In this paper, we review the contributions to date for analyzing the newsvendor problem.Our focus is on examining the specific extensions for analyzing this problem in the context of modeling customer demand, supplier costs, and the buyer risk profile. More specifically, we analyze the impact of market price, marketing effort, and stocking quantity on customer demand; how supplier prices can serve as a coordination mechanism in a supply chain setting; integrating alternative supplier pricing policies within the newsvendor framework; and how the buyer's risk profile moderates the newsvendor order quantity decision. For each of these areas, we summarize the current literature and develop extensions. Finally, we also propose directions for future research.

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Nucleic-acid-based immune adjuvants have been extensively investigated for the design of cancer vaccines. However, nucleic acids often require the assistance of a carrier system to improve cellular uptake. Yet, such systems are prone to carrierassociated adaptive immunity, leading to difficulties in a multidose treatment regimen. Here, we demonstrate that a spherical nucleic acid (SNA)-based self-adjuvanting system consisting of phosphodiester oligonucleotides and vitamin E can function as a potent anticancer vaccine without a carrier. The two functional modules work synergistically, serving as each other's delivery vector to enhance toll-like receptor 9 activation. The vaccine rapidly enters cells carrying OVA model antigens, which enables efficient activation of adaptive immunity in vitro and in vivo. In OVAexpressing tumor allograft models, both prophylactic and therapeutic vaccinations significantly retard tumor growth and prolong animal survival. Furthermore, the vaccinations were also able to reduce lung metastasis in a B16F10-OVA model.

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Background: Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of cancer. The aim of this study was to develop novel risk classifiers to predict the risk of irAEs and probability of clinical benefits of these individuals. Methods: The cancer patients received ICIs from the First Affiliated Hospital of Xi 'an Jiaotong University from November 2020 to October 2022 were collected and followed up. The logistic regression analyses were adopted to identify independent predictive factors of irAEs and clinical response. Two nomograms were developed to predict the irAEs and clinical response of these individuals, with receiver operating characteristic curve (ROC) and calibration curve being generated to assess their predictive ability. Besides, decision curve analysis (DCA) was performed to estimate the clinical utility of the nomograms. Results: This study included 583 cancer patients from 2434 cancer patients. Among them, 111 patients (19.0%) developed irAEs. The multivariate analysis indicated that duration of treatment (DOT)＞3 cycles, Hepatic-metastases, IL2＞2.225pg/ml, and IL8＞7.39pg/ml were correlated with higher irAEs risk. Overall, 347 patients were included in the final efficacy analysis, with an overall clinical benefit rate of 39.7% being observed. The multivariate analysis indicated that DOT＞3cycles, non-hepatic-metastases, irAEs and IL8＞7.39pg/ml were independent predictive factors of clinical benefit. Ultimately, two nomograms were successfully established to predict the probability of irAEs and clinical benefits. ROC curves yield acceptable performance of nomograms. Calibration curves showed satisfying consistencies between actual and predicted probability. DCA supported that the nomograms could provide more significant net clinical benefits to these patients. Conclusion: Specific baseline serum cytokines are closely correlated to irAEs and clinical response in these individuals. We established two nomograms that could effectively predict the risk of irAEs and probability of clinical response by integration of common clinicopathological parameters and serumcytokines.

Immune checkpoint inhibitors (ICIs) have revolutionized the therapeutic landscape of cancer therapy. This study aimed to develop novel risk classifiers to predict the risk of immune-related adverse events (irAEs) and the probability of clinical benefits. Patients with cancer who received ICIs from the First Affiliated Hospital of Xi 'an Jiaotong University from November 2020 to October 2022 were recruited and followed up. Logistic regression analyses were performed to identify independent predictive factors for irAEs and clinical response. Two nomograms were developed to predict the irAEs and clinical responses of these individuals, with a receiver operating characteristic curve to assess their predictive ability. Decision curve analysis was performed to estimate the clinical utility of the nomogram. This study included 583 patients with cancer. Among them, 111 (19.0%) developed irAEs. Duration of treatment (DOT) > 3 cycles, hepatic-metastases, IL2 > 2.225 pg/mL, and IL8 > 7.39 pg/mL were correlated with higher irAEs risk. A total of 347 patients were included in the final efficacy analysis, with an overall clinical benefit rate of 39.7%. DOT > 3 cycles, nonhepatic-metastases, and irAEs and IL8 > 7.39 pg/mL were independent predictive factors of clinical benefit. Ultimately, 2 nomograms were successfully established to predict the probability of irAEs and their clinical benefits. Ultimately, 2 nomograms were successfully established to predict the probability of irAEs and clinical benefits. The receiver operating characteristic curves yielded acceptable nomogram performance. Calibration curves and decision curve analysis supported the hypothesis that nomograms could provide more significant net clinical benefits to these patients. Specific baseline plasma cytokines were closely correlated with irAEs and clinical responses in these individuals.