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Objective A resident-led school-based clinic to serve low-income populations was established in 2019 and served as a continuity clinic for pediatric residents at a single university. Our aim was to assess the feasibility, clinic outcomes, and resident experience of a resident-led school-based clinic (RLSBC), established in an elementary school that serves an underserved population. Methods A retrospective chart review for the first 6 months (October 2019 to March 2020) of clinic operations was conducted. Feasibility metrics included the number of patients, visits and planned follow-ups; clinic outcomes included the number and type of presenting complaint, new diagnoses and interventions. Residents were also surveyed to assess their satisfaction and perceived learning in training at the school-based clinic. Results Over the first 19 clinic days, 48 children were seen at the school-based clinic. Of the clinic users, 60% did not have a primary care physician, 46% received a new diagnosis, 46% received an intervention in the form of medication prescription, laboratory/imaging requisitions or referrals, and 96% received a treatment plan. Residents positively rated the experience of staffing the school-based clinic in all aspects, including learning environment, clinic and team environment, teaching obtained, practice management, and overall experience. Conclusion A RLSBC is feasible and our outcomes suggest that such clinics may address health care needs of low-income families and children, while being a positively rated educational experience for pediatric residents. [ABSTRACT FROM AUTHOR]

Bone is the most common site of metastasis in prostate cancer (PCa) patients and is correlated with poor prognosis and increasing economic burden. Few studies have analyzed the prognostic prediction for metastatic PCa patients with the assistance of neural networks. Four convolutional neural network (CNN) models are developed and evaluated to predict the overall survival (OS) of PCa patients with bone metastasis. All the CNN models are first trained with 64 samples and evaluated with 10 samples; two models use only bone scan images and two models use both bone scan images and clinical parameters (CPs). The predictions of the best models are compared with those by two urology surgeons on 20 test samples. Our best models can predict OS of PCa patients with bone metastasis with AUC=0.8022 by using only bone scan images and AUC=0.8132 by using both bone scan images and CPs on 20 test samples. The best Youden indexes of the two models are 0.6263 and 0.7142, respectively, which are 0.3077 and 0.3131 higher than that of the urologists' average Youden index, which indicate that CNN models exhibit significant advantages. CNN models are suitable to predict OS in PCa patients with bone metastasis using bone scan images and CPs. Our models show better performance in terms of accuracy and stability than urology surgeons. [ABSTRACT FROM AUTHOR]

Plant salt damage caused by soil salinization is a common problem in the world. Regulating plant salt tolerance is regarded as one of the effective ways to solve soil salt damage. Choline chloride and rhamnolipid, two new materials, play a positive role in improving plant stress resistance, but the effects of combined application of choline chloride and rhamnolipid on plant salt tolerance are not clear. In this study, Provence tomato was used as material to study the effects of combined application of choline chloride and rhamnolipid on the growth, development, and physiological characteristics of tomato in moderately salinized soil. The results showed that the addition of choline chloride and rhamnolipid complexed with organic manures to soil decreased superoxide anion (O2−), malondialdehyde (MAD), and the ratio of Na+/K+ and increased peroxidase (POD) activity and osmolytes biosynthesis of proline. These indexes were related to the ratio of choline chloride and rhamnolipid, and the change range was the largest at an appropriate amount. Additionally, choline chloride and rhamnolipid application not only increased chlorophyll content, net photosynthetic rate, transpiration rate, and yield but also fruit quality, including soluble sugar and VC. Our findings highlight that choline chloride and rhamnolipid may be proposed as effective methods to improve salinity tolerance and increase yield and quality of plants in agriculture. [ABSTRACT FROM AUTHOR]

In this study, a SnCr/KIT-6 catalyst was synthesized by the incipient wetness impregnation method, and its performance was studied for the catalytic oxidation of chlorobenzene (CB). In addition, the activity, stability, physical structure, valence state change, chlorine deposition, and surface intermediates of the catalyst were analyzed using XRD, N2 adsorption–desorption analysis, H2-TPR, O2-TPD, TEM, XPS, and in situ FTIR spectroscopy. The experimental results revealed that the introduction of Sn can effectively improve the activity and chlorine resistance of the Cr/KIT-6 catalyst. According to T90 (temperature for the CB conversion of 90%), the catalyst exhibited the highest activity at a Sn/(Cr + Si) molar ratio of 0.15, which led to a CB conversion of greater than 65% for 100 h at T80. The introduction of Sn clearly promoted the dispersion of surface oxides and increased the content of highly oxidizing species (Cr6+). The results also suggested that the introduction of Sn promotes the dispersion of CrOx on the carrier (the major active species in CB degradation), rearranges the valence distribution via the redox equilibrium of 3Sn4+ + 2Cr3+ ↔ 2Cr6+ + 3Sn2+, and increases the surface Cr6+ content. The formation of a SnO2–CrOx solid solution improved the redox ability of the composite catalyst and reduced the deposition of the surface-deposited species (especially chlorine species) on the catalyst surface, resulting in the enhanced catalytic performance of the SnCr/KIT-6 catalyst toward the oxidation of CB. [ABSTRACT FROM AUTHOR]