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Table_4.docx

Li, Jialu ; Hao, Yiwei ; Liu, Ying ; [et al.]

Frontiers Media SA ; 2024

In: Frontiers in Public Health Vol. 11 ( 2024-1-5)

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In: Frontiers in Public Health, Frontiers Media SA, Vol. 11 ( 2024-1-5)

Abstract: The study aimed to use supervised machine learning models to predict the length and risk of prolonged hospitalization in PLWHs to help physicians timely clinical intervention and avoid waste of health resources. Methods Regression models were established based on RF, KNN, SVM, and XGB to predict the length of hospital stay using RMSE, MAE, MAPE, and R 2 , while classification models were established based on RF, KNN, SVM, NN, and XGB to predict risk of prolonged hospital stay using accuracy, PPV, NPV, specificity, sensitivity, and kappa, and visualization evaluation based on AUROC, AUPRC, calibration curves and decision curves of all models were used for internally validation. Results In regression models, XGB model performed best in the internal validation (RMSE = 16.81, MAE = 10.39, MAPE = 0.98, R 2 = 0.47) to predict the length of hospital stay, while in classification models, NN model presented good fitting and stable features and performed best in testing sets, with excellent accuracy (0.7623), PPV (0.7853), NPV (0.7092), sensitivity (0.8754), specificity (0.5882), and kappa (0.4672), and further visualization evaluation indicated that the largest AUROC (0.9779), AUPRC (0.773) and well-performed calibration curve and decision curve in the internal validation. Conclusion This study showed that XGB model was effective in predicting the length of hospital stay, while NN model was effective in predicting the risk of prolonged hospitalization in PLWH. Based on predictive models, an intelligent medical prediction system may be developed to effectively predict the length of stay and risk of HIV patients according to their medical records, which helped reduce the waste of healthcare resources.

Type of Medium: Online Resource

ISSN: 2296-2565

URL: Article

DOI: 10.3389/fpubh.2023.1282324

DOI: 10.3389/fpubh.2023.1282324.s001

DOI: 10.3389/fpubh.2023.1282324.s002

DOI: 10.3389/fpubh.2023.1282324.s003

DOI: 10.3389/fpubh.2023.1282324.s004

DOI: 10.3389/fpubh.2023.1282324.s005

DOI: 10.3389/fpubh.2023.1282324.s006

Language: Unknown

Publisher: Frontiers Media SA

Publication Date: 2024

detail.hit.zdb_id: 2711781-9

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Data_Sheet_1.docx

Ding, Yi ; Nie, Laiyin ; Yang, Xiao-Chen ; [et al.]

Frontiers Media SA ; 2022

In: Frontiers in Microbiology Vol. 12 ( 2022-1-5)

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In: Frontiers in Microbiology, Frontiers Media SA, Vol. 12 ( 2022-1-5)

Abstract: Esterases are a class of enzymes that split esters into an acid and an alcohol in a chemical reaction with water, having high potential in pharmaceutical, food and biofuel industrial applications. To advance the understanding of esterases, we have identified and characterized E53, an alkalophilic esterase from a marine bacterium Erythrobacter longus . The crystal structures of wild type E53 and three variants were solved successfully using the X-ray diffraction method. Phylogenetic analysis classified E53 as a member of the family IV esterase. The enzyme showed highest activity against p -nitrophenyl butyrate substrate at pH 8.5–9.5 and 40 ° C. Based on the structural feature, the catalytic pocket was defined as R1 (catalytic center), R2 (pocket entrance), and R3 (end area of pocket) regions. Nine variants were generated spanning R1–R3 and thorough functional studies were performed. Detailed structural analysis and the results obtained from the mutagenesis study revealed that mutations in the R1 region could regulate the catalytic reaction in both positive and negative directions; expanding the bottleneck in R2 region has improved the enzymatic activity; and R3 region was associated with the determination of the pH pattern of E53. N166A in R3 region showed reduced activity only under alkaline conditions, and structural analysis indicated the role of N166 in stabilizing the loop by forming a hydrogen bond with L193 and G233. In summary, the systematic studies on E53 performed in this work provide structural and functional insights into alkaliphilic esterases and further our knowledge of these enzymes.

Type of Medium: Online Resource

ISSN: 1664-302X

URL: Article

DOI: 10.3389/fmicb.2021.798194

DOI: 10.3389/fmicb.2021.798194.s001

Language: Unknown

Publisher: Frontiers Media SA

Publication Date: 2022

detail.hit.zdb_id: 2587354-4

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Management and Outcomes of Patients With Radiotherapy Interruption During the COVID-19 Pandemic

Ying, Xiaofang ; Bi, Jianping ; Ding, Yi ; [et al.]

Frontiers Media SA ; 2021

In: Frontiers in Oncology Vol. 11 ( 2021-11-19)

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In: Frontiers in Oncology, Frontiers Media SA, Vol. 11 ( 2021-11-19)

Abstract: This retrospective observational study examined patients who experienced radiotherapy (RT) interruption during the Wuhan lockdown for the novel coronavirus disease 2019 (COVID-19) pandemic. Materials and Methods The data of all patients whose RT was interrupted during the Wuhan lockdown from January 23 to April 8, 2020 were collected. Patient-, cancer-, and treatment-related characteristics were analyzed, along with interruption time, disease progression type, and survival status. The methods employed in order to compensate for RT interruption were also described. Results There were altogether 129 cancer patients whose RT was interrupted. Nineteen (14.7%) patients experienced a total interruption time of at most 7 days; the interruption time was 8–14 days for 27 (20.9%) patients, and 15 or more days for 47 (36.4%) patients. The remaining 36 (27.9%) patients did not come back to our hospital for further RT. We first describe our experience with re-immobilization and/or re-planning (n = 17) as well as dose compensation/adjustment. Of the 40 definitive radiotherapy patients, 37 had squamous cell carcinoma of nasopharyngeal, lung, or cervical origin. Most patients (85/93, 91.4%) were followed up for more than one year. Among the 40 patients who received definitive radiotherapy, nine patients experienced disease progression and five patients died. Three of the seven (42.9%) patients who did not finish radiotherapy after interruption died, as compared to only two of the 33 (6.1%) patients who completed radiotherapy. EQD2 (equivalent dose in 2 Gy fractions) at the time point of RT interruption was calculated. Five of the six patients (83.3%) who received EQD2 ≤10 Gy suffered from disease progression, compared with four of the 34 (11.8%) patients who received EQD2 & gt;10 Gy. For the seven definitive radiotherapy cases who did not finish radiotherapy, three received systemic anti-cancer treatments and three died (all of whom did not receive further systemic therapies). Conclusions This study provides the longest follow-up for the outcomes of RT interruption during COVID-19 pandemic to date. It cannot imply causation but implies that completing RT is important, along with the utility of having patients remain on systemic therapies if RT is to be interrupted.

Type of Medium: Online Resource

ISSN: 2234-943X

URL: Article

DOI: 10.3389/fonc.2021.754838

Language: Unknown

Publisher: Frontiers Media SA

Publication Date: 2021

detail.hit.zdb_id: 2649216-7

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