A Decision Support Framework for Curriculum Planning in Undergraduate Supply Chain Management Program: An Integrated Approach

Curriculum planning is an important but complex and challenging decision-making problem at universities. There is a growing interest in curriculum planning problem. However, the body of research on curriculum planning process using analytical methods is still small. Additionally, prior research focused on planning of an individual curriculum or making study plan for students. Curriculum planning at the program level is an under-researched topic. A robust model has not been constructed to address curriculum selection and credit allocation problems simultaneously. To help educational leaders make the most appropriate curriculum plan corresponding to their goals with the highest level of utility achieved, this study presents a new decision support framework with integrated approach. In the proposed framework, based on the competency weights derived from the analytical hierarchy process method, the importance of each potential curriculum is evaluated using the fuzzy comprehensive evaluation method. An exploratory estimation is made to calculate the contribution values of competency development by each curriculum taught at different levels. Finally, multichoice goal programming with utility function determines the curriculum to be provided and corresponding credits to minimize the aggregate deviations from predefined goals with multiple aspirations. An application to curriculum planning of an undergraduate supply chain management program is presented to validate the flexibility and practicality of the proposed approach. The implications of the study are not restricted to curriculum planning of supply chain management program.

Fast and Effective Prediction of the Absolute Binding Free Energies of Covalent Inhibitors of SARS-CoV-2 Main Protease and 20S Proteasome.

The COVID-19 pandemic has been a public health emergency with continuously evolving deadly variants around the globe. Among many preventive and therapeutic strategies, the design of covalent inhibitors targeting the main protease (Mpro) of SARS-CoV-2 that causes COVID-19 has been one of the hotly pursued areas. Currently, about 30% of marketed drugs that target enzymes are covalent inhibitors. Such inhibitors have been shown in recent years to have many advantages that counteract past reservation of their potential off-target activities, which can be minimized by modulation of the electrophilic warhead and simultaneous optimization of nearby noncovalent interactions. This process can be greatly accelerated by exploration of binding affinities using computational models, which are not well-established yet due to the requirement of capturing the chemical nature of covalent bond formation. Here, we present a robust computational method for effective prediction of absolute binding free energies (ABFEs) of covalent inhibitors. This is done by integrating the protein dipoles Langevin dipoles method (in the PDLD/S-LRA/ß version) with quantum mechanical calculations of the energetics of the reaction of the warhead and its amino acid target, in water. This approach evaluates the combined effects of the covalent and noncovalent contributions. The applicability of the method is illustrated by predicting the ABFEs of covalent inhibitors of SARS-CoV-2 Mpro and the 20S proteasome. Our results are found to be reliable in predicting ABFEs for cases where the warheads are significantly different. This computational protocol might be a powerful tool for designing effective covalent inhibitors especially for SARS-CoV-2 Mpro and for targeted protein degradation.

Breakthrough in breast reconstruction in the context of COVID-19: safety and efficiency of endoscopic breast reconstruction at a day surgery center.

BACKGROUND: In recently years, breast endoscopic reconstruction surgery is becoming increasingly popular. And we have explored a series of endoscopic breast reconstruction procedures and applied it to our day surgery under the epidemic control of the novel coronavirus. METHODS: The present study was a retrospective analysis. Patients who underwent unilateral breast endoscopic reconstruction surgery in the West China Hospital from April 2017 to February 2021 were included in the study. Patients were divided into the following three groups: ward exploration period (WEP), ward maturation period (WMP), and day surgery period (DSP), respectively. We compared the results of postoperative complications, hospitalization costs, operation time, and BREAST-Q (a patient-reported outcome instrument measuring health-related quality-of-life and patient satisfaction in breast surgery) scale scores among the three groups of patients. RESULTS: A total of 66 patients were included (WEP n=30, WMP n=14, DSP n=22). Four people refused to complete the BREAST-Q scale, and five patients missed complication record sheets. Patients in the DSP and WMP groups had slightly higher postoperative satisfaction with their breasts than WEP, but there was no statistically significant difference (3 months postoperatively: WEP vs. WMP =0.515, WEP vs. DSP =0.418, WMP vs. DSP =0.982). On the postoperative BREAST-Q scale scores of psychosocial, sexual life and chest well-being, patients with DSP scored slightly higher than those with WEP versus WMP, but there was no statistically significant difference. The incidence of postoperative complications was generally higher in the WEP group than in the WMP and DSP groups, but there was no statistically significant incidence of either major or minor complications (P=1.000). With the use of prostheses and mesh, patients in the DSP group had lower hospitalization costs than other two groups. In terms of operative time, patients in the WMP and DSP groups had shorter operative times compared with the WEP group, and the results were statistically significant (WEP vs. WMP =0.000, WEP vs. DSP =0.000, WMP vs. DSP =0.243). CONCLUSIONS: We believe that performing our newly developed endoscopic breast reconstructive surgery at a day surgery center is safe and reliable.

A new class of α-ketoamide derivatives with potent anticancer and anti-SARS-CoV-2 activities.

Inhibitors of the proteasome have been extensively studied for their applications in the treatment of human diseases such as hematologic malignancies, autoimmune disorders, and viral infections. Many of the proteasome inhibitors reported in the literature target the non-primed site of proteasome's substrate binding pocket. In this study, we designed, synthesized and characterized a series of novel α-keto phenylamide derivatives aimed at both the primed and non-primed sites of the proteasome. In these derivatives, different substituted phenyl groups at the head group targeting the primed site were incorporated in order to investigate their structure-activity relationship and optimize the potency of α-keto phenylamides. In addition, the biological effects of modifications at the cap moiety, P1, P2 and P3 side chain positions were explored. Many derivatives displayed highly potent biological activities in proteasome inhibition and anticancer activity against a panel of six cancer cell lines, which were further rationalized by molecular modeling analyses. Furthermore, a representative α-ketoamide derivative was tested and found to be active in inhibiting the cellular infection of SARS-CoV-2 which causes the COVID-19 pandemic. These results demonstrate that this new class of α-ketoamide derivatives are potent anticancer agents and provide experimental evidence of the anti-SARS-CoV-2 effect by one of them, thus suggesting a possible new lead to develop antiviral therapeutics for COVID-19.

Clinical features, treatments and outcomes of severe and critical severe patients infected with COVID-19: A system review and meta-analysis (preprint)

Backgrounds: The outbreak of COVID-19 caused by a novel coronavirus, SARS-CoV-2, has been listed as a public health emergency of international concern by WHO. Most COVID-19 patients presented with a mild infection, but many challenges exist in therapy of severe and critical severe patients. This paper systematically reviewed clinical features, treatments and outcomes of severe and critical severe patients infected COVID-19. Methods: The clinical, laboratory, imaging features, treatment and outcomes of COVID-19 were collected. The data were analyzed by using STATA 15 statistical software to estimate the prevalence and 95% CI in severe and critical severe patients with COVID-19. A random or fixed effect model was used to estimate the prevalence and 95% CI. Results: After screening, 8 studies including a total of 275 patients were included in this meta-analysis. The percentage of severe and critical severe patients in confirmed COVID-19 cases was 25% (95% CI 16-36%). Fever, cough, dyspnea, lymphopenia and bilateral distribution of patchy shadows were the most prevalent findings in these patients. Utilization rate of antiviral drugs, corticosteroid, non-invasive ventilation, invasive mechanical ventilation was high in therapy strategies. The most prevalent complications were ARDS, shock, and acute cardiac injury. Discussion: Severe and critical severe COVID-19 patients usually had complications even a fatal outcome. As vaccines and anti-coronaviral drugs are under development, the principles of treatment for these patients should be focused on improving oxygenation, lung protective and function support of multiple organs.