Young age (≤40 years) use to be considered an independent risk factor for the prognosis of women with early-stage breast cancer. We conducted a retrospective analysis to investigate this claim in a population of young patients who were stratified by molecular subtype. We identified 2,125 women with stage I to III breast cancer from the Fujian Medical University Union Hospital. Multivariable Cox proportional hazards models were used to analyze the relationship between age groups stratified by molecular subtype and 5-year disease-free survival (DFS), 5-year distant metastasis-free survival (DMFS), and 5-year breast cancer-specific survival (BCSS). Median follow-up time was 77 months. Patients ≤40 years of age presented with a significantly worse 5-year DFS and 5-year DMFS. In stratified analyses, young women with luminal A subtype disease were associated with a worse 5-year DFS, 5-year DMFS, and 5-year BCSS. Women with luminal B (Her2−) tumors showed a decrease in 5-year DFS and 5-year DMFS. Our findings support the hypothesis that young age seems to be an independent risk factor for the prognosis for breast cancer patients with the luminal A and luminal B (Her2−) subtypes but not in those with luminal B (Her2+), Her2 over-expression, and triple-negative disease.

The removal of heavy metals ions from wastewater by an economic, high-effective, and environmentally friendly method is particularly important. In this study, an effective lignin-based bio-adsorbent (SAPL-1.5), which contained specific functional groups and spatial cross-linking structures, was synthesized through chemical modification. SAPL-1.5 was comprehensively characterized by 31 P, 1 H, 13 C NMR, and elemental analysis as compared to the raw lignin. The results showed that the chemical reactivity of lignin was significantly improved after phenolation process, and the adsorption groups were successfully grafted onto lignin macromolecule. In addition, the influences of pH, SAPL-1.5 dosage, contact time, and initial Pb (II) concentration on the adsorption performance was systematically investigated. The highest adsorption capacity reached to 130.2 mg/g (Pb (II), 140 mg/L), and a removal efficiency of 100% was achieved (Pb (II), 20 mg/L). Moreover, the adsorption isotherm and adsorption kinetics indicated that the results were fitting well with the Langmuir and pseudo-second-order model, respectively. Furthermore, the removal efficiency of SAPL-1.5 for Pb (II) (20 mg/mL) still maintained over 85% after 5 cycles. Therefore, the lignin-based material obtained could be considered as a promising potential adsorbent with a low cost, high performance and reutilization for its application in the wastewater treatment process. It is believed that the lignin-based bio-sorbent can enlarge the lignin valorization in the current biorefinery process.

Recently, many researchers have been dedicated to using convolutional neural networks (CNNs) to extract global-context features (GCFs) for remote-sensing scene classification. Commonly, accurate classification of scenes requires knowledge about both the global context and local objects. However, unlike the natural images in which the objects cover most of the image, objects in remote-sensing images are generally small and decentralized. Thus, it is hard for vanilla CNNs to focus on both global context and small local objects. To address this issue, this paper proposes a novel end-to-end CNN by integrating the GCFs and local-object-level features (LOFs). The proposed network includes two branches, the local object branch (LOB) and global semantic branch (GSB), which are used to generate the LOFs and GCFs, respectively. Then, the concatenation of features extracted from the two branches allows our method to be more discriminative in scene classification. Three challenging benchmark remote-sensing datasets were extensively experimented on; the proposed approach outperformed the existing scene classification methods and achieved state-of-the-art results for all three datasets.

Eleven bacteriochlorins have been prepared for surface attachment, bioconjugation, water-solubilization, vibrational studies, and elaboration into multichromophore arrays.

Six types of lignin-carbohydrate complex (LCC) fractions were isolated from Eucalyptus. The acidic dioxane treatment applied significantly improved the yield of LCCs. The extraction conditions had a limited impact on the LCC structures and linkages. Characterization of the lignin-carbohydrate complex (LCC) structures and linkages promises to offer insight on plant cell wall chemistry. In this case, Eucalyptus LCCs were extracted by aqueous dioxane, and then precipitated sequentially by 70% ethanol, 100% ethanol, and acidic water (pH = 2). The composition and structure of the six LCC fractions obtained by selective precipitation were investigated by sugar analysis, molecular weight determination, and 2D HSQC NMR. It was found that the acidic (0.05-M HCl) dioxane treatment significantly improved the yield of LCCs (66.4% based on Klason lignin), which was higher than the neutral aqueous dioxane extraction, and the extraction condition showed limited impact on the LCC structures and linkages. In the fractionation process, the low-molecular-weight LCCs containing a high content of carbohydrates (60.3-63.2%) were first precipitated by 70% ethanol from the extractable solution. The phenyl glycoside (PhGlc) bonds (13.0-17.0 per 100Ar) and highly acetylated xylans were observed in the fractions recovered by the precipitation with 100% ethanol. On the other hand, such xylan-rich LCCs exhibited the highest frequency of β-O-4 linkages. The benzyl ether (BE) bonds were only detected in the fractions obtained by acidic water precipitation.