The relationship between social support and professional identity of health professional students from a two-way social support theory perspective: chain mediating effects of achievement motivation and meaning in life.

BACKGROUND: Studies has suggested that receiving social support improves the professional identity of health professional students. According to the two-way social support theory, social support includes receiving social support and giving social support. However, the effect of the two-way social support on health professional students' professional identity has not been clarified yet. METHODS: To explore the mechanism of how two-way social support affects health professional students' professional identity, an observational, cross-sectional study was conducted among a convenience and cluster sample of 1449 health professional students from two medical schools in western China. Measures included a short version of the two-way social support scale, a health professional students' professional identity questionnaire, an achievement motivation scale, and a meaning in life scale. Data were analyzed by use of SPSS26.0 software and PROCESSv4.0 plug-in. RESULTS: Receiving social support, giving social support, achievement motivation, meaning in life, and professional identity were positively correlated with each other. Receiving and giving social support not only directly predicted health professional students' professional identity, but also indirectly predicted health professional students' professional identity through the mediating roles of achievement motivation and meaning in life, and the chain mediating roles of achievement motivation and meaning in life, respectively. The effectiveness of predicting health professional students' professional identity varied among different types of two-way social support, which could be depicted as two-way social support > mainly giving social support > mainly receiving social support > low two-way social support. CONCLUSION: In the medical education, the awareness and ability of health professional students to receive and give social support should be strengthened. More attention should be drawn on the chain mediating effect of achievement motivation and meaning in life between two-way social support and professional identity. The current results shed new light on exploring effective ways of improving health professional students' professional identity, which suggested that more attention should be paid to the positive effects of mainly giving social support and two-way social support rather than only on the effects of receiving social support.

Lung Cancer Prediction Using Electronic Claims Records: A Transformer-Based Approach.

Electronic claims records (ECRs) are large scale and longitudinal collections of individual's medical service seeking actions. Compared to in-hospital medical records (EMRs), ECRs are more standardized and cross-sites. Recently, there has been studies showing promising results on modeling claims data for a wide range of medical applications. However, few of them address the exclusion criteria on cohort selection to extract new incidence without prior signs and also often lack of emphasis on predicting cancer in early stages. In this work, we aim to design a lung cancer prediction framework using ECRs with rigorous exclusion design using state-of-the-art sequence-based transformer. Furthermore, this work presents one of the first results by applying disease prediction model to the entire population in Taiwan. The result shows over 2.1 predictive power, 5 average positive predictive value (PPV), and 0.668 area under curve (AUC) in all-stage lung cancer and around 2.0 predictive power, 1 average PPV and 0.645 AUC in early-stage in our dataset. Sub-cohort analysis could funnel high precision selective group into prioritized clinical examination. Onset analysis validates the effect of our exclusion criteria. This work presents comprehensive analyses on lung cancer prediction, and the proposed approach can serve as a state-of-the-art disease risk prediction framework on claims data.

Instantly Detecting Catalysts' Hot Spots Temperature In Situ during Photocatalysis by Operando Raman Spectroscopy.

Precisely detecting the catalysts' hot spots temperature in situ instantly during photocatalysis is a great challenge but extremely important for chemical reactions. However, no efficient method has been developed to instantly detect the hot spots temperature in situ during photocatalysis. Herein, we designed a simple and convenient method to measure the instant hot spots temperature in situ on the nanostructure surface during photocatalysis by operando Raman spectroscopy using 4-methoxyphenyl isocyanide (MI) as the probe molecule. The νN≡C frequency of MI varied linearly with temperature, which is caused by the orientation change of the MI induced by temperature, leading to the change in the frequency of the νN≡C bond that directly interacts with the nanostructure surface. Using in situ surface-enhanced Raman spectroscopy (SERS), the surface temperature of the catalysts illuminating for each time can be measured instantly. Interestingly, the catalytic activity of the hydrogen evolution reaction (HER) for the Au-Ag/Ag2S heterojunction nanorods (HJNRs) are higher than that for the Ag-Au-Ag HJNRs, although they have a lower surface temperature during photocatalysis; therefore, hot carriers and electronic structure contributed more to the catalytic activity of the Au-Ag/Ag2S HJNRs than that of the Ag-Au-Ag HJNRs. Such an instant hot spots temperature detecting method of catalysts can greatly facilitate the analysis of the mechanism of catalytic processes.

First report of Agrobacterium tumefaciens causing crown gall disease of roselle (Hibiscus sabdariffa L.) in Taiwan.

Roselle (Hibiscus sabdariffa L.) plants, whose calyces are used for production of beverages or jams, are mainly cultivated in Taitung County of eastern Taiwan. Since 2016, large crown galls were observed on the roselle plants in the commercial plantations at Taimali and Jinfong Townships of Taitung County. A follow-up survey in July and August of 2017 revealed spreading of this disease to the neighboring areas including Beinan and Dawu Townships. Disease incidence was estimated to be 0.6-10%. Galls of varying sizes (2-15 cm in diameter) were usually found on the roots and crowns of the roselle plants, starting with small swellings at the infection sites. Galls were light-colored, and smooth and tender in texture at the early stage, but later turned dark-colored, and appeared rough and woody. In some cases, adventitious roots extruding from the larger crown galls could be seen. Isolation of the causal agent was performed by quadrantally streaking bacterial suspension made from surface-sterilized, macerated galls on trypticase soy agar (TSA). After incubating at 28°C for 5 days, single colonies were transferred onto new TSA plates for further cultivation at 28°C. Finally, circular, convex, viscous and milky white colonies with smooth surface similar to colony morphology of Agrobacterium tumefaciens C58 were obtained for further identification. First, all six candidate isolates (TZ-1, TL1-2, TL2-1, TD1-1, TD1-24 and TD2-1) were identified as Agrobacterium spp. using the partial sequences of the 16S rRNA gene (accession numbers MW205820 to MW205825 in the GenBank database). The selected isolates also showed some biochemical and physiological characteristics similar to A. tumefaciens, including oxidase positive, growth at 35°C and in 2% NaCl, and alkalinity from litmus milk. Moreover, they were tested negative for utilization of citrate and acid production on potato dextrose agar (PDA) supplemented with calcium carbonate. Under a transmission electron microscope, the bacterium was rod-shaped and possessed peritrichous flagella. By means of multiplex PCR using primers designed for differentiation of Agrobacterium rubi, Agrobacterium vitis and Agrobacterium biovars 1 and 2, a 184 bp product was detected in all six isolates, indicating that they all belong to Agrobacterium biovar 1. Furthermore, the recA allele of each isolate was PCR amplified using primers F2898/F2899, and recA sequence analysis assigned all six isolates to A. tumefaciens genomospecies G7 (GenBank accession numbers MZ570905-MZ570910). Pathogenicity assay was carried out by inoculating the stems of 2-week-old roselle seedlings through wounds made with a sterile needle with bacteria on it. The inoculated seedlings were kept in plastic bags to maintain high humidity. Symptoms similar to those observed in the field developed at the inoculation sites after 7 days, and Koch's postulates were fulfilled when the bacteria re-isolated from the galls were also identified as A. tumefaciens genomospecies G7 using recA gene sequence analysis. To our knowledge, this is the first report of crown gall disease caused by A. tumefaciens on Hibiscus sabdariffa in Taiwan. This disease may potentially damage the roselle industry if no action is taken to stop its spreading. Identification of the causal agent of roselle crown gall disease could help us further investigate its ecology and develop integrated pest management strategies for prevention of this disease in the future.

Deriving A Novel Health Index Using A Large-Scale Population Based Electronic Health Record With Deep Networks.

Health indexes are useful tools for monitoring the health condition of a population and can be used to guide healthcare policy of governments. However, most health indexes are constructed by using statistical methods to summarize recent adverse events (e.g., mortality). Information from these tools may reflect merely the impact of prior health policy holistically and can hardly indicate the most recent dynamics and its impact on future health conditions. As the advancements in medications and medical techniques rapidly evolve, there is a need of new health indexes that can reflect the most recent predictive health condition of a population and can easily be summarized with respect of any sub-population of interest. In this work, we develop a novel health index by using deep learning technique on a large-scale and longitudinal population based electronic health record (EHR). Three deep neural network (DNN) models were trained to predict 4-year event rates of mortality, hospitalization and cancer occurrence at an individual-level. Platt calibration approach was used to transform DNN output scores into estimated event risks. A novel health index is then constructed by weighted scoring these calibrated event risks. This individual-level health index not only provide a better predictive power but can also be flexibly summarized for different regions or sub-populations of interest - hence providing objective insights to develop precise personal or national policy beyond conventional health index.

Efficacy of Cone-Beam Computed Tomography in Evaluating Bone Quality for Optimum Implant Treatment Planning.

PURPOSE: This study examined (1) if cone-beam computed tomography (CBCT) can determine relative differences in bone mineral density distribution using clinical images of patients' mandibular bone and (2) if the relative differences can be used to detect the effects of sex and age on bone mineral density distribution. MATERIALS AND METHODS: Sixty-six clinical CBCT images from patients (36 females and 30 males) of 3 age groups (40, 50, and 60 years) were identified. Alveolar (AB) and basal cortical bone (CB) regions were digitally isolated. A histogram of gray levels, which are proportional to degrees of bone mineralization, was obtained from each region. Mean, variability (SD and coefficient of variation), and percentage differences of gray level parameters between AB and basal CBs were computed. RESULTS: Significant sex differences in gray level variability were observed within the postmenopausal age group (P < 0.042). CONCLUSION: These findings suggest that clinical CBCT images can be a valuable tool in providing information on bone quality, which is an important criterion for optimum planning for dental implant placement.

FDA approval summary: crizotinib for the treatment of metastatic non-small cell lung cancer with anaplastic lymphoma kinase rearrangements.

On August 26, 2011, crizotinib received accelerated approval for the treatment of patients with locally advanced or metastatic non-small cell lung cancer (NSCLC) that is ALK-positive as detected by a test approved by the U.S. Food and Drug Administration (FDA). Approval was based on two single-arm trials demonstrating objective response rates (ORRs) of 50% and 61% and median response durations of 42 and 48 weeks. On November 20, 2013, crizotinib received regular approval based on confirmation of clinical benefit in study A8081007, a randomized trial in 347 patients with ALK-positive advanced NSCLC who had previously received one platinum-containing regimen. Patients were assigned (1:1) to receive crizotinib 250 mg orally twice daily or standard of care (docetaxel or pemetrexed). The primary endpoint was progression-free survival (PFS) determined by independent radiology review; secondary endpoints were ORR and overall survival (OS). PFS was significantly longer in the crizotinib arm, with median PFS of 7.7 and 3.0 months in the crizotinib and chemotherapy arms, respectively, and a 46% absolute increase in ORR but no difference in OS between treatment arms at the interim analysis. The most common adverse drug reactions (>25%) in crizotinib-treated patients were vision disorders, nausea, diarrhea, vomiting, constipation, edema, elevated transaminases, and fatigue. The most serious toxicities of crizotinib were hepatotoxicity, interstitial lung disease or pneumonitis, and QT-interval prolongation. Crizotinib's rapid clinical development program (6 years from identification of ALK rearrangements in a subset of NSCLC to full FDA approval) is a model of efficient drug development in this new era of molecularly targeted oncology therapy.