To date, robust individualized DEA algorithms have been proposed for ribonucleic acid data, but their performance on proteomics data is underexplored. Herein, we performed a systematic evaluation on five individualized DEA algorithms for proteins on cancer proteomic datasets from seven cancer types. Results show that the within-sample relative expression orderings (REOs) of protein pairs in normal tissues were highly stable, providing the basis for individualized DEA for proteins using REOs. Moreover, individualized DEA algorithms achieve higher precision in detecting sample-specific deregulated proteins than population-level methods. To facilitate the utilization of individualized DEA algorithms in proteomics for prognostic biomarker discovery and personalized medicine, we provide Individualized DEP Analysis IDEPAXMBD (XMBD: Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.) (https://github.com/xmuyulab/IDEPA-XMBD), which is a user-friendly and open-source Python toolkit that integrates individualized DEA algorithms for DEP-associated deregulation pattern recognition.

Linearization of wavelength sweeping lasers for the construction of 4-D FMCW LiDAR images of slow-moving objects using baseband beat note signals.

A FMCW LiDAR system of both the distributed feedback laser and external cavity laser is established in baseband beat notes, rather than up-conversion to an intermediate frequency to exclude flicker noise. Meanwhile, utilizing fast-scanning MEMS mirrors, high-quality real-time (1 fps) 4-D images of the slow-moving object (10 mm/s) can be directly constructed at the baseband with a central frequency as low as 100 kHz and a small Doppler shift. The proposed LiDAR architecture based on such a low-frequency baseband significantly improves the optical power budget on the transmitter side and eliminates the costly high-speed sampling circuits on the receiver side.

Healthy lifestyles, systemic inflammation and breast cancer risk: a mediation analysis.

BACKGROUND: Despite the known association between healthy lifestyles and reduced risk of breast cancer, it remains unclear whether systemic inflammation, as a consequence of unhealthy lifestyles, may mediate the association. METHODS: A cohort study of 259,435 female participants in the UK Biobank was conducted to estimate hazard ratio (HR) for breast cancer according to 9 inflammation markers using Cox regression models. We further estimated the percentage of total association between healthy lifestyle index (HLI) and breast cancer that is mediated by these inflammation markers. RESULTS: During 2,738,705 person-years of follow-up, 8,889 cases of breast cancer were diagnosed among 259,435 women in the UK Biobank cohort. Higher level of C-reactive protein (CRP), systemic immune-inflammation index (SII), CRP-to-albumin Ratio (CAR), CRP-to-lymphocyte Ratio (CLR), monocyte-to-HDL-c ratio (MHR), and neutrophil-to-HDL-c ratio (NHR) were associated with increased breast cancer risk, while a higher lymphocyte-to-monocyte ratio (LMR) was associated with a lower risk. The inverse association between HLI and breast cancer was weakly mediated by CRP (8.5%), SII (1.71%), CAR (8.66%), CLR (6.91%), MHR (6.27%), and NHR (7.33%). When considering individual lifestyle factors, CRP and CAR each mediated 16.58% and 17.20%, respectively, of the associations between diet score and breast cancer risk, while the proportion mediated for physical activity and breast cancer were 12.13% and 11.48%, respectively. Furthermore, MHR was found to mediate 13.84% and 12.01% of the associations between BMI, waist circumference, and breast cancer. CONCLUSION: The association of HLI and breast cancer is weakly mediated by the level of inflammation, particularly by CRP and CAR. Systemic inflammatory status may be an intermediate in the biological pathway of breast cancer development.

High leukocyte mitochondrial DNA copy number contributes to poor prognosis in breast cancer patients.

BACKGROUND: Compelling evidence has indicated a significant association between leukocyte mitochondrial DNA copy number (mtDNAcn) and prognosis of several malignancies in a cancer-specific manner. However, whether leukocyte mtDNAcn can predict the clinical outcome of breast cancer (BC) patients has not been well investigated. METHODS: The mtDNA copy number of peripheral blood leukocytes from 661 BC patients was measured using a Multiplex AccuCopy™Kit based on a multiplex fluorescence competitive PCR principle. Kaplan-Meier curves and Cox proportional hazards regression model were applied to investigate the association of mtDNAcn with invasive disease-free survival (iDFS), distant disease-free survival (DDFS), breast cancer special survival (BCSS), and overall survival (OS) of patients. The possible mtDNAcn-environment interactions were also evaluated by the Cox proportional hazard regression models. RESULTS: BC patients with higher leukocyte mtDNA-CN exhibited a significantly worse iDFS than those with lower leukocyte mtDNAcn (5-year iDFS: fully-adjusted model: HR = 1.433[95%CI 1.038-1.978], P = 0.028). Interaction analyses showed that mtDNAcn was significantly associated with hormone receptor status (adjusted p for interaction: 5-year BCSS: 0.028, 5-year OS: 0.022), so further analysis was mainly in the HR subgroup. Multivariate Cox regression analysis demonstrated that mtDNAcn was an independent prognostic factor for both BCSS and OS in HR-positive patients (HR+: 5-year BCSS: adjusted HR (aHR) = 2.340[95% CI 1.163-4.708], P = 0.017 and 5-year OS: aHR = 2.446 [95% CI 1.218-4.913], P = 0.011). CONCLUSIONS: For the first time, our study demonstrated that leukocyte mtDNA copy number might influence the outcome of early-stage breast cancer patients depending on intrinsic tumor subtypes in Chinese women.

Relationship Between Weight-Adjusted Waist Index and Osteoporosis in the Senile in the United States from the National Health and Nutrition Examination Survey, 2017-2020.

BACKGROUND: Some studies suggested obesity may be beneficial in preventing bone loss through the negative relationship between body mass index (BMI) and osteoporosis in senile. However, using BMI to measure obesity is unconvincing due to confounding factors such as muscle mass were not taken into account, and few articles have yet taken a better way to evaluate the relationship between obesity and osteoporosis. METHODOLOGY: Using a cross-sectional sample of 1,979 participants aged ≥65 years from the National Health and Nutrition Examination Survey (NHANES) 2017 to 2020, we evaluated the relation of weight-adjusted waist index (WWI) with osteoporosis. WWI was calculated as waist (cm) divided by the square root of body weight (kg). Diagnosis of osteoporosis was described as follows: according to the updated reference for calculating bone mineral density T-Scores, we marked the BMD value as X, using the formula T femoral neck= (X g/cm2-0.888 g/cm2)/0.121 g/cm2, T lumbar spine= (X g/cm2- 1.065 g/cm2)/0.122 g/cm2, and defined those with a final T femoral neck <-0.25. T lumbar spine<-0.25 or patients with previously diagnosed OP in other hospitals as osteoporosis. RESULTS: All the 1,979 participants were between 65 and 80 years, there were 379 (21.1%) with osteoporosis, 608 (30.7%) with WWI exceeding 12 (cm/√kg) (range 8.85-14.14), and 955 (48.3%) women. Furthermore, the relationship between WWI and osteoporosis was nonlinear with a threshold effect point. Odds of OP significantly increased with the increase of WWI (OR 2.33, 95% CI 11.48-3.38, P = 0.0001) at the right side of the threshold point (WWI≥12) according to the threshold effect study. CONCLUSIONS: Found a significant positive relationship between WWI and osteoporosis. Body fat management in the senile may be good to prevent osteoporosis if confirmed by other prospective studies analyzing the longitudinal risk of osteoporosis with obesity.

Effects of antimony stress on growth, structure, enzyme activity and metabolism of Nipponbare rice (Oryza sativa L.) roots.

Some antimony (Sb) contaminated areas are used for rice cultivation in response to economic demands. However, little is known about the effects of Sb stress on the growth and metabolism of rice roots. Thus, a hydroponic experiment was carried out on the growth, root anatomy, enzyme activity, and metabolism of Nipponbare rice (Oryza sativa L. ssp. japonica cv. Nipponbare) under varying levels of Sb (III) stress (0 mg L-1, 10 mg L-1, and 50 mg L-1). With the increase of Sb concentration, rice root length and root fresh weight declined by 67.8 % and 90.5 % for 10 mg L-1 Sb stress and 94.1 % and 98.4 % for 50 mg L-1 Sb stress, respectively. Anatomical analysis of cross-sections of Sb-treated roots showed an increase in cell wall thickness and an increase in the number of cell mitochondria. The 10 mg L-1 and 50 mg L-1 Sb stress increased the activity of enzyme superoxide dismutase (SOD) in root cells by 1.94 and 2.40 times, respectively. Compared to the control, 10 mg L-1 Sb treatment increased the activity of catalase (CAT) and peroxidase (POD), as well as the concentrations of antioxidant glutathione (GSH) in the root by 1.46, 1.38, and 0.52 times, respectively. However, 50 mg L-1 Sb treatment significantly decreased the activity or content of CAT, POD and GSH by 28.1 %, 13.5 % and 28.2 %, respectively. Nontargeted LC/MS-based metabolomics analysis identified 23 and 13 significantly differential metabolites in rice roots exposed to 10 mg L-1 and 50 mg L-1 Sb, respectively, compared to the control. These differential metabolites were involved in four main metabolic pathways including the tricarboxylic acid cycle (TCA cycle), butanoate metabolism, alanine, aspartate and glutamate metabolism, and alpha-linolenic acid metabolism. Taken together, these findings indicate that Sb stress destroys the structure of rice roots, changes the activity of enzymes, and affects the metabolic pathway, thereby reducing the growth of rice roots and leading to toxicity.

Improved false-negative rates using a novel patient selection flowchart in initially biopsy-proven node-positive breast cancer undergoing blue-dye alone guided sentinel lymph node biopsy after neoadjuvant chemotherapy.

PURPOSE: Current trials support the application of sentinel lymph node biopsy (SLNB) in node-positive breast cancer treated with neoadjuvant chemotherapy (NAC) with a lower false-negative rate (FNR) if dual-tracer (radioisotope and blue-dye) is used. However, radioisotopes are not available in many areas of the world. In this study, we evaluated the feasibility and accuracy of SLNB mapped with methylene-blue-dye alone. METHODS: This study enrolled 132 patients with biopsy-proven node-positive breast cancer with a clip placed in the positive node who then received NAC. After chemotherapy and before operation, all patients underwent axillary ultrasound (AUS) assessment and were classified as either negative (AUS-) or positive (AUS +) according to the axillary status. All patients underwent both SLNB and axillary lymph node dissection (ALND). SLNB was mapped with methylene-blue-dye alone. FNRs were evaluated on factors potentially affecting false-negative SLN finding. RESULTS: Using methylene-blue-dye alone, the FNR of SLNB was 9.9%. Post-NAC AUS assessment (p = 0.009) and the number of SLNs retrieved (p = 0.029) showed association with FNRs in multivariate analysis. In AUS- group, FNR was as low as 2.5%. In AUS + group, retrieving ≥ 4 SLNs including the clipped node improved FNR from 17.1% to 4.8%. A flowchart was designed with the combination of post-NAC AUS assessment, retrieved SLN number, and the retrieved of clipped node further improve overall FNR to 3.3%. CONCLUSION: In biopsy-proven node-positive breast cancer treated with NAC, using a flowchart to optimize patient selection reduces the FNR of single-tracer (methylene-blue-dye) guided SLNB.

Identification of LARS as an essential gene for osteosarcoma proliferation through large-Scale CRISPR-Cas9 screening database and experimental verification.

BACKGROUND: Osteosarcoma is one of the most malignant tumors, and it occurs mostly in children and adolescents. Currently, surgery and chemotherapy are the main treatments. The recurrence rate is high and the prognosis is often poor. Finding an effective target gene therapy for osteosarcoma may effectively improve its prognosis. METHOD: In this study, genes essential for the survival of osteosarcoma cells were identified by genome-wide screening of CRISPR-Cas9 based on the DepMap database. The expression of these essential genes in osteosarcoma patients' tissues and normal tissues was identified in the GSE19276 database. Functional pathway enrichment analysis, protein interaction network construction, and LASSO were performed to construct a prognostic risk model based on these essential genes. CCK8 assay was used to detect the effect of essential gene-LARS (Leucyl-TRNA Synthetase 1) on the proliferation of osteosarcoma. RESULTS: In this study, 785 genes critical for osteosarcoma cell proliferation were identified from the DepMap. Among these 785 essential genes, 59 DEGs were identified in osteosarcoma tissues. In the functional enrichment analysis, these 59 essential genes were mainly enriched in cell cycle-related signaling pathways. Furthermore, we established a risk score module, including LARS and DNAJC17, screened from these 59 genes, and this module could divide osteosarcoma patients into the low-risk and high-risk groups. In addition, knockdown of LARS expression inhibited the proliferative ability of osteosarcoma cells. A significant correlation was found between LARS expression and Monocytic lineage, T cells, and Fibroblasts. CONCLUSION: In conclusion, LARS was identified as an essential gene for survival in osteosarcoma based on the DepMap database. Knockdown of LARS expression significantly inhibited the proliferation of osteosarcoma cells, suggesting that it is involved in the formation and development of osteosarcoma. The results are useful as a foundation for further studies to elucidate a potential osteosarcoma diagnostic index and therapeutic targets.

CTPS1 promotes malignant progression of triple-negative breast cancer with transcriptional activation by YBX1.

BACKGROUND: Cytidine nucleotide triphosphate synthase 1 (CTPS1) is a CTP synthase which play critical roles in DNA synthesis. However, its biological regulation and mechanism in triple-negative breast cancer (TNBC) has not been reported yet. METHODS: The expression of CTPS1 in TNBC tissues was determined by GEO, TCGA databases and immunohistochemistry (IHC). The effect of CTPS1 on TNBC cell proliferation, migration, invasion, apoptosis and tumorigenesis were explored in vivo and in vitro. In addition, the transcription factor Y-box binding protein 1 (YBX1) was identified by bioinformatics methods, dual luciferase reporter and chromatin immunoprecipitation (CHIP) assays. Pearson correlation analysis was utilized to assess the association between YBX1 and CTPS1 expression. RESULTS: CTPS1 expression was significantly upregulated in TNBC tissues and cell lines. Higher CTPS1 expression was correlated with a poorer disease-free survival (DFS) and overall survival (OS) in TNBC patients. Silencing of CTPS1 dramatically inhibited the proliferation, migration, invasion ability and induced apoptosis of MDA-MB-231 and HCC1937 cells. Xenograft tumor model also indicated that CTPS1 knockdown remarkably reduced tumor growth in mice. Mechanically, YBX1 could bind to the promoter of CTPS1 to promote its transcription. Furthermore, the expression of YBX1 was positively correlated with CTPS1 in TNBC tissues. Rescue experiments confirmed that the enhanced cell proliferation and invasion ability induced by YBX1 overexpression could be reversed by CTPS1 knockdown. CONCLUSION: Our data demonstrate that YBX1/CTPS1 axis plays an important role in the progression of TNBC. CTPS1 might be a promising prognosis biomarker and potential therapeutic target for patients with triple-negative breast cancer.

Clinical application of artificial neural network (ANN) modeling to predict BRCA1/2 germline deleterious variants in Chinese bilateral primary breast cancer patients.

BACKGROUND: Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic testing could not be carried out for all patients due to extensive use of healthcare resources, which in turn results in high medical costs. To date, existing BRCA1/2 deleterious variants prediction models have been developed in women of European or other descent who are quite genetically different from Asian population. Therefore, there is an urgent clinical need for tools to predict the frequency of BRCA1/2 deleterious variants in Asian BBC patients balancing the increased demand for and cost of cancer genetics services. METHODS: The entire coding region of BRCA1/2 was screened for the presence of germline deleterious variants by the next generation sequencing in 123 Chinese BBC patients. Chi-square test, univariate and multivariate logistic regression were used to assess the relationship between BRCA1/2 germline deleterious variants and clinicopathological characteristics. The R software was utilized to develop artificial neural network (ANN) and nomogram modeling for BRCA1/2 germline deleterious variants prediction. RESULTS: Among 123 BBC patients, we identified a total of 20 deleterious variants in BRCA1 (8; 6.5%) and BRCA2 (12; 9.8%). c.5485del in BRCA1 is novel frameshift deleterious variant. Deleterious variants carriers were younger at first diagnosis (P = 0.0003), with longer interval between two tumors (P = 0.015), at least one medullary carcinoma (P = 0.001), and more likely to be hormone receptor negative (P = 0.006) and HER2 negative (P = 0.001). Area under the receiver operating characteristic curve was 0.903 in ANN and 0.828 in nomogram modeling individually (P = 0.02). CONCLUSION: This study shows the spectrum of the BRCA1/2 germline deleterious variants in Chinese BBC patients and indicates that the ANN can accurately predict BRCA deleterious variants than conventional statistical linear approach, which confirms the BRCA1/2 deleterious variants carriers at the lowest costs without adding any additional examinations.

Assessment of rhizosphere bacterial diversity and composition in a metal hyperaccumulator (Boehmeria nivea) and a nonaccumulator (Artemisia annua) in an antimony mine.

AIMS: Heavy metal hyperaccumulators are widely used in mining restoration due to their ability to accumulate and transport heavy metals, compared to nonaccumulators. Rhizosphere bacteria in metal hyperaccumulators play a key role in the uptake of heavy metals from soil; however, assessments of the differences of rhizosphere bacteria between metal hyperaccumulators and nonaccumulator are scarce. METHODS AND RESULTS: To understand the difference of bacterial composition between hyperaccumulator and nonaccumulator in rhizosphere, the diversity and composition of rhizosphere bacteria in a metal hyperaccumulator (Boehmeria nivea) and a nonaccumulator (Artemisia annua) grown in the same field in Xikuangshan were evaluated using Illumina Miseq high-throughput sequencing technology. Boehmeria nivea and A. annua had 3926 overlapping OTUs, 19,736 and 17,579 unique OTUs, respectively. Boehmeria nivea had lower Chao1 index, Shannon index and Pielou index than A. annua. The dominant phyla and genera of rhizosphere bacteria in B. nivea and A. annua were similar, but some rhizosphere bacterial communities with heavy metal remediation ability mainly appeared in the rhizosphere of the hyperaccumulator. Compared to A. annua, B. nivea showed a significantly higher relative abundance of rhizosphere bacteria, such as Acidobacteria and Bacteroidete at the phylum level and RB41 at the genus level. Some specific rhizosphere bacteria with the ability to bind metal, such as Leifsonia and Kibdelosporangium, were only found in the rhizosphere of B. nivea. CONCLUSION: Results indicated that B. nivea, as a metal hyperaccumulator, has a key function in governing metal-resistant rhizosphere bacteria in response to antimony compound pollution stress. SIGNIFICANCE AND IMPACT OF STUDY: Understanding the diversity of rhizosphere bacteria between hyperaccumulators and nonaccumulators is beneficial to formulate strategies to improve metal uptake efficiency by selecting specific plant species and rhizosphere bacteria grown on polluted soil.

The impact of chemotherapy and survival prediction by machine learning in early Elderly Triple Negative Breast Cancer (eTNBC): a population based study from the SEER database.

PURPOSE: We aimed to analysis the impact of chemotherapy and establish prediction models of prognosis in early elderly triple negative breast cancer (eTNBC) by using machine learning. METHODS: We enrolled 4,696 patients in SEER Database who were 70 years or older, diagnosed with primary early TNBC(larger than 5 mm), from 2010 to 2016. The propensity-score matched method was utilized to reduce covariable imbalance. Univariable and multivariable analyses were used to compare breast cancer-specific survival(BCSS) and overall survival(OS). Nine models were developed by machine learning to predict the 5-year OS and BCSS for patients received chemotherapy. RESULTS: Compared to matched patients in no-chemotherapy group, multivariate analysis showed a better survival in chemotherapy group. Stratified analyses by stage demonstrated that patients with stage II and stage III other than stage I could benefit from chemotherapy. Further investigation in stage II found that chemotherapy was a better prognostic indicator for patients with T2N0M0 and stage IIb, but not in T1N1M0. Patients with grade III could achieve a better survival by receiving chemotherapy, but those with grade I and II couldn't. With 0.75 in 5-year BCSS and 0.81 in 5-year OS for AUC, the LightGBM outperformed other algorithms. CONCLUSION: For early eTNBC patients with stage I, T1N1M0 and grade I-II, chemotherapy couldn't improve survival. Therefore, de-escalation therapy might be appropriate for selected patients. The LightGBM is a trustful model to predict the survival and provide precious systemic treatment for patients received chemotherapy.

Quantitative proteomics reveals stage-specific protein regulation of triple negative breast cancer.

BACKGROUNDS: Triple negative breast cancer (TNBC) is a heterogeneous disease with more aggressive clinical courses than other subtypes of breast cancer. In this study, we performed high-resolution mass spectrometry-based quantitative proteomics with TNBC clinical tissue specimens to explore the early and sensitive diagnostic signatures and potential therapeutic targets for TNBC patients. METHODS: We performed an iTRAQ labeling coupled LC-MS/MS approach to explore the global proteome in tumor tissues and corresponding para-tumor tissues from 24 patients with grade I-II and grade III primary TNBC. Relative peptide quantification and protein identification were performed by Proteome Discoverer™ software with Mascot search engine. Differentially expressed proteins were analyzed by bioinformatic analyses, including GO function classification annotation and KEGG enrichment analysis. Pathway analyses for protein-protein interactions and upstream regulations of differentially expressed candidates were performed by Ingenuity Pathway Analysis (IPA) software. RESULTS: Totally, 5401 unique proteins were identified and quantified in different stage of TNBCs. 845 proteins were changed in patients with grade I or II TNBC, among which 304 were up-regulated and 541 were down-regulated. Meanwhile, for patients with grade III TNBC, 358 proteins were increased and 651 proteins were decreased. Comparing to para-cancerous tissues, various signaling pathways and metabolic processes, including PPAR pathways, PI3K-Akt pathway, one-carbon metabolism, amino acid synthesis, and lipid metabolism were activated in TNBC cancer tissues. Death receptor signaling was significantly activated in grade I-II TNBCs, however, remarkably inhibited in grade III TNBCs. Western blot experiments were conducted to validate expression levels of CYCS, HMGA1 and XIAP with samples from individual patients. CONCLUSIONS: Overall, our proteomic data presented precise quantification of potential signatures, signaling pathways, regulatory networks, and characteristic differences in each clinicopathological subgroup. The proteome provides complementary information for TNBC accurate subtype classification and therapeutic targets research.

Passive anti-sunlight glare traffic signs with non-axisymmetric freeform lens design.

This paper proposes a passive optical brightening element design, a non-axisymmetric freeform lens (NAFL), arranged and assembled on a traditional traffic sign. NAFL is the first optical design which can effectively solve the traffic problem that direct sunlight affects the driver's inability to look directly at the traffic sign. The NAFL can converge the sunlight behind the traffic sign and diverge forward to 150 meters away. In this way, the NAFL array combinations on the traffic sign can directly rely on sunlight as image information pixels. According to the simulation, the optical efficiency of the NAFL can be as high as 81.5%. Besides, the angular tolerance is also analyzed to evaluate the working hours of the NAFL. Finally, we made the prototype and proved that such passive brightening components could effectively improve the traffic sign's visibility in harsh sunlight.

Cyclin-dependent kinase 4 and 6 inhibitors in hormone receptor-positive, human epidermal growth factor receptor-2 negative advanced breast cancer: a meta-analysis of randomized clinical trials.

BACKGROUND: Breakthrough progress has been made in Cyclin-Dependent kinase 4 and 6 (CDK4/6) inhibitors when combined with endocrine therapy (ET) for hormone receptor-positive (HR+), HER2-negative (HER2-) advanced breast cancer (ABC). Though significant improvements of progression-free survival (PFS) for CDK4/6 inhibitors were demonstrated, however, the results of overall survival (OS) profile were not consistent. This study is conducted to further evaluate the efficacy and safety of CDK4/6 inhibitors for HR+ /HER2- ABC, and explore the prefer population through subgroup analysis. METHOD: We identified relevant randomized controlled trials that compared CDK4/6 inhibitors plus ET to ET alone in HR+ /HER2- ABC. We calculated the hazard ratios (HRs) for PFS and OS, and risk ratios (RRs) for objective response rate (ORR), clinical benefit rate (CBR), adverse events (AEs). Statistical analysis was performed with the random-effects model. RESULT: Eight trials and 4580 patients were included in this meta-analysis. Compared to ET alone, CDK4/6 inhibitors plus ET not only produced a significantly longer PFS (HR = 0.55, 95% confidence interval [CI] 0.50-0.59, p < 0.00001), but also manifested an extension of OS (HR = 0.79, 95% CI 0.67-0.93, p = 0.004) for HR+ /HER2- ABC. Similarly, the benefit was also manifested in ORR (RR = 1.47, 95% CI 1.30-1.67, p < 0.00001) and CBR (RR = 1.20, 95% CI 1.12-1.30, p < 0.00001). The improvements of PFS were observed in the combined treatment group as both the first-line (HR = 0.56) and the second-line therapy (HR = 0.53), and irrespective of menopausal status, the presence of visceral metastasis, previous treatment with chemotherapy, their race or age. Nevertheless, more hematologic and gastrointestinal adverse events were observed with CDK4/6 inhibitors. The most common Grade 3-4 AEs is neutropenia (RR 31.95). CONCLUSION: Significant advantages of PFS and OS were observed for CDK4/6 inhibitors in HR+/HER2- ABC. Furthermore, the benefit of PFS was across all subgroups. Though associated with an increased occurrence of AEs, most of which are reversible, manageable, and acceptable. Therefore, CDK4/6 inhibitors could be recommended as a preferred options for patients with HR+ /HER2- ABC.

A novel WO3/graphene composite using poly(ionic liquid) as a linker for enhanced supercapacitive performance.

WO3 has attracted widespread attention as an important semiconductor for supercapacitors. However, applications of WO3 are limited by its poor performance regarding capacitance and conductivity. In this paper, a novel method is presented for preparing a WO3/reduced graphene oxide (RGO) composite, based on poly(ionic liquid) (PIL) as a linker. PIL enables a tight contact between WO3 and graphene to exploit the excellent electrical conductivity of graphene. Results of the morphology for the as-prepared WO3/PIL/RGO composite indicate that the WO3 nanoparticles are distributed uniformly on the surface of the RGO. The WO3/PIL/RGO electrode displays a much higher specific capacitance, 316 F g-1 at 1 A g-1, than that of the pure WO3 electrode. Furthermore, WO3/PIL/RGO also has good rate and long cycling performance for supercapacitors, making it a promising electrode material.