The effective removal of oxytetracycline hydrochloride (OTC) from the water environment is of great importance. Adsorption as a simple, stable, and cost-effective technology is regarded as an important method for removing OTC. Herein, a low-cost biochar with a developed mesoporous structure was synthesized via pyrolysis of poplar leaf with potassium bicarbonate (KHCO3) as the activator. KHCO3 can endow biochar with abundant mesopores, but excessive KHCO3 cannot continuously promote the formation of mesoporous structures. In comparison with all of the prepared biochars, PKC-4 (biochar with a poplar leaf to KHCO3 mass ratio of 5:4) shows the highest adsorption performance for OTC as it has the largest surface area and richest mesoporous structure. The pseudo-second-order kinetic model and the Freundlich equilibrium model are more consistent with the experimental data, which implies that the adsorption process is multi-mechanism and multi-layered. In addition, the maximum adsorption capacities of biochar are slightly affected by pH changes, different metal ions, and different water matrices. Moreover, the biochar can be regenerated by pyrolysis, and its adsorption capacity only decreases by approximately 6% after four cycles. The adsorption of biochar for OTC is mainly controlled by pore filling, though electrostatic interactions, hydrogen bonding, and π-π interaction are also involved. This study realizes biomass waste recycling and highlights the potential of poplar leaf-based biochar for the adsorption of antibiotics.

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Purpose/Objective(s): Optimal treatment for nonesmall cell lung cancer (NSCLC), depending on patients' clinical stage, performance status, and preferences, may include surgical resection, radiation therapy, chemotherapy (in various combinations), or no treatment. We evaluated variation in stage-stratified use of treatment modalities in and out of a multidisciplinary (MultiD) program in a large community-based healthcare system. We hypothesized that MultiD care will optimize modality use. Materials/Methods: 2014-2015 NSCLC Tumor Registry data from 4 hospitals within 1 tri-state healthcare system retrospectively reviewed; MultiD data prospectively collected from a weekly MultiD tumor conference. MultiD data were analyzed separately from the tumor registry data. Any MultiD patients present in the tumor registry data were removed. Staging was based on information available before commencement of any treatment modality (defined as the actual treatment received). Patients were clustered into 3 stage groupings: I-II, III, and IV. Stage-stratified frequencies of treatment modalities across the 4 hospitals and the MultiD program were compared using Chi-squared tests. Results: 1,614 NSCLC patients were seen outside and 248 within the MultiD program. Demographics were similar except MultiD had a higher proportion of African American (26% v 33%, PZ.01) and Medicaid/ uninsured (8.3% v 22%) and fewer commercially insured (55% v 40%) patients (P<.001). Stage distributions for non-MultiD versus MultiD were: 29% versus 46% (stage I/II); 20% versus 25% (stage III); 52% versus 29% (stage IV). There were striking differences in use of modalities for non-MultiD versus MultiD: surgery for stage I/II disease 48% versus 63% and no treatment, 16% versus 6% (PZ.01); multimodality therapy for stage III, 62% versus 75%, and no treatment 19% versus 10% (PZ.02); chemotherapy for stage IV, 57% versus 70% stage IV, radiation only, 12% versus 13%, and no treatment 29% versus 9% (P<.001). Patient demographics were similar across the 4 hospitals, but modality use varied widely. For stage I/II, surgical resection rates ranged from 24%-62% and no treatment from 7%-42%; for stage III, multimodality treatment ranged from 40%-81%, and no treatment from 13%-36%; for stage IV, chemotherapy rates ranged from 47%-59%, and no treatment from 25%-43% (P<.001 for all stages). Conclusion: Despite less favorable patient demographics, stage-stratified care within a community-based MultiD Program was more directed towards active and multimodality care. Great heterogeneity in pattern of care exists across hospitals within the same healthcare system. Further research into the causes of stage-stratified treatment variation, and the potential use of structured MultiD Programs to improve access to care is warranted.