This paper investigates the C-logit stochastic user equilibrium (SUE) problem on a bimodal transportation network with road and rail travel modes. The C-logit model captures the overlapping effect among the different paths via commonality factors; sequentially, it has ability to obtain a more realistic traffic flow distribution pattern. In this paper, when we redefine the link travel cost functions and employ a binary Logit model for the mode split, the bimodal C-logit SUE model can be simplified into an unconstrained nonlinear mathematical programming formulation. Such model is verified to satisfy the bimodal C-logit SUE conditions at its stationary point and can be solved by existing algorithms. So, the simplified model can be convenient to be used on the general bimodal transportation network.
Purpose Anti-viral and anti-inflammatory therapies were effective in altering virus repletion and immune dysregulation in Coronavirus Disease 2019 (COVID-19) patients. This study aimed to explore the effect of combination therapy on disease progression in a real-world setting. Patients and Methods A total of 836 patients confirmed with SARS-CoV-2 infection participated in the study from 15 November to 25 December 2022 at Beijing Youan Hospital, Capital Medical University. A prospective cohort study was implemented to investigate the prognostic effect of the combination therapy on virus shedding and clinical recovery. Results About 78% of patients used nirmatrelvir/ritonavir (N/R, Paxlovid ® , Pfizer) negatively, 16% of patients were prescribed nirmatrelvir/ritonavir beyond five days of symptom onset, 4% of patients received N/R monotherapy within five days of symptom onset and 2% of patients received N/R combined with dexamethasone. Compared with untreated patients, N/R monotherapy reduced the median time to 10.0 days from 12.0 days according to the negative conversion of nucleic acid amplification test (NAAT), and combination therapy reduced the time to 7.0 days, and increased to a 1.99 (95% CI 0.92, 4.32) and 14.23-fold (95% CI 4.50, 44.95) probability of negative NAAT, respectively. N/R monotherapy reduced the clinical recovery time to 10.0 days from 13.0 days. Single-use and combined-use non-significantly increased the recovery probability by 61% and 69%, respectively. In mild and moderate patients, the HRs for clinical recovery increased to 1.69 (95% CI 0.73, 3.94) and 2.18 (95% CI 0.29, 16.62), respectively. Conclusion Combination therapy of N/R and dexamethasone increased negative conversion of NAAT and was associated with a non-significant improvement in clinical recovery. Further studies are warranted to confirm this efficacy.
The 5-year recurrence rate of thermal ablation for hepatocellular carcinoma (HCC) is high, and whether this treatment strategy induces systemic immune response remains elusive. This study aimed to investigate the effects of thermal ablation on HCC patients’ cytokine profiles and to explore the correlation of cytokine profiles with tumor recurrence after ablation. A total of 22 HCC patients were included in this prospective study. The levels of 27 cytokines in the peripheral blood of HCC patients were measured before ablation (baseline), week 1, and week 4 after ablation using a Bio-Plex Pro Human Cytokine 27-plex Assay kit. Cytokines showed different dynamic changing trends after ablation treatment. It was found that the level of IL-6 was significantly elevated at week 1 and returned to the baseline level at week 4 after ablation. The level of IL-10 was slightly reduced at week 1 and significantly decreased at week 4. The levels of MCP-1, macrophage inflammatory protein-1β (MIP-1β), and TNF-α were similarly reduced at week 1 and increased at week 4. The levels of IL-17, platelet-derived growth factor-BB (PDGF-BB), and regulated upon activation, normal T cell expressed and secreted (RANTES) showed little to no change at week 1 while an observable increase at week 4. Patients with a high IL-10 level (2.99 pg/ml) at baseline and low levels of TNF-α (20.4 pg/ml), PDGF-BB (107.78 pg/ml), and RANTES (2303.94 pg/ml) at week 4 were at risk of tumor recurrence during 1-year follow-up. The results suggested that thermal ablation activated systemic immune responses by changing the levels of cytokines. The results also demonstrated that measurement of IL-10 at baseline, TNF-α, PDGF-BB, and RANTES at week 4 after ablation might predict the risk of tumor recurrence.
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