Cancer immunotherapy is emerging as a promising treatment modality that suppresses and eliminates tumors by re-activating and maintaining the tumor-immune cycle, and further enhancing the body's anti-tumor immune response.

Radiation for Graves’ ophthalmopathy (GO) has traditionally utilized lateral opposing fields (LOF) or three-dimensional conformal radiotherapy (3DCRT) technique. The current study was conducted to report clinical outcomes and therapeutic effects of intensity modulated radiation therapy (IMRT) in treating GO patients. One hundred sixteen patients with GO were treated with IMRT as initial local therapy between July 2010 and August 2013, with a median follow-up of 62 months (range 45–81 months). Radiotherapy dose was 20 Gy in 10 fractions within two to three weeks. The immediate and long-term response to IMRT was evaluated in GO severity score and in each category of symptoms. Acute and long-term complications were recorded to assess its safety. Symptom severity score significantly fell from the start of treatment to 4- or 6- month post-IMRT (P < 0.01). In total, 85 patients (73.3%) experienced improvement of GO symptoms in the first half-year, and only 4 of them (4.7%) suffered recurrence of the GO symptoms during the subsequent follow-ups. Orbital pain, tearing and extraocular muscle dysfunction had the best treatment reaction to IMRT, while proptosis and blurred vision were the most refractory symptoms. Acute complications were slight and self-limited, mainly including intermittent eye redness in 9 patients (7.8%), sideburns hair loss in 19 patients (16.4%), increased milphosis or madarosis in 23 patients (19.8%) and pseudo-progression of GO symptoms in 15 patients (12.9%). For long-term complications, chronic xerophthalmias occurred in 7 patients (6.03%), cataract developed in 2 patients (1.72%), and all were well-managed by medical interventions. Radiation retinopathy and secondary malignancy was not presented in the cohort. The study demonstrated that IMRT could serve as a viable option in treating GO patients, with a satisfactory symptom control ability, and relatively slight and acceptable post-radiotherapeutic complications.

In many fields, the issue of solving the time-varying Sylvester equation (TVSE) is commonly encountered. Consequently, finding its exact solution has become a research hotspot. In general, the ZNN and IEZNN models are the most useful algorithms that are frequently utilized to solve the TVSE problem. However, the ZNN model is borned with noise susceptibility and the IEZNN model loses the adaptive performance due to its constant coefficient in solving the TVSE problem. In this paper, a residual error feedback zeroing neural network (REFZNN) is proposed to adaptively solve the TVSE problem. The REFZNN model feeds back the residual error to the solustion system, which forms a feedback regulation to reduce the residual error between the system output and the system target. Then, the convergence and noise patience of the REFZNN model are proved by theoretical analyses. Finally, the validity of the proposed model is verified by designing computer simulation experiments and its superiority is confirmed by the performance comparisons with the ZNN and IEZNN models.